From 32ce5d54a78a8b16a1532a74e4c3e4c9404366a8 Mon Sep 17 00:00:00 2001 From: gspark Date: Sat, 24 Oct 2026 04:35:49 +0900 Subject: [PATCH 1/2] fix: import dense KV into hybrid GPU cache groups (#258) --- .../pd/http_matrix/.research/events.jsonl | 1 + opt_prime/examples/pd/http_matrix/STATUS.md | 2 + .../evidence258/dense258-focused-b.log | 15 + .../evidence258/dense258-focused.log | 109 + .../http_matrix/evidence258/dense258-full.log | 21 + .../http_matrix/evidence258/dense258-red.log | 132 + .../evidence258/local201-gemma-matrix-a.json | 8397 +++++++++++++++++ .../local201-gemma-matrix-a.server0.log | 24 + .../experiments/2026-10-24-dense-hybrid258.md | 30 + opt_prime/opt_prime/accel/pd/paged.py | 30 +- opt_prime/tests/test_pd_dense_hybrid.py | 65 + 11 files changed, 8820 insertions(+), 6 deletions(-) create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/dense258-focused-b.log create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/dense258-focused.log create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/dense258-full.log create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/dense258-red.log create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.json create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.server0.log create mode 100644 opt_prime/examples/pd/http_matrix/experiments/2026-10-24-dense-hybrid258.md create mode 100644 opt_prime/tests/test_pd_dense_hybrid.py diff --git a/opt_prime/examples/pd/http_matrix/.research/events.jsonl b/opt_prime/examples/pd/http_matrix/.research/events.jsonl index 5f51c17b..0724aacb 100644 --- a/opt_prime/examples/pd/http_matrix/.research/events.jsonl +++ b/opt_prime/examples/pd/http_matrix/.research/events.jsonl @@ -3,3 +3,4 @@ {"id": "4c7935b757264687b1310fbe1ec6399a", "ts": "2026-10-23T21:26:38+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Production factory union of generation-config/tokenizer EOS fixes real KONI HTTP turn end: baseline length, fixed stop, ignore_eos length, streaming stop, reuse stop. Baseline factory3fail/3pass ->22related tests pass. Preserved failed initial SSE checker log.", "next": "Publish scoped serving fix; verify NPU HTTP and retain long RNGD semantic validation.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "KONI-8B", "backend": "gpu", "max_tokens": "8"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-http-final.json", "size": 5067, "sha256": "d5be9a4a52a6485f"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} {"id": "e4993823527144b5a14e6441b1cd5c01", "ts": "2026-10-23T21:29:56+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Published production EOS fix and real KONI HTTP evidence in draft PR230 (e5fa087). Final factory/streaming/sampling/batched suite22passed; hardware checker5/5 cases passed; changed files sensitive-clean,4unchanged baseline findings in this branch.", "next": "Verify same HTTP factory on NPU; continue full four-model long semantic and heterogeneous PD validation.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "gpu"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-http-final.json", "size": 5067, "sha256": "d5be9a4a52a6485f"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} {"id": "328b8349e9974a059ddc7e1a8a485e2c", "ts": "2026-10-23T21:32:23+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Real ATOM KONI HTTP also passes5/5 baseline/fixed/ignore/stream/reuse checks using same production factory: config-only length vs union stop. GPU+ATOM now10/10 expected outcomes; no SDK/artifact rebuild.", "next": "Update PR230 with NPU evidence; finish KONI medium-context RNGD handoff and broader PD work.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "atom", "kv_blocks": "1"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-atom-http.json", "size": 5199, "sha256": "4735255db379ff00"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} +{"id": "1020452aea8445f080108c1ed7f6d643", "ts": "2026-10-24T04:35:37+09:00", "task": "Dense hybrid GPU KV import (aicomp #258)", "result": "Dense hybrid receiver fix:31focused and505full CPU tests passed,34skipped,253subtests,151.69s. Preparing isolated PR and fresh Gemma live rerun; hardware and numerical acceptance not yet claimed.", "next": "Run corrected Gemma RNGD/GPU matrix preserving original failure; complete lifecycle and numerical checks", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {}, "artifacts": [], "experiments": ["experiments/2026-10-24-dense-hybrid258.md"], "labels": ["bug"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md index ce8ca12f..eb3dbbd6 100644 --- a/opt_prime/examples/pd/http_matrix/STATUS.md +++ b/opt_prime/examples/pd/http_matrix/STATUS.md @@ -37,3 +37,5 @@ A real terminated subprocess producer previously left /ready200 and new requests ## Batched producer timing (#249) Candidate exports airm_pd_producer_seconds_total{stage="prefill"|"transfer"} from existing accumulated batcher durations. Repeated scrapes do not add observations; missing timing keys are omitted. Tiny real-model admission test covers fixed worker-reported durations and legacy omissions. These counters are worker-reported admitted-handoff sums, not request latency or proof of zero cost for workers that do not measure stages. Full CPU suite:467passed,17skipped,135subtests,1existing warning. See pd-stage-metrics249 experiment. + +#258 dense hybrid KV: actual Gemma failure reproduced; mapping/group validation corrected.31focused and505full CPU tests pass; live rerun pending. diff --git a/opt_prime/examples/pd/http_matrix/evidence258/dense258-focused-b.log b/opt_prime/examples/pd/http_matrix/evidence258/dense258-focused-b.log new file mode 100644 index 00000000..7864cb60 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/dense258-focused-b.log @@ -0,0 +1,15 @@ +............................... [100%] +=============================== warnings summary =============================== +tests/test_pd_dense_hybrid.py::test_dense_gemma_pd_matches_independent_hf_beyond_window + /home/gspark/venvs/pt213/lib/python3.10/site-packages/torch/nn/attention/flex_attention.py:2481: UserWarning: flex_attention called without torch.compile() - this will use an unfused implementation that materializes the full scores matrix instead of generating a fused kernel. + + SOLUTION: Use torch.compile(flex_attention)(...) + + If you want to debug your score_mod/mask_mod, you can set: + torch.nn.attention.flex_attention._FLEX_ATTENTION_DISABLE_COMPILE_DEBUG = True + + This will allow you to use print statements or breakpoints. Note: This doesn't work with the backwards pass and may produce incorrect results. + _warn_once( + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +31 passed, 1 warning in 29.86s diff --git a/opt_prime/examples/pd/http_matrix/evidence258/dense258-focused.log b/opt_prime/examples/pd/http_matrix/evidence258/dense258-focused.log new file mode 100644 index 00000000..755579d0 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/dense258-focused.log @@ -0,0 +1,109 @@ +............FF................ [100%] +=================================== FAILURES =================================== +_________________ test_recurrent_pd_hands_over_state[qwen3_5] __________________ + +make = + + @RECURRENT + def test_recurrent_pd_hands_over_state(make): + model = make() + engine = TorchPrefillEngine(copy.deepcopy(model), max_context=128, chunk=8, page_size=8, prefix_cache=False) + b = PDBatcher(model, PrefillWorker(engine), slots=2, max_context=128, page_size=8) + prompts = _prompts(4, 6, 30, seed=4) + fs = [b.submit(PDRequest(f"p{i}", p, 12)) for i, p in enumerate(prompts)] +> b.run_until_idle() + +tests/test_pd_hybrid.py:157: +_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ +opt_prime/accel/pd/batching.py:207: in run_until_idle + self.step() +opt_prime/accel/pd/pd_batching.py:468: in step + self._admit_prefilled(block=not self.decoding) +opt_prime/accel/pd/pd_batching.py:497: in _admit_prefilled + self.kv.write_span(r.slot, out.start, out.keys, out.values) +_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ + +self = , slot = 0 +start = 0 +keys = tensor([[[[-0.0660, 2.0859, 0.4345, -1.4313, 0.4459, -0.0251, -0.4985, + -1.7052, -1.7932, 0.2561, 1.213...26, -0.4552, + -0.7853, 0.2788, -2.0608, -0.8472, -0.4423, -0.3608, 1.5063, + -1.4844, 0.3283]]]]) +values = tensor([[[[-2.4548e-01, -2.1482e-01, 7.9515e-03, 2.1531e-01, -9.8814e-03, + -1.9493e-02, -1.3410e-01, 1.33...3, -3.6229e-02, + -1.5983e-01, 8.6865e-02, 1.8228e-01, 1.4877e-02, -7.5556e-02, + 2.9426e-01]]]]) + + def write_span(self, slot, start, keys, values): + """keys/values [layers, kv_heads, n, head_dim] for positions start .. start+n of `slot` (a list of those, one + per KV group, for hybrid models), each group in one indexed copy (the PD admission of KV that another engine + prefilled)""" + if isinstance(keys, torch.Tensor) and isinstance(values, torch.Tensor): + layers = max(self.layer_group) + 1 + if keys.ndim != 4 or values.shape != keys.shape or keys.shape[0] != layers: +> raise ValueError("dense KV span must contain every model layer with matching K/V shapes") +E ValueError: dense KV span must contain every model layer with matching K/V shapes + +opt_prime/accel/pd/paged.py:454: ValueError +_______________ test_recurrent_pd_hands_over_state[qwen3_5_moe] ________________ + +make = + + @RECURRENT + def test_recurrent_pd_hands_over_state(make): + model = make() + engine = TorchPrefillEngine(copy.deepcopy(model), max_context=128, chunk=8, page_size=8, prefix_cache=False) + b = PDBatcher(model, PrefillWorker(engine), slots=2, max_context=128, page_size=8) + prompts = _prompts(4, 6, 30, seed=4) + fs = [b.submit(PDRequest(f"p{i}", p, 12)) for i, p in enumerate(prompts)] +> b.run_until_idle() + +tests/test_pd_hybrid.py:157: +_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ +opt_prime/accel/pd/batching.py:207: in run_until_idle + self.step() +opt_prime/accel/pd/pd_batching.py:468: in step + self._admit_prefilled(block=not self.decoding) +opt_prime/accel/pd/pd_batching.py:497: in _admit_prefilled + self.kv.write_span(r.slot, out.start, out.keys, out.values) +_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ + +self = , slot = 0 +start = 0 +keys = tensor([[[[-1.3119e+00, -4.6383e-02, 4.9614e-01, -9.4488e-01, -4.3832e-01, + 2.6910e-01, 6.3046e-01, -1.59...1, 1.3446e+00, + 4.5665e-01, 1.3538e-01, 3.4665e-01, -1.7604e-01, -2.0072e-02, + -1.5641e+00]]]]) +values = tensor([[[[-3.2685e-01, 2.6668e-01, 4.5333e-03, 7.0952e-02, 1.8279e-01, + 2.7009e-01, 1.4598e-01, 2.43...2, -9.8851e-02, + -5.3184e-02, -4.8559e-02, 9.7567e-02, 8.8385e-02, 8.4103e-02, + -3.2886e-02]]]]) + + def write_span(self, slot, start, keys, values): + """keys/values [layers, kv_heads, n, head_dim] for