gpu-mode / triton-indexLinks
Cataloging released Triton kernels.
☆261Updated 3 weeks ago
Alternatives and similar repositories for triton-index
Users that are interested in triton-index are comparing it to the libraries listed below
Sorting:
- ☆240Updated last week
- Applied AI experiments and examples for PyTorch☆296Updated last month
- Fast low-bit matmul kernels in Triton☆373Updated last week
- Collection of kernels written in Triton language☆155Updated 5 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆230Updated this week
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆226Updated 4 months ago
- A Quirky Assortment of CuTe Kernels☆603Updated this week
- Fastest kernels written from scratch☆366Updated 2 weeks ago
- ☆238Updated last year
- a minimal cache manager for PagedAttention, on top of llama3.☆122Updated last year
- extensible collectives library in triton☆88Updated 6 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆123Updated 4 months ago
- ring-attention experiments☆152Updated 11 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆213Updated last week
- A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.☆318Updated last week
- This repository contains the experimental PyTorch native float8 training UX☆224Updated last year
- ☆90Updated 10 months ago
- kernels, of the mega variety☆563Updated this week
- Fast Hadamard transform in CUDA, with a PyTorch interface☆239Updated 3 weeks ago
- KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems☆581Updated 2 weeks ago
- ☆121Updated 9 months ago
- A bunch of kernels that might make stuff slower 😉☆59Updated last week
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆99Updated 3 weeks ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆265Updated 2 months ago
- Learn CUDA with PyTorch☆84Updated last week
- A collection of memory efficient attention operators implemented in the Triton language.☆279Updated last year
- ☆118Updated 6 months ago
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆576Updated last month
- Perplexity GPU Kernels☆476Updated 2 weeks ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆320Updated last year