gpu-mode / triton-indexLinks
Cataloging released Triton kernels.
☆247Updated 6 months ago
Alternatives and similar repositories for triton-index
Users that are interested in triton-index are comparing it to the libraries listed below
Sorting:
- ☆227Updated this week
- Applied AI experiments and examples for PyTorch☆289Updated 2 months ago
- Fast low-bit matmul kernels in Triton☆338Updated last week
- A Quirky Assortment of CuTe Kernels☆374Updated this week
- Collection of kernels written in Triton language☆139Updated 3 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆193Updated this week
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆205Updated 2 months ago
- Fastest kernels written from scratch☆308Updated 4 months ago
- ring-attention experiments☆146Updated 9 months ago
- ☆227Updated last year
- a minimal cache manager for PagedAttention, on top of llama3.☆98Updated 11 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆206Updated this week
- This repository contains the experimental PyTorch native float8 training UX☆224Updated last year
- A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.☆200Updated this week
- extensible collectives library in triton☆88Updated 4 months ago
- kernels, of the mega variety☆461Updated 2 months ago
- ☆85Updated 8 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆106Updated 2 months ago
- A collection of memory efficient attention operators implemented in the Triton language.☆273Updated last year
- KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems☆505Updated this week
- A bunch of kernels that might make stuff slower 😉☆56Updated this week
- ☆107Updated 11 months ago
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆565Updated this week
- Fast Hadamard transform in CUDA, with a PyTorch interface☆213Updated last year
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆260Updated 2 weeks ago
- ☆110Updated 4 months ago
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆113Updated last year
- A minimal implementation of vllm.☆50Updated last year
- Triton-based implementation of Sparse Mixture of Experts.☆230Updated 8 months ago
- Perplexity GPU Kernels☆413Updated 2 weeks ago