positions start .. start+n of `slot` (a list of those, one + per KV group, for hybrid models), each group in one indexed copy (the PD admission of KV that another engine + prefilled)""" + if isinstance(keys, torch.Tensor) and isinstance(values, torch.Tensor): + layers = max(self.layer_group) + 1 + if keys.ndim != 4 or values.shape != keys.shape or keys.shape[0] != layers: +> raise ValueError("dense KV span must contain every model layer with matching K/V shapes") +E ValueError: dense KV span must contain every model layer with matching K/V shapes + +opt_prime/accel/pd/paged.py:454: ValueError +=============================== warnings summary =============================== +tests/test_pd_hybrid.py::test_batched_beyond_window_matches_hf[gemma3] + /home/gspark/venvs/pt213/lib/python3.10/site-packages/torch/nn/attention/flex_attention.py:2481: UserWarning: flex_attention called without torch.compile() - this will use an unfused implementation that materializes the full scores matrix instead of generating a fused kernel. + + SOLUTION: Use torch.compile(flex_attention)(...) + + If you want to debug your score_mod/mask_mod, you can set: + torch.nn.attention.flex_attention._FLEX_ATTENTION_DISABLE_COMPILE_DEBUG = True + + This will allow you to use print statements or breakpoints. Note: This doesn't work with the backwards pass and may produce incorrect results. + _warn_once( + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +=========================== short test summary info ============================ +FAILED tests/test_pd_hybrid.py::test_recurrent_pd_hands_over_state[qwen3_5] +FAILED tests/test_pd_hybrid.py::test_recurrent_pd_hands_over_state[qwen3_5_moe] +2 failed, 28 passed, 1 warning in 26.53s diff --git a/opt_prime/examples/pd/http_matrix/evidence258/dense258-full.log b/opt_prime/examples/pd/http_matrix/evidence258/dense258-full.log new file mode 100644 index 00000000..8dacb4f1 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/dense258-full.log @@ -0,0 +1,21 @@ +.sssssss.....................ssssssssss.....................................................s..... [ 18%] +........................................................s.s............. [ 31%] +....ss.....................ss....s...................................... [ 45%] +........................................................................ [ 58%] +....s.s...........................................s..................... [ 72%] +................................................................... [ 84%] +s.s...........................................................................s.... [100%] +=============================== warnings summary =============================== +tests/test_kvstore.py::test_second_engine_reuses_chunks_from_the_store[lmcache] + /home/gspark/venvs/pt213/lib/python3.10/site-packages/torch/nn/attention/flex_attention.py:2481: UserWarning: flex_attention called without torch.compile() - this will use an unfused implementation that materializes the full scores matrix instead of generating a fused kernel. + + SOLUTION: Use torch.compile(flex_attention)(...) + + If you want to debug your score_mod/mask_mod, you can set: + torch.nn.attention.flex_attention._FLEX_ATTENTION_DISABLE_COMPILE_DEBUG = True + + This will allow you to use print statements or breakpoints. Note: This doesn't work with the backwards pass and may produce incorrect results. + _warn_once( + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +505 passed, 34 skipped, 1 warning, 253 subtests passed in 151.69s (0:02:31) diff --git a/opt_prime/examples/pd/http_matrix/evidence258/dense258-red.log b/opt_prime/examples/pd/http_matrix/evidence258/dense258-red.log new file mode 100644 index 00000000..adaedfa1 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/dense258-red.log @@ -0,0 +1,132 @@ +FFF [100%] +=================================== FAILURES =================================== +______________ test_dense_span_maps_model_layers_at_nonzero_start ______________ + + def test_dense_span_maps_model_layers_at_nonzero_start(): + cache = pool() + keys = torch.arange(30).reshape(3, 1, 5, 2).float() +> cache.write_span(0, 3, keys, keys + 100) + +tests/test_pd_dense_hybrid.py:19: +_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ + +self = , slot = 0 +start = 3 +keys = [tensor([[[[ 0., 1.], + [ 2., 3.], + [ 4., 5.], + [ 6., 7.], + [ 8., 9.]]], + + + ...]], + + + [[[20., 21.], + [22., 23.], + [24., 25.], + [26., 27.], + [28., 29.]]]])] +values = [tensor([[[[100., 101.], + [102., 103.], + [104., 105.], + [106., 107.], + [108., 109.... [[[120., 121.], + [122., 123.], + [124., 125.], + [126., 127.], + [128., 129.]]]])] + + def write_span(self, slot, start, keys, values): + """keys/values [layers, kv_heads, n, head_dim] for positions start .. start+n of `slot` (a list of those, one + per KV group, for hybrid models), each group in one indexed copy (the PD admission of KV that another engine + prefilled)""" + keys = keys if isinstance(keys, (list, tuple)) else [keys] + values = values if isinstance(values, (list, tuple)) else [values] + idx = self.span_index(slot, start, start + keys[0].shape[2]) + for pk, pv, k, v in zip(self.gk, self.gv, keys, values): +> pk[:, :, idx] = k.to(self.device, pk.dtype, non_blocking=True) +E RuntimeError: shape mismatch: value tensor of shape [3, 1, 5, 2] cannot be broadcast to indexing result of shape [2, 1, 5, 2] + +opt_prime/accel/pd/paged.py:455: RuntimeError +______ test_invalid_grouped_span_rejected_before_any_write[missing_group] ______ + +bad = 'missing_group' + + @pytest.mark.parametrize('bad', ['missing_group', 'bad_later_shape']) + def test_invalid_grouped_span_rejected_before_any_write(bad): + cache = pool() + keys = [torch.ones(2, 1, 5, 2), torch.ones(1, 1, 5, 2)] + values = [x + 1 for x in keys] + if bad == 'missing_group': + keys, values = keys[:1], values[:1] + else: + values[1] = torch.ones(1, 1, 4, 2) +> with pytest.raises(ValueError): +E Failed: DID NOT RAISE ValueError + +tests/test_pd_dense_hybrid.py:37: Failed +_____ test_invalid_grouped_span_rejected_before_any_write[bad_later_shape] _____ + +bad = 'bad_later_shape' + + @pytest.mark.parametrize('bad', ['missing_group', 'bad_later_shape']) + def test_invalid_grouped_span_rejected_before_any_write(bad): + cache = pool() + keys = [torch.ones(2, 1, 5, 2), torch.ones(1, 1, 5, 2)] + values = [x + 1 for x in keys] + if bad == 'missing_group': + keys, values = keys[:1], values[:1] + else: + values[1] = torch.ones(1, 1, 4, 2) + with pytest.raises(ValueError): +> cache.write_span(0, 0, keys, values) + +tests/test_pd_dense_hybrid.py:38: +_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ + +self = , slot = 0 +start = 0 +keys = [tensor([[[[1., 1.], + [1., 1.], + [1., 1.], + [1., 1.], + [1., 1.]]], + + + [[[1.... [1., 1.]]]]), tensor([[[[1., 1.], + [1., 1.], + [1., 1.], + [1., 1.], + [1., 1.]]]])] +values = [tensor([[[[2., 2.], + [2., 2.], + [2., 2.], + [2., 2.], + [2., 2.]]], + + + [[[2.... [2., 2.], + [2., 2.]]]]), tensor([[[[1., 1.], + [1., 1.], + [1., 1.], + [1., 1.]]]])] + + def write_span(self, slot, start, keys, values): + """keys/values [layers, kv_heads, n, head_dim] for positions start .. start+n of `slot` (a list of those, one + per KV group, for hybrid models), each group in one indexed copy (the PD admission of KV that another engine + prefilled)""" + keys = keys if isinstance(keys, (list, tuple)) else [keys] + values = values if isinstance(values, (list, tuple)) else [values] + idx = self.span_index(slot, start, start + keys[0].shape[2]) + for pk, pv, k, v in zip(self.gk, self.gv, keys, values): + pk[:, :, idx] = k.to(self.device, pk.dtype, non_blocking=True) +> pv[:, :, idx] = v.to(self.device, pv.dtype, non_blocking=True) +E RuntimeError: shape mismatch: value tensor of shape [4, 2] cannot be broadcast to indexing result of shape [1, 1, 5, 2] + +opt_prime/accel/pd/paged.py:456: RuntimeError +=========================== short test summary info ============================ +FAILED tests/test_pd_dense_hybrid.py::test_dense_span_maps_model_layers_at_nonzero_start +FAILED tests/test_pd_dense_hybrid.py::test_invalid_grouped_span_rejected_before_any_write[missing_group] +FAILED tests/test_pd_dense_hybrid.py::test_invalid_grouped_span_rejected_before_any_write[bad_later_shape] +3 failed in 2.48s diff --git a/opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.json b/opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.json new file mode 100644 index 00000000..6deb6f56 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.json @@ -0,0 +1,8397 @@ +{ + "passed": false, + "model": "Gemma3-1B", + "mode": "pd", + "dtype": "bfloat16", + "torch": "2.13.0+cu130", + "transformers": "5.15.0", + "replicas": 1, + "cpu_threads_per_server": 4, + "prompts": { + "128": [ + 2, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 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"cfd4821e2a2112f3fcf7f242f3e76efe47134640e4bf22b3b63fb808be6148f0", + "startup_timeout_s": 1800, + "timing_scope": "Client first SSE event, full response e2e and estimated TPOT=(e2e-first_event)/(output_tokens-1). SSE can coalesce tokens; this is not per-token kernel timing. Loading/warmup/correctness checks excluded.", + "physical_gpus": 1, + "physical_rngd": 1, + "physical_atom": 0, + "slots_per_decoder": 4, + "producer_cache": false, + "decoder_cache": false, + "producer_chunk": 8192, + "local_chunk": 256, + "context": 9216, + "server_config": { + "servers": [ + [ + "/home/gspark/venvs/pt213/bin/python", + "-c", + "import sys,importlib.util,runpy\ns=importlib.util.spec_from_file_location('opt_prime.accel.serve.llmd','/tmp/llmd240.py')\nm=importlib.util.module_from_spec(s);sys.modules[s.name]=m;s.loader.exec_module(m)\nrunpy.run_path('/home/gspark/workspace/aicomp-atom-prefetch-253/opt_prime/examples/pd/serve_batched.py',run_name='__main__')\n", + "--model", + "/tmp/serving-matrix-models/Gemma3-1B", + "--device", + "cuda:0", + "--dtype", + "bfloat16", + "--slots", + "4", + "--max-context", + "9216", + "--max-output", + "128", + "--kv", + "paged", + "--page-size", + "64", + "--chunk", + "256", + "--port", + "{port}", + "--pd-prefill-python", + "/tmp/rngd-gpu201-src/python-worker.sh", + "--pd-prefill-args", + "--width 8192 --engine-factory gemma_prefill:Prefill" + ] + ], + "metadata": { + "physical_gpus": 1, + "physical_rngd": 1, + "physical_atom": 0, + "slots_per_decoder": 4, + "producer_cache": false, + "decoder_cache": false, + "producer_chunk": 8192, + "local_chunk": 256, + "context": 9216 + } + }, + "load_s": 677.6346402899944, + "error": "" +} diff --git a/opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.server0.log b/opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.server0.log new file mode 