Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.

The Platform for Self-Improving Code. Ideal for GPU kernels, ML model development, feature engineering, prompt engineering, and other optimizable code.

Custom Linux kernels purpose-built for Apple Mac hardware

Forge: Swarm Agents That Turn Slow PyTorch Into Fast CUDA/Triton Kernels

Extended TileLang as a unified DSL to enable high-performance kernel development for Near-Memory Computing, Distributed Memory AI Accelerators, and Networked Accelerators.

A collection of high-performance CUDA kernels and experiments for learning and optimizing GPU compute primitives.

Optimized Ubuntu Touch for Lenovo Tab M8 HD (TB-8505F) - Kernel improvements, performance tuning, boot experience, and system optimizations for the MediaTek Helio A22 tablet

CUDA HPC Kernel Optimization Textbook: Naive to Tensor Core — GEMM, FlashAttention & Quantization | CUDA 高性能算子开发教科书：从 Naive 到 Tensor Core 完整优化路径，涵盖 GEMM/FlashAttention/量化

The Ultimate Kernel Orchestration Suite for Windows. Optimized for low-latency development and high-priority workloads.

Skill pack for custom PyTorch MPS kernels on Apple Silicon (examples, tests, and optimization patterns).

CUDA Kernel Library for LLM Inference: FlashAttention, HGEMM, Tensor Core GEMM with pybind11 Bindings | LLM 推理加速 CUDA Kernel 库：FlashAttention、HGEMM、Tensor Core GEMM，含 pybind11 Python 绑定