zinccat / Awesome-Triton-KernelsLinks
Collection of kernels written in Triton language
☆154Updated 5 months ago
Alternatives and similar repositories for Awesome-Triton-Kernels
Users that are interested in Awesome-Triton-Kernels are comparing it to the libraries listed below
Sorting:
- Cataloging released Triton kernels.☆252Updated this week
- Applied AI experiments and examples for PyTorch☆295Updated 3 weeks ago
- Fast low-bit matmul kernels in Triton☆357Updated last week
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆221Updated this week
- ☆233Updated 3 weeks ago
- ☆88Updated 10 months ago
- extensible collectives library in triton☆88Updated 5 months ago
- ring-attention experiments☆150Updated 10 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆113Updated 3 months ago
- Triton-based implementation of Sparse Mixture of Experts.☆238Updated 2 weeks ago
- A Quirky Assortment of CuTe Kernels☆450Updated last week
- ☆110Updated last year
- This repository contains the experimental PyTorch native float8 training UX☆224Updated last year
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆263Updated last month
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆209Updated last week
- Fast Hadamard transform in CUDA, with a PyTorch interface☆231Updated last week
- A bunch of kernels that might make stuff slower 😉☆58Updated 2 weeks ago
- a minimal cache manager for PagedAttention, on top of llama3.☆120Updated last year
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆219Updated 4 months ago
- A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.☆289Updated last week
- ☆230Updated last year
- Fastest kernels written from scratch☆323Updated 5 months ago
- Framework to reduce autotune overhead to zero for well known deployments.☆81Updated last week
- A minimal implementation of vllm.☆52Updated last year
- A collection of memory efficient attention operators implemented in the Triton language.☆277Updated last year
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆114Updated last year
- Boosting 4-bit inference kernels with 2:4 Sparsity☆82Updated last year
- QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference☆118Updated last year
- [ICLR 2025] Palu: Compressing KV-Cache with Low-Rank Projection☆138Updated 6 months ago
- Explore training for quantized models☆24Updated 2 months ago