☆261Jul 11, 2024Updated last year
Alternatives and similar repositories for cutlass-kernels
Users that are interested in cutlass-kernels are comparing it to the libraries listed below
Sorting:
- ☆178May 7, 2025Updated 9 months ago
- ☆115May 16, 2025Updated 9 months ago
- A Easy-to-understand TensorOp Matmul Tutorial☆410Feb 11, 2026Updated 2 weeks ago
- We invite you to visit and follow our new repository at https://github.com/microsoft/TileFusion. TiledCUDA is a highly efficient kernel …☆193Jan 28, 2025Updated last year
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆79Aug 12, 2024Updated last year
- flash attention tutorial written in python, triton, cuda, cutlass☆488Jan 20, 2026Updated last month
- TileFusion is an experimental C++ macro kernel template library that elevates the abstraction level in CUDA C for tile processing.☆106Jun 28, 2025Updated 8 months ago
- ☆168Feb 5, 2026Updated 3 weeks ago
- Examples of CUDA implementations by Cutlass CuTe☆269Jul 1, 2025Updated 8 months ago
- Benchmark tests supporting the TiledCUDA library.☆18Nov 19, 2024Updated last year
- Implement Flash Attention using Cute.☆101Dec 17, 2024Updated last year
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆46Jun 11, 2025Updated 8 months ago
- Standalone Flash Attention v2 kernel without libtorch dependency☆114Sep 10, 2024Updated last year
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆96Feb 20, 2026Updated last week
- Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruct…☆526Sep 8, 2024Updated last year
- ☆65Apr 26, 2025Updated 10 months ago
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆147May 10, 2025Updated 9 months ago
- Perplexity GPU Kernels☆567Nov 7, 2025Updated 3 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆327Updated this week
- Tile primitives for speedy kernels☆3,183Feb 24, 2026Updated last week
- Framework to reduce autotune overhead to zero for well known deployments.☆97Sep 19, 2025Updated 5 months ago
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆1,025Sep 4, 2024Updated last year
- Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.☆72Sep 8, 2024Updated last year
- A fast communication-overlapping library for tensor/expert parallelism on GPUs.☆1,261Aug 28, 2025Updated 6 months ago
- A Quirky Assortment of CuTe Kernels☆814Feb 23, 2026Updated last week
- ☆52May 19, 2025Updated 9 months ago
- Applied AI experiments and examples for PyTorch☆319Aug 22, 2025Updated 6 months ago
- study of cutlass☆22Nov 10, 2024Updated last year
- NVSHMEM‑Tutorial: Build a DeepEP‑like GPU Buffer☆163Feb 11, 2026Updated 2 weeks ago
- PyTorch bindings for CUTLASS grouped GEMM.☆143May 29, 2025Updated 9 months ago
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆751Aug 6, 2025Updated 6 months ago
- Fastest kernels written from scratch☆548Sep 18, 2025Updated 5 months ago
- ☆49Apr 15, 2024Updated last year
- Multiple GEMM operators are constructed with cutlass to support LLM inference.☆20Aug 3, 2025Updated 7 months ago
- Fast low-bit matmul kernels in Triton☆433Feb 1, 2026Updated last month
- Distributed Compiler based on Triton for Parallel Systems☆1,371Feb 13, 2026Updated 2 weeks ago
- CUTLASS and CuTe Examples☆132Nov 30, 2025Updated 3 months ago
- ☆104Sep 9, 2024Updated last year
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆816Mar 6, 2025Updated 11 months ago