Show HN: UHOP – An Open Hardware Optimization Platform for GPUs (github.com)

UHOP is an open‑source platform that automates GPU acceleration across CUDA, ROCm/HIP, Metal, OpenCL (and more), announced with a live demo (uhop.dev) and a developer‑friendly CLI/Local Agent. It detects your hardware, dispatches to the best backend (Torch/MPS/CPU, OpenCL, Triton, CPU fallback), and can generate kernels via AI (OpenAI) with build/validation and smoke tests. Developers can wrap simple Python implementations with @uhop.optimize("op") and UHOP will compile, validate, cache the fastest device‑specific implementation, and reuse it — making portable high‑performance code easier to write and run everywhere. Technically, UHOP is layered: a Vite/React frontend for live controls and benchmarks, Node/Express backend that routes jobs, a Python Local Agent that executes operations securely on your machine, and a UHOP Core (Python) providing backends, optimizer, AI codegen/validation, and caching. Features include per‑device on‑disk kernel caching, a web API, Docker support, and environment knobs (OPENAI_API_KEY optional for AI‑codegen). The repo (MIT) outlines planned work — multi‑backend benchmarking/policies, correctness suites, training loops for AI‑generated kernels, and tighter PyTorch/JAX integration — and invites GPU/compiler engineers, ML researchers, and frontend devs to contribute. Prereqs: Python 3.10+, platform drivers/toolchains (CUDA/ROCm/OpenCL/MPS).