gpu-mode / ring-attention
ring-attention experiments
☆132Updated 6 months ago
Alternatives and similar repositories for ring-attention:
Users that are interested in ring-attention are comparing it to the libraries listed below
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆120Updated this week
- Cataloging released Triton kernels.☆220Updated 3 months ago
- ☆202Updated last week
- ☆104Updated 8 months ago
- Collection of kernels written in Triton language☆120Updated last month
- This repository contains the experimental PyTorch native float8 training UX☆224Updated 9 months ago
- Applied AI experiments and examples for PyTorch☆262Updated last week
- Fast low-bit matmul kernels in Triton☆295Updated this week
- Triton-based implementation of Sparse Mixture of Experts.☆212Updated 5 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆87Updated this week
- 🚀 Efficiently (pre)training foundation models with native PyTorch features, including FSDP for training and SDPA implementation of Flash…☆244Updated this week
- A bunch of kernels that might make stuff slower 😉☆40Updated this week
- ☆78Updated 5 months ago
- Official repository for DistFlashAttn: Distributed Memory-efficient Attention for Long-context LLMs Training☆209Updated 8 months ago
- extensible collectives library in triton☆85Updated last month
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆169Updated last month
- ☆84Updated last month
- 🔥 A minimal training framework for scaling FLA models☆117Updated this week
- Boosting 4-bit inference kernels with 2:4 Sparsity☆73Updated 8 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆120Updated 4 months ago
- Odysseus: Playground of LLM Sequence Parallelism☆69Updated 10 months ago
- ☆103Updated 11 months ago
- Perplexity GPU Kernels☆272Updated this week
- Flash-Muon: An Efficient Implementation of Muon Optimzer☆91Updated this week
- [ICLR2025] Breaking Throughput-Latency Trade-off for Long Sequences with Speculative Decoding☆115Updated 5 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆194Updated this week
- Efficient triton implementation of Native Sparse Attention.☆142Updated 3 weeks ago
- ☆202Updated 9 months ago
- Small scale distributed training of sequential deep learning models, built on Numpy and MPI.☆130Updated last year
- [ICLR 2025] COAT: Compressing Optimizer States and Activation for Memory-Efficient FP8 Training☆189Updated 2 weeks ago