100644 index 00000000..9d22f638 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/local201-gemma-matrix-a.server0.log @@ -0,0 +1,24 @@ + +Loading weights: 0%| | 0/340 [00:00", line 4, in + File "/usr/lib/python3.10/runpy.py", line 289, in run_path + return _run_module_code(code, init_globals, run_name, + File "/usr/lib/python3.10/runpy.py", line 96, in _run_module_code + _run_code(code, mod_globals, init_globals, + File "/usr/lib/python3.10/runpy.py", line 86, in _run_code + exec(code, run_globals) + File "/home/gspark/workspace/aicomp-atom-prefetch-253/opt_prime/examples/pd/serve_batched.py", line 152, in + owner.run() # owner loop on the main thread + File "/home/gspark/workspace/aicomp-atom-prefetch-253/opt_prime/opt_prime/accel/serve/batched.py", line 217, in run + b.step() + File "/home/gspark/workspace/aicomp-atom-prefetch-253/opt_prime/opt_prime/accel/pd/pd_batching.py", line 468, in step + self._admit_prefilled(block=not self.decoding) + File "/home/gspark/workspace/aicomp-atom-prefetch-253/opt_prime/opt_prime/accel/pd/pd_batching.py", line 497, in _admit_prefilled + self.kv.write_span(r.slot, out.start, out.keys, out.values) + File "/home/gspark/workspace/aicomp-atom-prefetch-253/opt_prime/opt_prime/accel/pd/paged.py", line 455, in write_span + pk[:, :, idx] = k.to(self.device, pk.dtype, non_blocking=True) +RuntimeError: shape mismatch: value tensor of shape [26, 1, 128, 256] cannot be broadcast to indexing result of shape [22, 1, 128, 256] +/usr/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 1 leaked shared_memory objects to clean up at shutdown + warnings.warn('resource_tracker: There appear to be %d ' diff --git a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-dense-hybrid258.md b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-dense-hybrid258.md new file mode 100644 index 00000000..c1803cab --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-dense-hybrid258.md @@ -0,0 +1,30 @@ +# Dense subprocess KV import into hybrid GPU pools + +- **Date**: 2026-10-24 +- **Task**: aicomp #258; four-model serving matrix #201 +- **Host / device**: GPU+RNGD host; CPU regression tests, Torch2.13.0+cu130 +- **Commit**: base273952a plus uncommitted fix/258-dense-hybrid-kv + +## Question +Why does live Gemma RNGD-to-GPU fail on its first request despite grouped Torch producer tests passing? + +## Setup +Actual runtime3e16c33, Gemma3-1B26layers,22sliding/4global, BF16, fourGPUslots/context9216/page64/cacheoff, RNGDwidth8192. First128-token request sends dense[26,1,128,256] KV; write_span incorrectly treats it as first group[22,1,128,256] and owner exits. Original local201-gemma-matrix-a.json and server log retained. Zero completed performance batches; deferred fault queue correctly stopped. Remote ATOM run is independent and unchanged. + +Fix maps dense model-layer spans into receiver groups, preserves grouped and single-group/recurrent formats, and validates all group shapes/counts before writes. Protocol unchanged. + +## Command +From aicomp-dense-hybrid-258/opt_prime: +```bash +OMP_NUM_THREADS=2 MKL_NUM_THREADS=2 PYTHONPATH=. /home/gspark/venvs/pt213/bin/python -m pytest -q tests/test_pd_dense_hybrid.py +OMP_NUM_THREADS=2 MKL_NUM_THREADS=2 PYTHONPATH=. /home/gspark/venvs/pt213/bin/python -m pytest -q tests/test_pd_dense_hybrid.py tests/test_pd_hybrid.py tests/test_pd_batching_disagg.py +CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=2 MKL_NUM_THREADS=2 PYTHONPATH=. /home/gspark/venvs/pt213/bin/python -m pytest -q +``` + +## Results +Initial shell test-file path was incorrect; no tests ran. Corrected path before RED run. +RED:3tests fail: dense mapping shape mismatch, missing group silently accepted, malformed later-group write not validated atomically. First fix run28pass/2fail exposed single-group recurrent compatibility regression; preserved existing single-group tensor semantics. Added actual tiny Gemma dense producer->PDBatcher comparison against independent full-HF greedy beyond sliding window. +Focused rerun:31passed,1existing flex-attention warning,29.86s. Logs /tmp/dense258-red.log, /tmp/dense258-focused.log, /tmp/dense258-focused-b.log. Full regression:505passed,34skipped,253subtests passed,1existing warning,151.69s; log /tmp/dense258-full.log. + +## Conclusion +Cause reproduced and focused correction passes. Hardware rerun and publication remain; no claim that numerical parity or live Gemma serving is fixed yet. diff --git a/opt_prime/opt_prime/accel/pd/paged.py b/opt_prime/opt_prime/accel/pd/paged.py index a9b0bf5c..80c235b7 100644 --- a/opt_prime/opt_prime/accel/pd/paged.py +++ b/opt_prime/opt_prime/accel/pd/paged.py @@ -445,12 +445,30 @@ def span_index(self, slot, start, end): return self.physical([slot] * (end - start), torch.arange(start, end, device=self.device)) def write_span(self, slot, start, keys, values): - """keys/values [layers, kv_heads, n, head_dim] for positions start .. start+n of `slot` (a list of those, one - per KV group, for hybrid models), each group in one indexed copy (the PD admission of KV that another engine - prefilled)""" - keys = keys if isinstance(keys, (list, tuple)) else [keys] - values = values if isinstance(values, (list, tuple)) else [values] - idx = self.span_index(slot, start, start + keys[0].shape[2]) + """Import [layers, kv_heads, n, head_dim] KV at `start`: either model-layer order for uniform geometry, + or one tensor per receiver group. Hybrid dense inputs are split by model-layer indices; grouped inputs + also support differing head geometries. Validate all shapes before copying any group.""" + if isinstance(keys, torch.Tensor) and isinstance(values, torch.Tensor) and len(self.groups) == 1: + keys, values = [keys], [values] + if isinstance(keys, torch.Tensor) and isinstance(values, torch.Tensor): + layers = max(self.layer_group) + 1 + if keys.ndim != 4 or values.shape != keys.shape or keys.shape[0] != layers: + raise ValueError("dense KV span must contain every model layer with matching K/V shapes") + # Subprocess producers export model-layer order; pools group attention geometries. + keys = [keys if g.layers == tuple(range(layers)) else keys[list(g.layers)] for g in self.groups] + values = [values if g.layers == tuple(range(layers)) else values[list(g.layers)] for g in self.groups] + if not isinstance(keys, (list, tuple)) or not isinstance(values, (list, tuple)): + raise ValueError("KV spans must both be dense tensors or grouped sequences") + if len(keys) != len(self.groups) or len(values) != len(self.groups): + raise ValueError("KV span group count must match the receiver") + n = None + for g, k, v in zip(self.groups, keys, values): + if not isinstance(k, torch.Tensor) or not isinstance(v, torch.Tensor) or k.ndim != 4: + raise ValueError("each KV group must contain four-dimensional tensors") + n = k.shape[2] if n is None else n + if k.shape != (len(g.layers), g.kv_heads, n, g.head_dim) or v.shape != k.shape: + raise ValueError("KV span shapes must match receiver groups and share a token count") + idx = self.span_index(slot, start, start + n) for pk, pv, k, v in zip(self.gk, self.gv, keys, values): pk[:, :, idx] = k.to(self.device, pk.dtype, non_blocking=True) pv[:, :, idx] = v.to(self.device, pv.dtype, non_blocking=True) diff --git a/opt_prime/tests/test_pd_dense_hybrid.py b/opt_prime/tests/test_pd_dense_hybrid.py new file mode 100644 index 00000000..a9454acc --- /dev/null +++ b/opt_prime/tests/test_pd_dense_hybrid.py @@ -0,0 +1,65 @@ +"""Dense subprocess KV must preserve model-layer order in grouped GPU pools (#258).""" +import pytest +import torch +from opt_prime.accel.pd.paged import PagedKV +from opt_prime.accel.pd.torch_models import KVGroup + + +def pool(): + groups = (KVGroup('sliding', 4, 1, 2, (0, 2)), KVGroup('full', None, 1, 2, (1,))) + cache = PagedKV(3, 1, 1, 2, torch.float32, 'cpu', pages=4, page_size=4, + max_context=16, groups=groups) + assert cache.alloc(0, 12) == 0 + return cache + + +def test_dense_span_maps_model_layers_at_nonzero_start(): + cache = pool() + keys = torch.arange(30).reshape(3, 1, 5, 2).float() + cache.write_span(0, 3, keys, keys + 100) + idx = cache.span_index(0, 3, 8) + for layer in range(3): + k, v = cache.layer_kv(layer) + torch.testing.assert_close(k[:, idx], keys[layer]) + torch.testing.assert_close(v[:, idx], keys[layer] + 100) + assert all(not x[:, :, :3].any() for x in cache.gk) + + +@pytest.mark.parametrize('bad', ['missing_group', 'bad_later_shape']) +def test_invalid_grouped_span_rejected_before_any_write(bad): + cache = pool() + keys = [torch.ones(2, 1, 5, 2), torch.ones(1, 1, 5, 2)] + values = [x + 1 for x in keys] + if bad == 'missing_group': + keys, values = keys[:1], values[:1] + else: + values[1] = torch.ones(1, 1, 4, 2) + with pytest.raises(ValueError): + cache.write_span(0, 0, keys, values) + assert all(not x.any() for x in cache.gk + cache.gv) + + +def test_dense_gemma_pd_matches_independent_hf_beyond_window(): + from dataclasses import replace + from test_pd_hybrid import _gemma3, _greedy, _prompts + from opt_prime.accel.pd import PDRequest + from opt_prime.accel.pd.pd_batching import TorchPrefillEngine, PrefillWorker, PDBatcher + import copy + + class DenseEngine(TorchPrefillEngine): + def prefill(self, request, send_from=0): + out = super().prefill(request, send_from) + def dense(groups): + by_layer = {layer: span[i] for g, span in zip(self.kv.groups, groups) + for i, layer in enumerate(g.layers)} + return torch.stack([by_layer[i] for i in range(len(by_layer))]) + return replace(out, keys=dense(out.keys), values=dense(out.values)) + + model = _gemma3() + engine = DenseEngine(copy.deepcopy(model), max_context=128, chunk=16, page_size=8) + batcher = PDBatcher(model, PrefillWorker(engine), slots=2, max_context=128, page_size=8, + prefix_cache=False) + prompts = _prompts(3, 25, 40, seed=258) + futures = [batcher.submit(PDRequest(str(i), p, 20)) for i, p in enumerate(prompts)] + batcher.run_until_idle() + assert [f.result() for f in futures] == [_greedy(model, p, 20) for p in prompts] From 32f18ffbe0b54127c7581b0d3d77fe8a41fcb72e Mon Sep 17 00:00:00 2001 From: gspark Date: Sat, 24 Oct 2026 04:41:25 +0900 Subject: [PATCH 2/2] exp: validate live Gemma dense KV fix on RNGD and GPU (#258) --- .../pd/http_matrix/.research/events.jsonl | 1 + opt_prime/examples/pd/http_matrix/STATUS.md | 2 + .../local258-gemma-matrix-b-config.json | 44 + .../local258-gemma-matrix-b-reference.json | 9757 +++++++++++++ .../evidence258/local258-gemma-matrix-b.json | 12006 ++++++++++++++++ .../local258-gemma-matrix-b.server0.log | 3 + .../evidence258/local258-gemma-summary.json | 59 + .../experiments/2026-10-24-dense-hybrid258.md | 21 + 8 files changed, 21893 insertions(+) create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b-config.json create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b-reference.json create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.json create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.server0.log create mode 100644 opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-summary.json diff --git a/opt_prime/examples/pd/http_matrix/.research/events.jsonl b/opt_prime/examples/pd/http_matrix/.research/events.jsonl index 0724aacb..2e372e17 100644 --- a/opt_prime/examples/pd/http_matrix/.research/events.jsonl +++ b/opt_prime/examples/pd/http_matrix/.research/events.jsonl @@ -4,3 +4,4 @@ {"id": "e4993823527144b5a14e6441b1cd5c01", "ts": "2026-10-23T21:29:56+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Published production EOS fix and real KONI HTTP evidence in draft PR230 (e5fa087). Final factory/streaming/sampling/batched suite22passed; hardware checker5/5 cases passed; changed files sensitive-clean,4unchanged baseline findings in this branch.", "next": "Verify same HTTP factory on NPU; continue full four-model long semantic and heterogeneous PD validation.