huggingface / hf-rocm-kernelsLinks
☆23Updated 7 months ago
Alternatives and similar repositories for hf-rocm-kernels
Users that are interested in hf-rocm-kernels are comparing it to the libraries listed below
Sorting:
- ☆15Updated 3 months ago
- Automatic differentiation for Triton Kernels☆29Updated 6 months ago
- Ship correct and fast LLM kernels to PyTorch☆140Updated 3 weeks ago
- ☆32Updated 7 months ago
- TileFusion is an experimental C++ macro kernel template library that elevates the abstraction level in CUDA C for tile processing.☆106Updated 7 months ago
- ☆54Updated 9 months ago
- ☆52Updated 8 months ago
- This repository contains companion software for the Colfax Research paper "Categorical Foundations for CuTe Layouts".☆103Updated 4 months ago
- Framework to reduce autotune overhead to zero for well known deployments.☆96Updated 4 months ago
- extensible collectives library in triton☆95Updated 10 months ago
- DeeperGEMM: crazy optimized version☆73Updated 9 months ago
- ☆65Updated 9 months ago
- ☆39Updated last month
- It is an LLM-based AI agent, which can write correct and efficient gpu kernels automatically.☆60Updated this week
- An experimental communicating attention kernel based on DeepEP.☆35Updated 6 months ago
- A bunch of kernels that might make stuff slower 😉☆75Updated this week
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆165Updated 3 months ago
- A Triton-only attention backend for vLLM☆23Updated last week
- ☆104Updated last year
- ☆95Updated this week
- Wave: Python Domain-Specific Language for High Performance Machine Learning☆42Updated last week
- High-Performance FP32 GEMM on CUDA devices☆117Updated last year
- Debug print operator for cudagraph debugging☆14Updated last year
- Benchmark tests supporting the TiledCUDA library.☆18Updated last year
- Quantized Attention on GPU☆44Updated last year
- Efficient Long-context Language Model Training by Core Attention Disaggregation☆87Updated 2 weeks ago
- Evaluating Large Language Models for CUDA Code Generation ComputeEval is a framework designed to generate and evaluate CUDA code from Lar…☆96Updated last month
- Example of applying CUDA graphs to LLaMA-v2☆12Updated 2 years ago
- FlashInfer Bench @ MLSys 2026: Building AI agents to write high performance GPU kernels☆112Updated this week
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆46Updated 8 months ago