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feat(placement): pack several models onto one GPU - #908
Lets several models share one GPU. Receipts and load rows carry a measured memory footprint. The planner may form a shared lane from identities of the same bundle and queue pool, some pinned and the rest loaded on demand. Such a lane is feasible when the pinned models, the largest on-demand model and the working memory at the lane's concurrency fit within 80% of the card. A co-residency receipt must also show every resident within its warm bound. The search is deterministic first-fit in decreasing footprint, and it tries existing lanes first, so a second run over its own plan changes nothing. Shared lanes are priced jointly, so a pinned model cannot move to an option the plan total does not reward. Every lane that pins a model gets its own named queue pool, kept across replans, so a plan with several pinned lanes can be emitted as chart values. Generation models are never packed.
Package tests, including random estates and replan idempotence
lint, typecheck, public-tree check
Summary by CodeRabbit
New Features
Placement planning uses GPU capacity, measured footprints, working memory, and co-residency evidence to assess which identities can share a lane, subject to memory limits and sharing restrictions.
Compatible identities can be packed onto shared lanes when placement and cost constraints are met.
Lanes with pinned identities preserve eligible existing queue pools or receive distinct pools; other lanes use the configured pool.
Reports include memory usage, co-resident identities, undeclared GPU memory, and requests for missing measurements.
Bug Fixes
Replanning better retains compatible pinned placements and supports lazy residents without a one-run delay.
…nes jointly
One card can hold several models: some pinned and always resident, the
rest loaded on demand. The planner now forms such lanes from measured
evidence and prices a shared lane once for all its residents.
- Receipts record footprintMiB, workingMemoryMiB and coResidents, boot
records the footprintMiB of a load that succeeded, and price-list
profiles gpuMemoryMiB. A lane fits when its pinned footprints, its
largest lazy footprint and its largest working memory at the lane's
concurrency come to at most 80% of the card. Only single-card lanes
without fallback cells hold several identities.
- A pinned identity beside other pinned identities is judged by a
co-residency receipt whose coResidents include them, and its demand is
priced at that receipt. A receipt measured beside more residents stands
for fewer. A current shared lane without one is kept and asks for it.
- Lazy-resident options on current host lanes need the memory check, and
a footprint or working memory that is not on file is a measurement
request.
- A packing pass visits every identity alone on its lane in decreasing
floor cost and tries lanes that pin a never-cold identity first, then in
decreasing footprint in use. It keeps a move only when the plan total
falls and every resident's service level holds, and a move that lacks
footprints, a load or a co-residency receipt becomes a measurement
request bounded by that fall.
- Shared lanes are priced jointly: identities that left a lane their
neighbours keep return to it, alone or together, whenever that does not
raise the plan total, and an identity whose co-pinned neighbours change
in the run is decided again beside the ones it is left with. Loosening a
bound can no longer raise the plan total because a pinned identity left
a shared lane; the levers test that pinned that defect now asserts the
identity stays.
- Generation identities are never packed.
…esident for evidence
- Identities that join a lane in one run must fit it together. Each
lazy join was checked only beside the residents the lane had before,
so two joiners that fit alone could overfill the card. Joiners that do
not fit together are admitted first fit in decreasing footprint and the
rest are decided again without that lane.
- A missing footprint or working memory is requested from the resident
that lacks it, under its own identity and warmth at the lane, instead
of from the joining identity. A kept lazy resident whose lane lacks
memory evidence now asks for it, a profile without gpuMemoryMiB is named
in the report as gpuMemoryUndeclared, and a repeated request is listed
once.
- Packing makes a lazy resident only on a lane where a never-cold
identity is pinned, as the lazy-resident posture requires, and visits a
lazy resident that is alone on its own lane like any other identity
alone on its lane.
- The unshared parameter names identities that never share a lane: they
are never packed or made lazy residents, and no identity joins a lane
they are on.
- The random-estate property test also starts from current plans that
are not the planner's own fixpoint, and a new property test checks
that guests joining one host lane fit it together.
- A shared lane holds its container ceiling once against the total, its
GPU type and the shared quota, whichever residents it carries, so a
packing fits where the separate lanes would be refused.
- A shared lane over a ceiling is refused with its maxContainers intact,
and the refusal names it.