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "gpu"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-http-final.json", "size": 5067, "sha256": "d5be9a4a52a6485f"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} {"id": "328b8349e9974a059ddc7e1a8a485e2c", "ts": "2026-10-23T21:32:23+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Real ATOM KONI HTTP also passes5/5 baseline/fixed/ignore/stream/reuse checks using same production factory: config-only length vs union stop. GPU+ATOM now10/10 expected outcomes; no SDK/artifact rebuild.", "next": "Update PR230 with NPU evidence; finish KONI medium-context RNGD handoff and broader PD work.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "atom", "kv_blocks": "1"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-atom-http.json", "size": 5199, "sha256": "4735255db379ff00"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} {"id": "1020452aea8445f080108c1ed7f6d643", "ts": "2026-10-24T04:35:37+09:00", "task": "Dense hybrid GPU KV import (aicomp #258)", "result": "Dense hybrid receiver fix:31focused and505full CPU tests passed,34skipped,253subtests,151.69s. Preparing isolated PR and fresh Gemma live rerun; hardware and numerical acceptance not yet claimed.", "next": "Run corrected Gemma RNGD/GPU matrix preserving original failure; complete lifecycle and numerical checks", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {}, "artifacts": [], "experiments": ["experiments/2026-10-24-dense-hybrid258.md"], "labels": ["bug"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} +{"id": "551af4e77bca4e67bf0512304142ac48", "ts": "2026-10-24T04:41:11+09:00", "task": "Dense hybrid GPU KV import (aicomp #258)", "result": "Corrected live Gemma completed24batches;20/20token checks and60/60timed texts exact to nativeGPU,84remote/0local/0errors. Shape crash fixed on hardware. Qwen0.6 GPU lifecycle passed; Qwen4 next. Owned ATOM Pod confirmed absent.", "next": "Publish hardware evidence PR259; finish remaining GPU fault coverage and numerical boundary work", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {}, "artifacts": [{"path": "analysis/serving-matrix-201/local258-gemma-summary.json", "size": 1288, "sha256": "3afbcc7e61bb3239"}], "experiments": ["experiments/2026-10-24-dense-hybrid258.md"], "labels": ["bug"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"} diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md index eb3dbbd6..76a8b514 100644 --- a/opt_prime/examples/pd/http_matrix/STATUS.md +++ b/opt_prime/examples/pd/http_matrix/STATUS.md @@ -39,3 +39,5 @@ A real terminated subprocess producer previously left /ready200 and new requests Candidate exports airm_pd_producer_seconds_total{stage="prefill"|"transfer"} from existing accumulated batcher durations. Repeated scrapes do not add observations; missing timing keys are omitted. Tiny real-model admission test covers fixed worker-reported durations and legacy omissions. These counters are worker-reported admitted-handoff sums, not request latency or proof of zero cost for workers that do not measure stages. Full CPU suite:467passed,17skipped,135subtests,1existing warning. See pd-stage-metrics249 experiment. #258 dense hybrid KV: actual Gemma failure reproduced; mapping/group validation corrected.31focused and505full CPU tests pass; live rerun pending. + +#258 corrected live Gemma32ce5d5:24batches,20/20token checks,60/60timed texts exact;84remote/0local/0errors. 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The red box contains apples.", + "text_equal": true, + "first_sse_s": 0.8616885480005294, + "tpot_est_s": 0.022479125580209636, + "e2e_s": 1.5585414409870282 + } + ] + }, + { + "repeat": 0, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.327565315994434, + "output_tok_s": 20.228949620867507, + "median_first_sse_s": 3.1842421285109594, + "median_tpot_est_s": 0.04828712501611951, + "median_e2e_s": 4.712491140031489, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n8192-o32-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 2.391294007014949, + "tpot_est_s": 0.04893068335537288, + "e2e_s": 3.908145191031508 + }, + { + "id": "r0-n8192-o32-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.97719025000697, + "tpot_est_s": 0.04966602706530642, + "e2e_s": 5.516837089031469 + }, + { + "id": "r0-n8192-o32-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 5.586830934975296, + "tpot_est_s": 0.02389118622522801, + "e2e_s": 6.327457707957365 + }, + { + "id": "r0-n8192-o32-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 0.8460470410063863, + "tpot_est_s": 0.047643566676866145, + "e2e_s": 2.3229976079892367 + } + ] + }, + { + "repeat": 1, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 1.6122419649618678, + "output_tok_s": 19.8481373735715, + "median_first_sse_s": 0.8560083319898695, + "median_tpot_est_s": 0.02438926193562727, + "median_e2e_s": 1.6120754519943148, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n8192-o32-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 0.8560083319898695, + "tpot_est_s": 0.02438926193562727, + "e2e_s": 1.6120754519943148 + } + ] + }, + { + "repeat": 1, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.3169962099636905, + "output_tok_s": 20.26279512375008, + "median_first_sse_s": 3.2272187810158357, + "median_tpot_est_s": 0.048546157419613954, + "median_e2e_s": 4.732149661023868, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n8192-o32-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 5.591927806963213, + "tpot_est_s": 0.02338547316274696, + "e2e_s": 6.3168774750083685 + }, + { + "id": "r1-n8192-o32-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 4.008953606011346, + "tpot_est_s": 0.04884064203361049, + "e2e_s": 5.523013509053271 + }, + { + "id": "r1-n8192-o32-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 0.8543014360475354, + "tpot_est_s": 0.04905808441934266, + "e2e_s": 2.375102053047158 + }, + { + "id": "r1-n8192-o32-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 2.4454839560203254, + "tpot_est_s": 0.048251672805617415, + "e2e_s": 3.9412858129944652 + } + ] + }, + { + "repeat": 1, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 0.8204469860065728, + "output_tok_s": 39.00312944746882, + "median_first_sse_s": 0.022432287980336696, + "median_tpot_est_s": 0.02573897038781715, + "median_e2e_s": 0.8203403700026684, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n128-o32-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.022432287980336696, + "tpot_est_s": 0.02573897038781715, + "e2e_s": 0.8203403700026684 + } + ] + }, + { + "repeat": 1, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 0.9248383460217156, + "output_tok_s": 138.4025657571453, + "median_first_sse_s": 0.09417829802259803, + "median_tpot_est_s": 0.025639875015551823, + "median_e2e_s": 0.8890144235047046, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n128-o32-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.16205501300282776, + "tpot_est_s": 0.02460053306440973, + "e2e_s": 0.9246715379995294 + }, + { + "id": "r1-n128-o32-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.11661841202294454, + "tpot_est_s": 0.02533383054786452, + "e2e_s": 0.9019671590067446 + }, + { + "id": "r1-n128-o32-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.07173818402225152, + "tpot_est_s": 0.02594591948323913, + "e2e_s": 0.8760616880026646 + }, + { + "id": "r1-n128-o32-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.02596474502934143, + "tpot_est_s": 0.026576486290357405, + "e2e_s": 0.849835820030421 + } + ] + }, + { + "repeat": 2, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 0.7699311460019089, + "output_tok_s": 41.56215807890003, + "median_first_sse_s": 0.022508475987706333, + "median_tpot_est_s": 0.02410532329081287, + "median_e2e_s": 0.7697734980029054, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n128-o32-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.022508475987706333, + "tpot_est_s": 0.02410532329081287, + "e2e_s": 0.7697734980029054 + } + ] + }, + { + "repeat": 2, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 0.9497653330327012, + "output_tok_s": 134.7701327350857, + "median_first_sse_s": 0.0939450245059561, + "median_tpot_est_s": 0.026423867822872593, + "median_e2e_s": 0.9130849270150065, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n128-o32-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.024733664002269506, + "tpot_est_s": 0.027449237096363738, + "e2e_s": 0.8756600139895454 + }, + { + "id": "r2-n128-o32-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.07038984901737422, + "tpot_est_s": 0.026785010903803332, + "e2e_s": 0.9007251870352775 + }, + { + "id": "r2-n128-o32-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.11750019999453798, + "tpot_est_s": 0.026062724741941858, + "e2e_s": 0.9254446669947356 + }, + { + "id": "r2-n128-o32-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 0.16151664697099477, + "tpot_est_s": 0.0254189828391968, + "e2e_s": 0.9495051149860956 + } + ] + }, + { + "repeat": 2, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 1.6145283309742808, + "output_tok_s": 19.82003002740108, + "median_first_sse_s": 0.8517699309741147, + "median_tpot_est_s": 0.024601110936923614, + "median_e2e_s": 1.6144043700187467, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n8192-o32-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 0.8517699309741147, + "tpot_est_s": 0.024601110936923614, + "e2e_s": 1.6144043700187467 + } + ] + }, + { + "repeat": 2, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.447684141981881, + "output_tok_s": 