C++20 GPU compute runtime with CUDA-like ergonomics.
-
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.
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.
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.
To associate your repository with the cuda-alternative topic, visit your repo's landing page and select "manage topics."