C++20 GPU compute runtime with CUDA-like ergonomics.
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Updated
Jul 24, 2026 - C++
C++20 GPU compute runtime with CUDA-like ergonomics.
CUDA-equivalent tensor-core acceleration for Apple Silicon. C-ABI kernel library wrapping simdgroup_matrix (M1+) and mpp::tensor_ops (M5+): GEMM, FlashAttention, Conv2D, Q4_0/Q8_0 quantized inference, GGUF reader, full transformer training kernels. One binary, M1 → M5.
Environment diagnostics, compatibility resolver, and a live-tracked map of the Python AI ecosystem on AMD ROCm.
Native Apple Silicon Metal port of mumax3, extending CUDA based micromagnetic simulation to macOS with MPSGraph FFT and validated physics compatibility.
Système d'exploitation Exokernel "Bare-Metal" et langage dédié (Neuro-Lang) pour l'IA. Élimination de la "Taxe d'Abstraction" : exécution Ring-0, mémoire unifiée SASOS et accès GPU direct sans latenc
From-scratch LLM inference engine for Apple Silicon: hand-written Metal kernels (simdgroup_matrix GEMM, FlashAttention prefill, paged-attention decode), paged KV cache, continuous batching, OpenAI-compatible server. C++17, no PyTorch/llama.cpp/MLX.
Custom C++/HIP inference engine for Qwen3.8-27B on 4x AMD MI50 (gfx906/ROCm). Written from scratch - not llama.cpp, not a wrapper, no Python in the execution path. 103.7 tok/s with chained MTP speculative decoding.
GPU-accelerated Sobel edge detection using OpenCL. Features a high-performance "Universal Tiling" implementation with local memory (SRAM) caching and strided loading, achieving a 138x speedup on NVIDIA K20 hardware.
An open, vendor-neutral compute language — CUDA's grid-of-threads model without the lock-in. One language for AI, hashing and graphics; targets Apple Metal today, FPGA/custom silicon next.
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