19.85208908832428, + "median_first_sse_s": 3.276922040997306, + "median_tpot_est_s": 0.04964715587031547, + "median_e2e_s": 4.815983872977085, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n8192-o32-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 4.08150992001174, + "tpot_est_s": 0.049592274321889084, + "e2e_s": 5.618870423990302 + }, + { + "id": "r2-n8192-o32-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 5.687382168020122, + "tpot_est_s": 0.02451739248241328, + "e2e_s": 6.447421334974933 + }, + { + "id": "r2-n8192-o32-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 0.8545690670143813, + "tpot_est_s": 0.049953862420103, + "e2e_s": 2.4031388020375744 + }, + { + "id": "r2-n8192-o32-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 2.4723341619828716, + "tpot_est_s": 0.04970203741874185, + "e2e_s": 4.013097321963869 + } + ] + } + ], + "harness_sha256": "c80a54247b001b8f9c43a54e6418d609a6414134992afb70b58300694cbb37f7", + "timing_scope": "Client first SSE event, full response e2e and estimated TPOT=(e2e-first_event)/(output_tokens-1). SSE can coalesce tokens; this is not per-token kernel timing. Loading/warmup/correctness checks excluded.", + "load_s": 5.0826301440247335, + "references": { + "128:32": { + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background" + }, + "8192:32": { + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples." + }, + "128:128": { + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains" + }, + "8192:128": { + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books." + } + }, + "warmup_and_checks_s": 13.61248098599026, + "metrics": [ + "# HELP vllm:num_requests_running Requests executing on the stage.\n# TYPE vllm:num_requests_running gauge\nvllm:num_requests_running{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:num_requests_waiting Requests queued for the stage owner.\n# TYPE vllm:num_requests_waiting gauge\nvllm:num_requests_waiting{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:kv_cache_usage_perc Occupied fraction of the stage's KV lanes (1 = full).\n# TYPE vllm:kv_cache_usage_perc gauge\nvllm:kv_cache_usage_perc{model_name=\"Gemma3-1B\"} 0.0\n# HELP vllm:gpu_cache_usage_perc Occupied fraction of the stage's KV lanes (1 = full).\n# TYPE vllm:gpu_cache_usage_perc gauge\nvllm:gpu_cache_usage_perc{model_name=\"Gemma3-1B\"} 0.0\n# HELP vllm:request_success_total Finished requests by finish reason.\n# TYPE vllm:request_success_total counter\nvllm:request_success_total{model_name=\"Gemma3-1B\",finished_reason=\"length\"} 42\n# HELP airm_stage_request_failures_total Requests that ended with an engine error.\n# TYPE airm_stage_request_failures_total counter\nairm_stage_request_failures_total{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:prompt_tokens_total Prompt tokens of finished requests.\n# TYPE vllm:prompt_tokens_total counter\nvllm:prompt_tokens_total{model_name=\"Gemma3-1B\"} 174720\n# HELP vllm:generation_tokens_total Generated tokens of finished requests.\n# TYPE vllm:generation_tokens_total counter\nvllm:generation_tokens_total{model_name=\"Gemma3-1B\"} 1344\n# HELP vllm:time_to_first_token_seconds Time to first token (prefill stage: fenced prefill).\n# TYPE vllm:time_to_first_token_seconds histogram\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.001\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.005\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.01\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.02\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.04\"} 8\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.06\"} 8\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.08\"} 12\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.1\"} 12\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.25\"} 20\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 20\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.75\"} 21\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 30\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.5\"} 34\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"5.0\"} 38\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"7.5\"} 42\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"10.0\"} 42\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 42\nvllm:time_to_first_token_seconds_sum{model_name=\"Gemma3-1B\"} 58.04631465714192\nvllm:time_to_first_token_seconds_count{model_name=\"Gemma3-1B\"} 42\n# HELP vllm:time_per_output_token_seconds Time per output token after the first (decode stage).\n# TYPE vllm:time_per_output_token_seconds histogram\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.01\"} 0\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.025\"} 17\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.05\"} 41\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.075\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.1\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.15\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.2\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.3\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.4\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.75\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.5\"} 42\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 42\nvllm:time_per_output_token_seconds_sum{model_name=\"Gemma3-1B\"} 1.3612469855861198\nvllm:time_per_output_token_seconds_count{model_name=\"Gemma3-1B\"} 42\n# HELP vllm:e2e_request_latency_seconds Stage request latency, from execution start to reply.\n# TYPE vllm:e2e_request_latency_seconds histogram\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.3\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.8\"} 3\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 20\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.5\"} 20\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.0\"} 25\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.5\"} 29\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"5.0\"} 34\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"10.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"15.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"20.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"30.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"40.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"50.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"60.0\"} 42\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 42\nvllm:e2e_request_latency_seconds_sum{model_name=\"Gemma3-1B\"} 100.24497121031163\nvllm:e2e_request_latency_seconds_count{model_name=\"Gemma3-1B\"} 42\n# HELP airm_kv_transfer_seconds KV transfer time from the prefill source to the decode destination.\n# TYPE airm_kv_transfer_seconds histogram\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.0005\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.001\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.0025\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.005\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.01\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.025\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.05\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.1\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.25\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 0\nairm_kv_transfer_seconds_sum{model_name=\"Gemma3-1B\"} 0.0\nairm_kv_transfer_seconds_count{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:cache_config_info Information of the LLMEngine CacheConfig.\n# TYPE vllm:cache_config_info gauge\nvllm:cache_config_info{model_name=\"Gemma3-1B\",block_size=\"64\",num_gpu_blocks=\"576\",enable_prefix_caching=\"False\"} 1\n# HELP vllm:prefix_cache_queries_total Prompt tokens looked up in the prefix cache.\n# TYPE vllm:prefix_cache_queries_total counter\nvllm:prefix_cache_queries_total{model_name=\"Gemma3-1B\"} 174720\n# HELP vllm:prefix_cache_hits_total Prompt tokens served from the prefix cache.\n# TYPE vllm:prefix_cache_hits_total counter\nvllm:prefix_cache_hits_total{model_name=\"Gemma3-1B\"} 0\n" + ], + "parity_passed": true, + "derived_from": [ + "perf248-gemma-native-a.json", + "perf248-gemma-native-long128.json" + ] +} diff --git a/opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.json b/opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.json new file mode 100644 index 00000000..a56dac2b --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.json @@ -0,0 +1,12006 @@ +{ + "passed": true, + "model": "Gemma3-1B", + "mode": "pd", + "dtype": "bfloat16", + "torch": "2.13.0+cu130", + "transformers": "5.15.0", + "replicas": 1, + "cpu_threads_per_server": 4, + "prompts": { + "128": [ + 2, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 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The red box contains apples. 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The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "tokens_equal": true + }, + { + "id": "warm-0-8192-32", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. 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The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "tokens_equal": true + } + ], + "correctness_batches": [ + { + "input_tokens": 128, + "output_tokens": 32, + "concurrency": 1, + "rows": [ + { + "id": "check-128-32-1-0", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. 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The blue box contains books.