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<!--
SPDX-License-Identifier: CC-BY-SA-4.0
SPDX-FileCopyrightText: 2025-2026 Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
-->

[![Topology](https://img.shields.io/badge/Project-Topology-9558B2)](TOPOLOGY.md)
[![85](https://img.shields.io/badge/Completion-85%25-green)](TOPOLOGY.md) [![OpenSSF Best Practices](https://img.shields.io/badge/OpenSSF-Best_Practices-green?logo=opensourcesecurity)](https://www.bestpractices.dev/en/projects/new?repo_url=https://github.com/hyperpolymath/LowLevel.jl) ![License:
PMPL-1.0](https://img.shields.io/badge/License-MPL--2.0-blue.svg) <embed
src="https://api.thegreenwebfoundation.org/greencheckimage/github.com"
data-link="https://www.thegreenwebfoundation.org/green-web-check/?url=github.com" />
![Peak System](https://img.shields.io/badge/Status-Peak_System-red.svg)

**The Definitive Bare-Metal & Coprocessor Foundation for Julia.**

<div id="toc">

</div>

# Overview

LowLevel.jl is not just a bridge; it is a **Resource-Aware Hardware
Orchestrator**. It provides the Hyperpolymath ecosystem with deep-cycle
diagnostics, self-healing fault tolerance, and native execution paths
for every major processing unit in modern and future computing.

It is designed for "High-Stakes Silicon"—where performance is
non-negotiable and failure must be mathematically impossible.

# Core Architectural Pillars

## 1. Universal Coprocessor Support (X-PU)

LowLevel.jl provides specialized kernels and dispatch logic for: \*
**CPU**: Optimized for **Intel Core i9/Xeon** (AVX-512) and **AMD Ryzen
9/Pro** (Zen 4/5 extensions). \* **GPU**: Native hooks for NVIDIA
(CUDA), AMD (ROCm), and Apple (Metal). \* **NPU/TPU**: Dedicated paths
for Neural and Tensor units (Intel NPU, Google TPU). \* **QPU**: Quantum
Processing Unit abstraction layer for hybrid classical-quantum
algorithms. \* **PPU/MPU**: Physics and Mathematical Processing Units
for high-fidelity simulations. \* **DSP/APU**: Digital Signal and
Audio/Accelerated Processing Units. \* **IOPU**: Specialized I/O
Processing for high-frequency data ingestion.

## 2. Resilience & Self-Healing

- **Diagnostics**: Real-time monitoring of thermal throttling, cache
misses, and branch mispredictions.

- **Self-Healing**: Automated kernel hot-swapping. If an AVX-512 kernel
triggers a hardware fault, the system transparently downgrades to a
verified scalar fallback.

- **Fault-Tolerance**: Integration with Julia’s task system to handle
hardware-level MCE (Machine Check Exceptions) without crashing the
runtime.

## 3. Resource Awareness

- **Topology Mapping**: Deep awareness of NUMA nodes, L1/L2/L3 cache
boundaries, and memory bandwidth saturation.

- **Energy-Aware Computing**: Dynamic frequency scaling hooks to
optimize for performance-per-watt during massive research simulations.

# Project Structure

```text
LowLevel.jl/
├── src/
│ ├── LowLevel.jl # Main Orchestrator
│ ├── hardware/ # Topology & Feature Detection
│ ├── accelerators/ # NPU, TPU, QPU, GPU modules
│ ├── resilience/ # Self-healing & Fault tolerance
│ ├── diagnostics/ # Telemetry & Performance monitoring
│ ├── asm/ # Multi-arch Assembly (x86, ARM, RISC-V)
│ └── zig/ # Safe systems logic
└── deps/ # Binary artifacts
```

# License

Palimpsest-MPL-1.0 License.
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