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Universal Hardware-Aware Compute Runtime — a modular, capability-driven execution stack

Project description

UHCR

A Python framework for hardware-optimized computation with JIT compilation across x86_64, AArch64, RISC-V, and CUDA.

Python 3.10+ License: Apache-2.0 Tests: passing Docs: GitHub Pages PyPI: v3.0.0

Full documentation

Install

pip install uhcr

Quick Example

import uhcr

@uhcr.jit(eager=True)
def compute(a, b):
    return (a + b) * 2

Features

  • JIT Compilation - Traces Python functions and compiles to native machine code
  • Multi-ISA Code Generation - Targets x86_64 (AVX2), AArch64 (NEON), and RISC-V (RVV)
  • CUDA Backend - GPU acceleration via PTX JIT for NVIDIA hardware
  • Optimization Pipeline - Constant folding, dead code elimination, strength reduction, CSE
  • Hardware Detection - Automatic CPUID, GPU probe, and NUMA topology discovery
  • Plugin System - Extend with custom backends, kernels, and passes via TOML manifests
  • Tensor API - High-level tensor operations dispatched to the optimal backend
  • Built-in Benchmarks - Performance measurement suite for comparing execution paths

Documentation

Experimental Status

UHCR v3 includes the CLI tool (uhcr) and expanded hardware detection (RAM speed/type, CPU cache topology). These are now stable and production-ready as of v3.0.0.

License

Apache-2.0

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