\nThis is background", + "tokens_equal": true + }, + { + "id": "check-128-32-4-3", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "tokens_equal": true + } + ] + }, + { + "input_tokens": 128, + "output_tokens": 128, + "concurrency": 1, + "rows": [ + { + "id": "check-128-128-1-0", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "tokens_equal": true + } + ] + }, + { + "input_tokens": 128, + "output_tokens": 128, + "concurrency": 4, + "rows": [ + { + "id": "check-128-128-4-0", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "tokens_equal": true + }, + { + "id": "check-128-128-4-1", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "tokens_equal": true + }, + { + "id": "check-128-128-4-2", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "tokens_equal": true + }, + { + "id": "check-128-128-4-3", + "endpoint": 0, + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "tokens_equal": true + } + ] + }, + { + "input_tokens": 8192, + "output_tokens": 32, + "concurrency": 1, + "rows": [ + { + "id": "check-8192-32-1-0", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "tokens_equal": true + } + ] + }, + { + "input_tokens": 8192, + "output_tokens": 32, + "concurrency": 4, + "rows": [ + { + "id": "check-8192-32-4-0", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "tokens_equal": true + }, + { + "id": "check-8192-32-4-1", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "tokens_equal": true + }, + { + "id": "check-8192-32-4-2", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "tokens_equal": true + }, + { + "id": "check-8192-32-4-3", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "tokens_equal": true + } + ] + }, + { + "input_tokens": 8192, + "output_tokens": 128, + "concurrency": 1, + "rows": [ + { + "id": "check-8192-128-1-0", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "tokens_equal": true + } + ] + }, + { + "input_tokens": 8192, + "output_tokens": 128, + "concurrency": 4, + "rows": [ + { + "id": "check-8192-128-4-0", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "tokens_equal": true + }, + { + "id": "check-8192-128-4-1", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "tokens_equal": true + }, + { + "id": "check-8192-128-4-2", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "tokens_equal": true + }, + { + "id": "check-8192-128-4-3", + "endpoint": 0, + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "tokens_equal": true + } + ] + } + ], + "batches": [ + { + "repeat": 0, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 2.2904554959968664, + "output_tok_s": 13.971020199225814, + "median_first_sse_s": 1.5108581809909083, + "median_tpot_est_s": 0.025144204773354314, + "median_e2e_s": 2.290328528964892, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n128-o32-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 1.5108581809909083, + "tpot_est_s": 0.025144204773354314, + "e2e_s": 2.290328528964892 + } + ] + }, + { + "repeat": 0, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.748568509006873, + "output_tok_s": 18.966985343509037, + "median_first_sse_s": 3.739605376991676, + "median_tpot_est_s": 0.024642839452304367, + "median_e2e_s": 4.483405248989584, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n128-o32-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 5.97458356898278, + "tpot_est_s": 0.02495238383961541, + "e2e_s": 6.748107468010858 + }, + { + "id": "r0-n128-o32-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 1.500138386967592, + "tpot_est_s": 0.025934682452991124, + "e2e_s": 2.304113543010317 + }, + { + "id": "r0-n128-o32-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 4.48501377296634, + "tpot_est_s": 0.024333295064993325, + "e2e_s": 5.239345919981133 + }, + { + "id": "r0-n128-o32-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 2.994196981017012, + "tpot_est_s": 0.023653793451000726, + "e2e_s": 3.7274645779980347 + } + ] + }, + { + "repeat": 0, + "input_tokens": 128, + "output_tokens_per_request": 128, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 128, + "wall_s": 4.796814206987619, + "output_tok_s": 26.684377271385607, + "median_first_sse_s": 1.5960666799801402, + "median_tpot_est_s": 0.025201801937091803, + "median_e2e_s": 4.796695525990799, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n128-o128-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 1.5960666799801402, + "tpot_est_s": 0.025201801937091803, + "e2e_s": 4.796695525990799 + } + ] + }, + { + "repeat": 0, + "input_tokens": 128, + "output_tokens_per_request": 128, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 512, + "wall_s": 9.2023759779986, + "output_tok_s": 55.6378049782045, + "median_first_sse_s": 3.747203663981054, + "median_tpot_est_s": 0.025615204184996257, + "median_e2e_s": 7.031058817461599, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n128-o128-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 2.97643485898152, + "tpot_est_s": 0.026048857023422495, + "e2e_s": 6.284639700956177 + }, + { + "id": "r0-n128-o128-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 6.004263092996553, + "tpot_est_s": 0.025179445173400712, + "e2e_s": 9.202052630018443 + }, + { + "id": "r0-n128-o128-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 4.517972468980588, + "tpot_est_s": 0.025665397362097893, + "e2e_s": 7.77747793396702 + }, + { + "id": "r0-n128-o128-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 1.4891845749807544, + "tpot_est_s": 0.02556501100789462, + "e2e_s": 4.7359409729833715 + } + ] + }, + { + "repeat": 0, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 2.366323228983674, + "output_tok_s": 13.523089157073382, + "median_first_sse_s": 1.5761602520360611, + "median_tpot_est_s": 0.02548522151623582, + "median_e2e_s": 2.3662021190393716, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n8192-o32-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 1.5761602520360611, + "tpot_est_s": 0.02548522151623582, + "e2e_s": 2.3662021190393716 + } + ] + }, + { + "repeat": 0, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.86172240995802, + "output_tok_s": 18.65420842647919, + "median_first_sse_s": 3.8799441659939475, + "median_tpot_est_s": 0.024729849500281197, + "median_e2e_s": 4.646569500502665, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n8192-o32-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.0876672510057688, + "tpot_est_s": 0.02703399496761361, + "e2e_s": 3.9257210950017907 + }, + { + "id": "r0-n8192-o32-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.163121389981825, + "tpot_est_s": 0.024610431354132392, + "e2e_s": 3.926044761959929 + }, + { + "id": "r0-n8192-o32-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 6.1076439549797215, + "tpot_est_s": 0.02431109380690501, + "e2e_s": 6.861287862993777 + }, + { + "id": "r0-n8192-o32-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 4.59676694200607, + "tpot_est_s": 0.02484926764643, + "e2e_s": 5.3670942390454 + } + ] + }, + { + "repeat": 0, + "input_tokens": 8192, + "output_tokens_per_request": 128, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 128, + "wall_s": 4.5618909490294755, + "output_tok_s": 28.058540072561687, + "median_first_sse_s": 1.6409755409695208, + "median_tpot_est_s": 0.022998321196889344, + "median_e2e_s": 4.561762332974467, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n8192-o128-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 1.6409755409695208, + "tpot_est_s": 0.022998321196889344, + "e2e_s": 4.561762332974467 + } + ] + }, + { + "repeat": 0, + "input_tokens": 8192, + "output_tokens_per_request": 128, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 512, + "wall_s": 9.174527505005244, + "output_tok_s": 55.80668865188686, + "median_first_sse_s": 3.9438374804740306, + "median_tpot_est_s": 0.026099092728324513, + "median_e2e_s": 7.258422256971244, + "all_text_equal": true + }, + "rows": [ + { + "id": "r0-n8192-o128-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 3.2243761209538206, + "tpot_est_s": 0.026589788913572807, + "e2e_s": 6.601279312977567 + }, + { + "id": "r0-n8192-o128-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 6.17021787801059, + "tpot_est_s": 0.023652339913317656, + "e2e_s": 9.174065047001932 + }, + { + "id": "r0-n8192-o128-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 3.1425981000065804, + "tpot_est_s": 0.027227902755610586, + "e2e_s": 6.600541749969125 + }, + { + "id": "r0-n8192-o128-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 4.6632988399942406, + "tpot_est_s": 0.025608396543076218, + "e2e_s": 7.91556520096492 + } + ] + }, + { + "repeat": 1, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 2.362075195007492, + "output_tok_s": 13.547409526858226, + "median_first_sse_s": 1.595306287985295, + "median_tpot_est_s": 0.02472866922541852, + "median_e2e_s": 2.361895033973269, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n8192-o32-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 1.595306287985295, + "tpot_est_s": 0.02472866922541852, + "e2e_s": 2.361895033973269 + } + ] + }, + { + "repeat": 1, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.873117864015512, + "output_tok_s": 18.623280224852422, + "median_first_sse_s": 3.894633021525806, + "median_tpot_est_s": 0.02512674477428288, + "median_e2e_s": 4.673562109528575, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n8192-o32-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 4.610491946048569, + "tpot_est_s": 0.02479748874189212, + "e2e_s": 5.379214097047225 + }, + { + "id": "r1-n8192-o32-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.1787740970030427, + "tpot_est_s": 0.02545600080667364, + "e2e_s": 3.9679101220099255 + }, + { + "id": "r1-n8192-o32-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 6.1218647719942965, + "tpot_est_s": 0.02422014600034022, + "e2e_s": 6.872689298004843 + }, + { + "id": "r1-n8192-o32-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.0994568440364674, + "tpot_est_s": 0.028010789676749658, + "e2e_s": 3.9677913240157068 + } + ] + }, + { + "repeat": 1, + "input_tokens": 8192, + "output_tokens_per_request": 128, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 128, + "wall_s": 4.764570051047485, + "output_tok_s": 26.864963391997847, + "median_first_sse_s": 1.67179589899024, + "median_tpot_est_s": 0.024351226653551727, + "median_e2e_s": 4.764401683991309, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n8192-o128-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 1.67179589899024, + "tpot_est_s": 0.024351226653551727, + "e2e_s": 4.764401683991309 + } + ] + }, + { + "repeat": 1, + "input_tokens": 8192, + "output_tokens_per_request": 128, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 512, + "wall_s": 9.365355414978694, + "output_tok_s": 54.66957497214907, + "median_first_sse_s": 3.89337626149063, + "median_tpot_est_s": 0.02681725643328611, + "median_e2e_s": 7.299167828517966, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n8192-o128-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 3.0981669789762236, + "tpot_est_s": 0.027850157133941577, + "e2e_s": 6.635136934986804 + }, + { + "id": "r1-n8192-o128-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 6.1365045820130035, + "tpot_est_s": 0.025420169425325278, + "e2e_s": 9.364866099029314 + }, + { + "id": "r1-n8192-o128-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 3.1730173389660195, + "tpot_est_s": 0.02726812708681068, + "e2e_s": 6.636069478990976 + }, + { + "id": "r1-n8192-o128-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 4.6137351840152405, + "tpot_est_s": 0.02636638577976154, + "e2e_s": 7.962266178044956 + } + ] + }, + { + "repeat": 1, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 2.3247535999980755, + "output_tok_s": 13.764899643569318, + "median_first_sse_s": 1.5667432280024514, + "median_tpot_est_s": 0.024444153549284826, + "median_e2e_s": 2.324511988030281, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n128-o32-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 