dropbox / gemliteLinks
Fast low-bit matmul kernels in Triton
☆410Updated last week
Alternatives and similar repositories for gemlite
Users that are interested in gemlite are comparing it to the libraries listed below
Sorting:
- Applied AI experiments and examples for PyTorch☆311Updated 4 months ago
- Cataloging released Triton kernels.☆278Updated 3 months ago
- ☆263Updated this week
- Collection of kernels written in Triton language☆173Updated 8 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆301Updated last week
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆244Updated 7 months ago
- A Quirky Assortment of CuTe Kernels☆701Updated last week
- Accelerating MoE with IO and Tile-aware Optimizations☆351Updated last week
- This repository contains the experimental PyTorch native float8 training UX☆227Updated last year
- Fast Hadamard transform in CUDA, with a PyTorch interface☆267Updated 2 months ago
- kernels, of the mega variety☆631Updated 2 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆216Updated 2 weeks ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆276Updated 5 months ago
- a minimal cache manager for PagedAttention, on top of llama3.☆127Updated last year
- Fastest kernels written from scratch☆499Updated 3 months ago
- extensible collectives library in triton☆91Updated 8 months ago
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆148Updated last month
- A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.☆691Updated this week
- ☆253Updated last year
- ring-attention experiments☆160Updated last year
- PyTorch bindings for CUTLASS grouped GEMM.☆135Updated 6 months ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆331Updated last year
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆732Updated 4 months ago
- ☆99Updated last year
- Boosting 4-bit inference kernels with 2:4 Sparsity☆89Updated last year
- Helpful kernel tutorials and examples for tile-based GPU programming☆456Updated this week
- A safetensors extension to efficiently store sparse quantized tensors on disk☆220Updated last week
- Triton-based implementation of Sparse Mixture of Experts.☆257Updated 2 months ago
- A bunch of kernels that might make stuff slower 😉☆69Updated this week
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆123Updated last year