meta-pytorch / applied-aiLinks
Applied AI experiments and examples for PyTorch
☆305Updated 2 months ago
Alternatives and similar repositories for applied-ai
Users that are interested in applied-ai are comparing it to the libraries listed below
Sorting:
- Cataloging released Triton kernels.☆267Updated 2 months ago
- Fast low-bit matmul kernels in Triton☆395Updated 3 weeks ago
- ☆247Updated last week
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆286Updated this week
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆216Updated last week
- Collection of kernels written in Triton language☆167Updated 7 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆130Updated 5 months ago
- This repository contains the experimental PyTorch native float8 training UX☆225Updated last year
- A Quirky Assortment of CuTe Kernels☆660Updated 3 weeks ago
- ☆148Updated 10 months ago
- ☆244Updated last year
- extensible collectives library in triton☆91Updated 7 months ago
- ring-attention experiments☆155Updated last year
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆272Updated 4 months ago
- Fastest kernels written from scratch☆394Updated 2 months ago
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆244Updated 6 months ago
- A collection of memory efficient attention operators implemented in the Triton language.☆284Updated last year
- ☆93Updated last year
- PyTorch bindings for CUTLASS grouped GEMM.☆167Updated last month
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆134Updated last week
- Triton-based implementation of Sparse Mixture of Experts.☆248Updated last month
- ☆113Updated last year
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆328Updated last year
- 🚀 Efficiently (pre)training foundation models with native PyTorch features, including FSDP for training and SDPA implementation of Flash…☆272Updated 2 weeks ago
- Fast Hadamard transform in CUDA, with a PyTorch interface☆257Updated last month
- kernels, of the mega variety☆608Updated last month
- a minimal cache manager for PagedAttention, on top of llama3.☆125Updated last year
- A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.☆620Updated last week
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆121Updated last year
- Triton-based Symmetric Memory operators and examples☆63Updated last month