1.5667432280024514, + "tpot_est_s": 0.024444153549284826, + "e2e_s": 2.324511988030281 + } + ] + }, + { + "repeat": 1, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.910503959981725, + "output_tok_s": 18.522527552438955, + "median_first_sse_s": 3.895199087477522, + "median_tpot_est_s": 0.024860345628938726, + "median_e2e_s": 4.663536224979907, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n128-o32-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 1.6579777470324188, + "tpot_est_s": 0.025389127611678334, + "e2e_s": 2.445040702994447 + }, + { + "id": "r1-n128-o32-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 6.137959661020432, + "tpot_est_s": 0.02490552590273681, + "e2e_s": 6.910030964005273 + }, + { + "id": "r1-n128-o32-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 4.64684960397426, + "tpot_est_s": 0.024815165355140643, + "e2e_s": 5.41611972998362 + }, + { + "id": "r1-n128-o32-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 3.1435485709807836, + "tpot_est_s": 0.024754972548239055, + "e2e_s": 3.910952719976194 + } + ] + }, + { + "repeat": 1, + "input_tokens": 128, + "output_tokens_per_request": 128, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 128, + "wall_s": 4.461202546954155, + "output_tok_s": 28.69181541362448, + "median_first_sse_s": 1.5299377689952962, + "median_tpot_est_s": 0.023079273102559354, + "median_e2e_s": 4.461005453020334, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n128-o128-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 1.5299377689952962, + "tpot_est_s": 0.023079273102559354, + "e2e_s": 4.461005453020334 + } + ] + }, + { + "repeat": 1, + "input_tokens": 128, + "output_tokens_per_request": 128, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 512, + "wall_s": 9.030195322993677, + "output_tok_s": 56.69866284024768, + "median_first_sse_s": 3.7366444774670526, + "median_tpot_est_s": 0.024563179878008323, + "median_e2e_s": 6.886159525485709, + "all_text_equal": true + }, + "rows": [ + { + "id": "r1-n128-o128-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 5.969657895970158, + "tpot_est_s": 0.02409340122047313, + "e2e_s": 9.029519850970246 + }, + { + "id": "r1-n128-o128-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 1.49522059696028, + "tpot_est_s": 0.024718203606160987, + "e2e_s": 4.634432454942726 + }, + { + "id": "r1-n128-o128-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 4.4812921559787355, + "tpot_est_s": 0.02440815614985566, + "e2e_s": 7.5811279870104045 + }, + { + "id": "r1-n128-o128-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 2.9919967989553697, + "tpot_est_s": 0.02519050602366649, + "e2e_s": 6.191191063961014 + } + ] + }, + { + "repeat": 2, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 2.2597848279983737, + "output_tok_s": 14.160640253675972, + "median_first_sse_s": 1.5103488470194861, + "median_tpot_est_s": 0.024170222322291303, + "median_e2e_s": 2.2596257390105166, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n128-o32-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 1.5103488470194861, + "tpot_est_s": 0.024170222322291303, + "e2e_s": 2.2596257390105166 + } + ] + }, + { + "repeat": 2, + "input_tokens": 128, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.741844188014511, + "output_tok_s": 18.985903030443115, + "median_first_sse_s": 3.732695197482826, + "median_tpot_est_s": 0.02387951748378034, + "median_e2e_s": 4.469844311999623, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n128-o32-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 1.5008222800097428, + "tpot_est_s": 0.02330038683759349, + "e2e_s": 2.223134271975141 + }, + { + "id": "r2-n128-o32-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 2.9846051529748365, + "tpot_est_s": 0.023099359258213232, + "e2e_s": 3.7006852899794467 + }, + { + "id": "r2-n128-o32-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 4.480785241990816, + "tpot_est_s": 0.024458648129967193, + "e2e_s": 5.239003334019799 + }, + { + "id": "r2-n128-o32-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 32, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background", + "text_equal": true, + "first_sse_s": 5.974033045989927, + "tpot_est_s": 0.024743959870970538, + "e2e_s": 6.741095801990014 + } + ] + }, + { + "repeat": 2, + "input_tokens": 128, + "output_tokens_per_request": 128, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 128, + "wall_s": 4.477250958036166, + "output_tok_s": 28.588971491592243, + "median_first_sse_s": 1.5097385320113972, + "median_tpot_est_s": 0.023364666047300704, + "median_e2e_s": 4.4770511200185865, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n128-o128-c1-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 1.5097385320113972, + "tpot_est_s": 0.023364666047300704, + "e2e_s": 4.4770511200185865 + } + ] + }, + { + "repeat": 2, + "input_tokens": 128, + "output_tokens_per_request": 128, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 512, + "wall_s": 9.189100630988833, + "output_tok_s": 55.71818402699373, + "median_first_sse_s": 3.789242965489393, + "median_tpot_est_s": 0.024978641177459772, + "median_e2e_s": 6.98378747201059, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n128-o128-c4-0", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 1.5114298789994791, + "tpot_est_s": 0.024919903425565795, + "e2e_s": 4.676257614046335 + }, + { + "id": "r2-n128-o128-c4-1", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 3.021255431987811, + "tpot_est_s": 0.025270408574917066, + "e2e_s": 6.2305973210022785 + }, + { + "id": "r2-n128-o128-c4-2", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 4.557230498990975, + "tpot_est_s": 0.025037378929353753, + "e2e_s": 7.736977623018902 + }, + { + "id": "r2-n128-o128-c4-3", + "endpoint": 0, + "input_tokens": 128, + "output_tokens": 128, + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains", + "text_equal": true, + "first_sse_s": 6.037344223994296, + "tpot_est_s": 0.024811360559253915, + "e2e_s": 9.188387015019543 + } + ] + }, + { + "repeat": 2, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 32, + "wall_s": 2.377213032974396, + "output_tok_s": 13.46114107407582, + "median_first_sse_s": 1.5799840969848447, + "median_tpot_est_s": 0.0257130860981922, + "median_e2e_s": 2.377089766028803, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n8192-o32-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 1.5799840969848447, + "tpot_est_s": 0.0257130860981922, + "e2e_s": 2.377089766028803 + } + ] + }, + { + "repeat": 2, + "input_tokens": 8192, + "output_tokens_per_request": 32, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 128, + "wall_s": 6.852902977028862, + "output_tok_s": 18.67821570348506, + "median_first_sse_s": 3.8961350434983615, + "median_tpot_est_s": 0.026530165967884503, + "median_e2e_s": 4.718570188502781, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n8192-o32-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.179252378991805, + "tpot_est_s": 0.026403139709615178, + "e2e_s": 3.9977497099898756 + }, + { + "id": "r2-n8192-o32-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 4.613017708004918, + "tpot_est_s": 0.026657192226153828, + "e2e_s": 5.439390667015687 + }, + { + "id": "r2-n8192-o32-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 3.097106582019478, + "tpot_est_s": 0.029018431451291807, + "e2e_s": 3.996677957009524 + }, + { + "id": "r2-n8192-o32-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 32, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples.", + "text_equal": true, + "first_sse_s": 6.109172015974764, + "tpot_est_s": 0.023986742773558944, + "e2e_s": 6.852761041955091 + } + ] + }, + { + "repeat": 2, + "input_tokens": 8192, + "output_tokens_per_request": 128, + "concurrency": 1, + "summary": { + "requests": 1, + "output_tokens": 128, + "wall_s": 4.543451378995087, + "output_tok_s": 28.172415488313387, + "median_first_sse_s": 1.5830856129759923, + "median_tpot_est_s": 0.023308924519856587, + "median_e2e_s": 4.543319026997779, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n8192-o128-c1-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 1.5830856129759923, + "tpot_est_s": 0.023308924519856587, + "e2e_s": 4.543319026997779 + } + ] + }, + { + "repeat": 2, + "input_tokens": 8192, + "output_tokens_per_request": 128, + "concurrency": 4, + "summary": { + "requests": 4, + "output_tokens": 512, + "wall_s": 9.30586173402844, + "output_tok_s": 55.019085242561296, + "median_first_sse_s": 3.972675955010345, + "median_tpot_est_s": 0.02599037773210526, + "median_e2e_s": 7.273453926987713, + "all_text_equal": true + }, + "rows": [ + { + "id": "r2-n8192-o128-c4-0", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 3.2236539379809983, + "tpot_est_s": 0.02681329611809851, + "e2e_s": 6.628942544979509 + }, + { + "id": "r2-n8192-o128-c4-1", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 3.1478790330002084, + "tpot_est_s": 0.027407607811184117, + "e2e_s": 6.628645225020591 + }, + { + "id": "r2-n8192-o128-c4-2", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 6.253407351032365, + "tpot_est_s": 0.024029581173227763, + "e2e_s": 9.305164160032291 + }, + { + "id": "r2-n8192-o128-c4-3", + "endpoint": 0, + "input_tokens": 8192, + "output_tokens": 128, + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.", + "text_equal": true, + "first_sse_s": 4.721697972039692, + "tpot_est_s": 0.02516745934611201, + "e2e_s": 7.917965308995917 + } + ] + } + ], + "harness_sha256": "cfd4821e2a2112f3fcf7f242f3e76efe47134640e4bf22b3b63fb808be6148f0", + "startup_timeout_s": 1800, + "timing_scope": "Client first SSE event, full response e2e and estimated TPOT=(e2e-first_event)/(output_tokens-1). SSE can coalesce tokens; this is not per-token kernel timing. Loading/warmup/correctness checks excluded.", + "physical_gpus": 1, + "physical_rngd": 1, + "physical_atom": 0, + "slots_per_decoder": 4, + "producer_cache": false, + "decoder_cache": false, + "producer_chunk": 8192, + "local_chunk": 256, + "context": 9216, + "server_config": { + "servers": [ + [ + "/home/gspark/venvs/pt213/bin/python", + "-c", + "import sys,importlib.util,runpy\ns=importlib.util.spec_from_file_location('opt_prime.accel.serve.llmd','/tmp/llmd240.py')\nm=importlib.util.module_from_spec(s);sys.modules[s.name]=m;s.loader.exec_module(m)\nrunpy.run_path('/home/gspark/workspace/aicomp-dense-hybrid-258/opt_prime/examples/pd/serve_batched.py',run_name='__main__')\n", + "--model", + "/tmp/serving-matrix-models/Gemma3-1B", + "--device", + "cuda:0", + "--dtype", + "bfloat16", + "--slots", + "4", + "--max-context", + "9216", + "--max-output", + "128", + "--kv", + "paged", + "--page-size", + "64", + "--chunk", + "256", + "--port", + "{port}", + "--pd-prefill-python", + "/tmp/rngd-gpu201-src/python-worker.sh", + "--pd-prefill-args", + "--width 8192 --engine-factory gemma_prefill:Prefill" + ] + ], + "metadata": { + "physical_gpus": 1, + "physical_rngd": 1, + "physical_atom": 0, + "slots_per_decoder": 4, + "producer_cache": false, + "decoder_cache": false, + "producer_chunk": 8192, + "local_chunk": 256, + "context": 9216 + } + }, + "load_s": 13.739347908005584, + "references": { + "128:32": { + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background" + }, + "8192:32": { + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples." + }, + "128:128": { + "tokens": [ + 9079, + 107, + 106, + 107, + 106, + 130614, + 107, + 106, + 107, + 106, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097 + ], + "text": " Paris\n\n nonlocal\n\n\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains" + }, + "8192:128": { + "tokens": [ + 9079, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761, + 107, + 2094, + 563, + 1695, + 4403, + 236761, + 669, + 2604, + 3673, + 6097, + 36157, + 236761, + 669, + 3730, + 3673, + 6097, + 6249, + 236761 + ], + "text": " Paris.