The sie-cluster chart carries a lane's pinned set on a static queue pool, and the default queue pool carries no pins, so a plan with more than one pinned lane on one queue pool could not be emitted as Helm values. The planner now gives every lane that pins an identity a named queue pool derived from the lane name, unique within the plan, keeps a named pool the current plan already gives the lane, and leaves lazy-only and cold lanes on the parameters' queue pool. A lane's queue pool no longer decides whether a current placement, a lazy host or a packing target is reusable, since the pool follows from the lane.
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The planner now uses GPU-memory measurements, card capacity, and co-residency receipts when evaluating shared lanes. It adds iterative packing, solitary-identity constraints, and named queue pools for pinned lanes. Schemas, reports, tests, fixtures, and documentation reflect these changes.
Changes: Measured placement and packing
Layer / File(s)
Summary
Memory and co-residency evidence packages/sie_placement/src/sie_placement/schema.py, packages/sie_placement/src/sie_placement/report.py, packages/sie_placement/src/sie_placement/planner.py, packages/sie_placement/tests/test_schema.py, packages/sie_placement/tests/fixtures/planner/price-list.json, packages/sie_placement/tests/fixtures/planner/receipts.json
Receipts and successful boot evidence accept memory measurements. Receipts also record co-residents. Machine profiles accept GPU-memory capacity. Planner parameters add unshared, and report structures add co-residency and memory fields.
Evidence-aware selection and lane assignment packages/sie_placement/src/sie_placement/planner.py, packages/sie_placement/README.md, packages/sie_placement/tests/test_planner.py, packages/sie_placement/tests/test_availability.py, packages/sie_placement/tests/test_levers.py, packages/sie_placement/tests/fixtures/planner/expected-plan.json
The planner evaluates placements with memory and co-residency evidence, and requests missing measurements. Pinned lanes receive named queue pools; eligible existing named pools can be retained.
Iterative layout and packing packages/sie_placement/src/sie_placement/planner.py, packages/sie_placement/README.md, packages/sie_placement/tests/test_packing.py
The planner checks combined lane memory and packs eligible identities when measured fit and cost conditions are met. It retries placement when a proposed join exceeds the memory limit.
Placement reporting and documented rules packages/sie_placement/src/sie_placement/planner.py, packages/sie_placement/src/sie_placement/report.py, packages/sie_placement/README.md, packages/sie_placement/tests/fixtures/planner/expected-report.json, packages/sie_placement/tests/test_planner.py
Reports add co-residents, lane memory usage and limits, profiles without declared GPU memory, and requests for missing evidence. Fixtures and documentation describe the updated outputs and placement rules.
Sequence Diagram(s)
sequenceDiagram
participant Planner
participant Receipts as Placement receipts
participant Report
Planner->>Receipts: Evaluate memory and co-residency evidence
Receipts-->>Planner: Return measurements and receipt matches
Planner->>Report: Record placements and measurement requests
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Possibly related PRs
superlinked/sie#904: Defines the schemas that this change extends with memory and co-residency fields.
superlinked/sie#836: Changes pinned-model validation and warm-floor accounting for pool and lane assignments.
Merge Risk: Minimal · up to c35ea
The planner may miss a measurement request that could reveal a saving in a narrow case. This does not prevent merging.
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…pe maximum
- A shared lane holds its container ceiling once against the total and its
GPU type, and its envelope maximum once against the shared quota, so a
packing fits a quota the separate lanes' envelope maxima would exceed.
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…code
- A receipt's footprintMiB and workingMemoryMiB, a boot row's footprintMiB
and a machine profile's gpuMemoryMiB go through the integer check, so a
document built in code refuses booleans and floats as parsing does.
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Actionable comments posted: 1
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Inline comments:
Review comments at @packages/sie_placement/README.md:
- Around line 102-111: Update the README wording about the derived queue pool to
say it uses the slug of the lane name: lowercase the name and replace each run
of characters outside a-z and 0-9 with a hyphen. Preserve the existing
description of truncation and digest behavior.
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- A pinning lane keeps its current named queue pool only when no other lane
keeps it and it is neither default nor the parameters' queue_pool, each
compared in lowercase as the chart canonicalizes lane tokens. A current
pool spelled Default, or a second lane on Batch and batch, gets a derived
pool instead.
