a-hamdi / native-sparse-attentionLinks
☆15Updated 8 months ago
Alternatives and similar repositories for native-sparse-attention
Users that are interested in native-sparse-attention are comparing it to the libraries listed below
Sorting:
- ☆215Updated 10 months ago
- A curated list of resources for learning and exploring Triton, OpenAI's programming language for writing efficient GPU code.☆427Updated 7 months ago
- making the official triton tutorials actually comprehensible☆60Updated 2 months ago
- 100 days of building GPU kernels!☆523Updated 6 months ago
- GPU Kernels☆203Updated 6 months ago
- ☆14Updated 7 months ago
- Cataloging released Triton kernels.☆264Updated 2 months ago
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆240Updated 6 months ago
- Fast low-bit matmul kernels in Triton☆392Updated 2 weeks ago
- ☆386Updated 6 months ago
- ☆225Updated 2 weeks ago
- Building blocks for foundation models.☆567Updated last year
- A repository to unravel the language of GPUs, making their kernel conversations easy to understand☆195Updated 5 months ago
- LLaMA 2 implemented from scratch in PyTorch☆358Updated 2 years ago
- Learn CUDA with PyTorch☆100Updated last month
- KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA (+ more DSLs)☆642Updated last week
- coding CUDA everyday!☆66Updated last week
- Best practices & guides on how to write distributed pytorch training code☆530Updated 2 weeks ago
- This repository is a curated collection of resources, tutorials, and practical examples designed to guide you through the journey of mast…☆405Updated 8 months ago
- ☆877Updated this week
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆580Updated 2 months ago
- Recreating PyTorch from scratch (C/C++, CUDA, NCCL and Python, with multi-GPU support and automatic differentiation!)☆160Updated last year
- An extension of the nanoGPT repository for training small MOE models.☆207Updated 8 months ago
- All Homeworks for TinyML and Efficient Deep Learning Computing 6.5940 • Fall • 2023 • https://efficientml.ai☆182Updated last year
- Custom kernels in Triton language for accelerating LLMs☆26Updated last year
- Fastest kernels written from scratch☆386Updated last month
- Applied AI experiments and examples for PyTorch☆302Updated 2 months ago
- Notes on quantization in neural networks☆104Updated last year
- ☆545Updated last year
- Collection of kernels written in Triton language☆161Updated 7 months ago