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books.\nThis is background context. The red box contains apples. The blue box contains books." + } + }, + "warmup_and_checks_s": 61.43669509899337, + "metrics": [ + "# HELP vllm:num_requests_running Requests executing on the stage.\n# TYPE vllm:num_requests_running gauge\nvllm:num_requests_running{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:num_requests_waiting Requests queued for the stage owner.\n# TYPE vllm:num_requests_waiting gauge\nvllm:num_requests_waiting{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:kv_cache_usage_perc Occupied fraction of the stage's KV lanes (1 = full).\n# TYPE vllm:kv_cache_usage_perc gauge\nvllm:kv_cache_usage_perc{model_name=\"Gemma3-1B\"} 0.0\n# HELP vllm:gpu_cache_usage_perc Occupied fraction of the stage's KV lanes (1 = full).\n# TYPE vllm:gpu_cache_usage_perc gauge\nvllm:gpu_cache_usage_perc{model_name=\"Gemma3-1B\"} 0.0\n# HELP vllm:request_success_total Finished requests by finish reason.\n# TYPE vllm:request_success_total counter\nvllm:request_success_total{model_name=\"Gemma3-1B\",finished_reason=\"length\"} 84\n# HELP airm_stage_request_failures_total Requests that ended with an engine error.\n# TYPE airm_stage_request_failures_total counter\nairm_stage_request_failures_total{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:prompt_tokens_total Prompt tokens of finished requests.\n# TYPE vllm:prompt_tokens_total counter\nvllm:prompt_tokens_total{model_name=\"Gemma3-1B\"} 349440\n# HELP vllm:generation_tokens_total Generated tokens of finished requests.\n# TYPE vllm:generation_tokens_total counter\nvllm:generation_tokens_total{model_name=\"Gemma3-1B\"} 6720\n# HELP vllm:time_to_first_token_seconds Time to first token (prefill stage: fenced prefill).\n# TYPE vllm:time_to_first_token_seconds histogram\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.001\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.005\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.01\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.02\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.04\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.06\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.08\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.1\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.25\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.75\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 0\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.5\"} 28\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"5.0\"} 68\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"7.5\"} 84\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"10.0\"} 84\nvllm:time_to_first_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 84\nvllm:time_to_first_token_seconds_sum{model_name=\"Gemma3-1B\"} 289.0731810472207\nvllm:time_to_first_token_seconds_count{model_name=\"Gemma3-1B\"} 84\n# HELP vllm:time_per_output_token_seconds Time per output token after the first (decode stage).\n# TYPE vllm:time_per_output_token_seconds histogram\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.01\"} 0\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.025\"} 51\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.05\"} 83\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.075\"} 83\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.1\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.15\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.2\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.3\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.4\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.75\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.5\"} 84\nvllm:time_per_output_token_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 84\nvllm:time_per_output_token_seconds_sum{model_name=\"Gemma3-1B\"} 2.146048682772676\nvllm:time_per_output_token_seconds_count{model_name=\"Gemma3-1B\"} 84\n# HELP vllm:e2e_request_latency_seconds Stage request latency, from execution start to reply.\n# TYPE vllm:e2e_request_latency_seconds histogram\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.3\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.8\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.5\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.0\"} 0\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"2.5\"} 13\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"5.0\"} 40\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"10.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"15.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"20.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"30.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"40.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"50.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"60.0\"} 84\nvllm:e2e_request_latency_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 84\nvllm:e2e_request_latency_seconds_sum{model_name=\"Gemma3-1B\"} 456.112672785006\nvllm:e2e_request_latency_seconds_count{model_name=\"Gemma3-1B\"} 84\n# HELP airm_kv_transfer_seconds KV transfer time from the prefill source to the decode destination.\n# TYPE airm_kv_transfer_seconds histogram\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.0005\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.001\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.0025\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.005\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.01\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.025\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.05\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.1\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.25\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"0.5\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"1.0\"} 0\nairm_kv_transfer_seconds_bucket{model_name=\"Gemma3-1B\",le=\"+Inf\"} 0\nairm_kv_transfer_seconds_sum{model_name=\"Gemma3-1B\"} 0.0\nairm_kv_transfer_seconds_count{model_name=\"Gemma3-1B\"} 0\n# HELP vllm:cache_config_info Information of the LLMEngine CacheConfig.\n# TYPE vllm:cache_config_info gauge\nvllm:cache_config_info{model_name=\"Gemma3-1B\",block_size=\"64\",num_gpu_blocks=\"576\",enable_prefix_caching=\"False\"} 1\n# HELP vllm:prefix_cache_queries_total Prompt tokens looked up in the prefix cache.\n# TYPE vllm:prefix_cache_queries_total counter\nvllm:prefix_cache_queries_total{model_name=\"Gemma3-1B\"} 349440\n# HELP vllm:prefix_cache_hits_total Prompt tokens served from the prefix cache.\n# TYPE vllm:prefix_cache_hits_total counter\nvllm:prefix_cache_hits_total{model_name=\"Gemma3-1B\"} 0\n# HELP airm_pd_prefills_total Prompts prefilled by the PD prefill worker (remote) or here (local).\n# TYPE airm_pd_prefills_total counter\nairm_pd_prefills_total{model_name=\"Gemma3-1B\",side=\"remote\"} 84\nairm_pd_prefills_total{model_name=\"Gemma3-1B\",side=\"local\"} 0\n# HELP airm_pd_transferred_tokens_total Prompt KV tokens received from the prefill side.\n# TYPE airm_pd_transferred_tokens_total counter\nairm_pd_transferred_tokens_total{model_name=\"Gemma3-1B\"} 349440\n# HELP airm_pd_producer_seconds_total Accumulated worker-reported seconds for admitted PD handoffs; excludes failed/cancelled handoffs. Prefill includes KV gathering; transfer excludes destination KV installation.\n# TYPE airm_pd_producer_seconds_total counter\nairm_pd_producer_seconds_total{model_name=\"Gemma3-1B\",stage=\"prefill\"} 127.2515719148796\nairm_pd_producer_seconds_total{model_name=\"Gemma3-1B\",stage=\"transfer\"} 0.0\n" + ], + "parity_passed": true +} diff --git a/opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.server0.log b/opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.server0.log new file mode 100644 index 00000000..77c83261 --- /dev/null +++ b/opt_prime/examples/pd/http_matrix/evidence258/local258-gemma-matrix-b.server0.log @@ -0,0 +1,3 @@ + Loading weights: 0%| | 0/340 [00:00 analysis/serving-matrix-201/local258-gemma-queue.log 2>&1` with corrected worktree runtime and unchanged failed-run prompts/reference/configuration. New local258-gemma-matrix-b files preserve original failure. QueuePID1211034 confirmed live. Deferred run_gpu258_faults_after_matrix.py watches this PID, requires completed four-model workloads (correctedGemma selected), preserves native parity failures, and uses32ce5d5 for all fault tests. Already completed Qwen/KONI diagnostics are not rerun. No corrected hardware result yet. + +## Corrected live Gemma run completed + +Runtime32ce5d5:24timed batches complete with passed=true/parity_passed=true,20/20 nonstream token comparisons and60/60 timed SSE texts equal nativeGPU references.84remote prefills,0local,0request errors. Input128/8192,output32/128,c1/4,3repeats; same original reference prompts asserted. Startup13.739s excluded; reused environment, not comparable to prior cold compile time. Raw local258-gemma-matrix-b.json,config,reference,serverlog and summary. + +|Input|Output|Concurrency|Median tok/s| +|---:|---:|---:|---:| +|128|32|1|13.971| +|128|32|4|18.967| +|128|128|1|28.589| +|128|128|4|55.718| +|8192|32|1|13.523| +|8192|32|4|18.654| +|8192|128|1|28.059| +|8192|128|4|55.019| + +Original failed run is preserved. The shape mismatch is fixed on live hardware; this fixture does not resolve separate long arithmetic quality failures. A resource_tracker shutdown warning remains in the log; the subsequent empty-device check allowed the queued fault suite to start. This does not prove no transient SHM leak.