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Fix comments: Fix CodeRabbit comments on this PR
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Review comments at @packages/sie_placement/README.md:
- Around line 192-193: The README statement that the planner requests missing
memory evidence is too broad. Qualify it to explain that `current_gaps` requests
memory evidence only for lazy residents, so a current co-pinned placement may
remain without a `footprint` request and the report may not identify every
unmeasured shared lane.
- Around line 194-195: Update the footprint measurement documentation to clarify
that a profile without gpuMemoryMiB cannot accept new joins, but an existing
shared lane may be retained and reported on that profile. Preserve the
distinction between placement of new identities and retention of current
sharing.
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⚠️ Outside diff range comments (1)
Major · Check combined demand before packing · planner.py:1574-1957
packages/sie_placement/src/sie_placement/planner.py:1574-1957 Major · Stability & Availability · Heavy lift
Check combined demand before packing
If two pinned identities each need the full GPU at their co-residency rate, packing can leave them on a lane with a one-container ceiling. The shared lane cannot serve both demands at those rates, so requests can accumulate. Check the combined demand against the lane’s capacity before accepting the packing.
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Review comment at @packages/sie_placement/src/sie_placement/planner.py around
lines 1574 - 1957:
Update packings and its acceptance path in pack to verify that the combined
demand of pinned co-residents at their co-residency receipt rates fits the
target lane’s capacity before accepting a packing. Reuse the planner’s existing
demand and capacity semantics, and reject the packing when the combined demand
exceeds capacity.
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Review comments at @packages/sie_placement/src/sie_placement/planner.py:
- Around line 1574-1957: Update packings and its acceptance path in pack to
verify that the combined demand of pinned co-residents at their co-residency
receipt rates fits the target lane’s capacity before accepting a packing. Reuse
the planner’s existing demand and capacity semantics, and reject the packing
when the combined demand exceeds capacity.
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packages/sie_placement/README.md
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- A lane with a floor and several priced residents now costs the containers
each hour needs for their requests together, each resident's requests
taking the share of a container its priced receipt's rate gives them.
Pricing each resident's demand against the floor on its own counted a
container that both residents need as free, so a packing could look
cheaper than the lane it makes.
- A packing after which the lane's residents together need more containers
than its maxContainers in some hour is not made, so two residents that each
fill a one-container ceiling are not packed onto it.
On the outside-diff finding "Check combined demand before packing" (planner.py, packings and pack): it holds, and c35ea60 fixes it.
_pricing priced each resident's demand against the lane floor on its own (demand_hours calls above_floor_hours per identity), and pack accepts a move when that total falls. Two pinned residents that each fit in the floor container at their co-residency rate were therefore priced at the floor alone, although together they need a second container. A co-residency receipt names the identities loaded beside the measured one; it does not measure both under load at once, so the shares add up.
A lane with a floor and several priced residents now costs, for each hour, the containers their requests need together: each resident's requests take the share of a container its priced receipt's rate gives them, the shares are summed and rounded up, capped by maxContainers, less the floor. A lane with one resident is priced as before.
pack no longer makes a move after which the lane's residents together need more containers than its maxContainers in some hour.
Tests: test_a_shared_lane_prices_its_residents_demand_together packs two identities that each need one container at 8 rps in one hour and prices the lane at one container all month plus the second container for that hour. test_a_packing_whose_residents_together_need_more_containers_than_the_ceiling_is_not_made keeps them apart under a one-container ceiling, with no co-residency request, and packs them when their demand fits one container together. Both fail on the previous head.
The README's Pricing section and packing step 4 now say this.
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Summary
Lets several models share one GPU. Receipts and load rows carry a measured memory footprint. The planner may form a shared lane from identities of the same bundle and queue pool, some pinned and the rest loaded on demand. Such a lane is feasible when the pinned models, the largest on-demand model and the working memory at the lane's concurrency fit within 80% of the card. A co-residency receipt must also show every resident within its warm bound. The search is deterministic first-fit in decreasing footprint, and it tries existing lanes first, so a second run over its own plan changes nothing. Shared lanes are priced jointly, so a pinned model cannot move to an option the plan total does not reward. Every lane that pins a model gets its own named queue pool, kept across replans, so a plan with several pinned lanes can be emitted as chart values. Generation models are never packed.
Stacked on #907. Refs #903.
Verification
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