Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.
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Nov 9, 2026 - Python
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Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.
Fastest MoE/LLM inference runtime for consumer and edge Blackwell GPUs. SN74 on Gittensor.
gpu cuda moe inference-engine gpu-programming mixture-of-experts edge-ai on-device-ai blackwell llm bittensor qwen agentic-ai rtx-5090 kernel-optimization gittensor
Open source skill library for AI coding agents to write, optimize, and debug high performance compute kernels across CUDA, Triton, and quantized workloads.
cuda high-performance-computing triton quantization rocm gpu-kernels prompt-engineering llm-agents ai-coding kernel-optimization
A lightweight, general-purpose framework for evaluating GPU kernel and benchmark.
Pure C++ and HIP inference for gpt-oss on AMD GPUs - no rocBLAS, no RCCL, no MPI. Every kernel, collective and the tokenizer written from scratch. 84,451 tok/s on the 20B and 40,271 on the 120B, on one node of 8x MI250.
cpp amd hip gpu-computing rocm inference-engine mixture-of-experts llm-inference flash-attention mi250 kernel-optimization gpt-oss
Custom Linux kernels purpose-built for Apple Mac hardware
performance linux-kernel arch-linux kvm qemu pvg amdgpu macpro kernel-optimization mac-hardware macos-virtualization
🔥 The living map of LLM-driven kernel generation: 280+ agents, models, benchmarks, and industry systems across NVIDIA, AMD, Ascend, TPU, and more. Continuously updated.
Repo containing artifacts for Neurips 2025 tutorial- How to Build Agents to Generate Kernels for Faster LLMs (and Other Models!)
Agent-queryable ROCm kernel optimization knowledge base for AMD Instinct MI300/gfx942 and MI350/MI355X/gfx950, packaged for Codex CLI and Claude Code with merged-PR provenance, real-silicon validation, and a maintainer-controlled pull-request evidence pipeline.
可验证的 CUDA 学习主线：SGEMM、通用 GPU 算子、性能优化与轻量推理组件
learning education tutorial cplusplus hpc cuda stable gemm inference-engine gpu-programming sgemm cuda-programming ai-infra tensor-core kernel-optimization gpu-kernel
Open reproduction of NVIDIA's AVO paper (arXiv:2603.24517): evolutionary search where an autonomous coding agent IS the variation operator — Vary(P)=Agent(P,K,f). Runs on the Claude Code or Codex session you already have.
mcp evolutionary-algorithms reproducibility 2048 codex expectimax paper-implementation llm-agents coding-agents mcp-server claude-code kernel-optimization
Evidence-driven CUDA, CUTLASS, Triton and GPU workload optimization for ChatGPT · 使用 ChatGPT 驱动 GPU workload 性能优化
performance skills gpu cuda pytorch triton profiling cutlass codex chatgpt vllm llm-inference nsight-compute agent-skills kernel-optimization trtllm
Portable Ascend C and TileLang operator engineering skill with tested workflows and lessons from DeepGEMM and TileKernels.
METAL-SCI: a scientific compute benchmark for evolutionary LLM kernel search on Apple Silicon Metal
benchmark metal scientific-computing code-generation harness gpu-kernels apple-silicon evolutionary-search coding-agents kernel-optimization llm-harness
RWKV-7 FP8 quantized inference - 6.4x decode speedup on Blackwell GPUs with <0.3% accuracy loss. Full FP8 E4M3 weight quantization with fused Triton kernels.
nvidia triton quantization model-quantization blackwell inference-acceleration weight-quantization low-bit-quantization llm fp8 rwkv rwkv7 kernel-optimization rtx-5070-ti e4m3
Fast Triton kernels for multi-scale deformable attention (MSDA) — the core operator behind Deformable DETR, DINO, and Mask2Former — plus a from-scratch course and hands-on labs
education deep-learning gpu cuda pytorch transformer triton object-detection attention-mechanism gpu-kernels gpu-programming deformable-detr deformable-attention triton-lang kernel-optimization
Noeris — autonomous kernel fusion discovery + Triton autotuning for LLM kernels and Gemma layer deeper fusion (A100/H100 wins).
benchmarking cuda pytorch triton autotuning gemma gpu-kernels github-actions kernel-fusion llm-training llm-inference kernel-optimization
Custom AWS Transform agent that migrates PyTorch/Triton kernels to AWS Trainium NKI (@nki.jit) and compiles, numerically verifies, and profiles every candidate on a real Trainium device before opening a PR.
mcp pytorch triton neuron nki code-migration aws-transform llm-agent kernel-optimization aws-trainium amazon-bedrock-agentcore gpu-to-trainium
Extended TileLang as a unified DSL to enable high-performance kernel development for Near-Memory Computing, Distributed Memory AI Accelerators, and Networked Accelerators.
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