Alternatives and similar repositories for accelerated-model-architectures

Users that are interested in accelerated-model-architectures are comparing it to the libraries listed below

• cchan / tccl
  extensible collectives library in triton
  ☆90Updated 6 months ago
• meta-pytorch / kraken
  Triton-based Symmetric Memory operators and examples
  ☆48Updated last week
• gpu-mode / ring-attention
  ring-attention experiments
  ☆155Updated last year
• Deep-Learning-Profiling-Tools / triton-viz
  ☆242Updated this week
• zinccat / Awesome-Triton-Kernels
  Collection of kernels written in Triton language
  ☆157Updated 6 months ago
• gpu-mode / triton-index
  Cataloging released Triton kernels.
  ☆263Updated last month
• triton-lang / kernels
  ☆93Updated 11 months ago
• meta-pytorch / applied-ai
  Applied AI experiments and examples for PyTorch
  ☆299Updated 2 months ago
• shawntan / scattermoe
  Triton-based implementation of Sparse Mixture of Experts.
  ☆246Updated 3 weeks ago
• IST-DASLab / qutlass
  QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning
  ☆120Updated this week
• dropbox / gemlite
  Fast low-bit matmul kernels in Triton
  ☆385Updated last week
• meta-pytorch / float8_experimental
  This repository contains the experimental PyTorch native float8 training UX
  ☆223Updated last year
• tgale96 / grouped_gemm
  PyTorch bindings for CUTLASS grouped GEMM.
  ☆125Updated 4 months ago
• stanford-futuredata / stk
  ☆112Updated last year
• meta-pytorch / tritonbench
  Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.
  ☆264Updated this week
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆84Updated last year
• IBM / triton-dejavu
  Framework to reduce autotune overhead to zero for well known deployments.
  ☆84Updated last month
• ademeure / QuickRunCUDA
  ☆13Updated 3 weeks ago
• meta-pytorch / BackendBench
  How to ensure correctness and ship LLM generated kernels in PyTorch
  ☆107Updated last week
• HanGuo97 / hilt
  ☆35Updated this week
• gau-nernst / quantized-training
  Explore training for quantized models
  ☆25Updated 3 months ago
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆117Updated last year
• andylolu2 / simpleGEMM
  The simplest but fast implementation of matrix multiplication in CUDA.
  ☆39Updated last year
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆215Updated this week
• pytorch / helion
  A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.
  ☆491Updated this week
• gau-nernst / learn-cuda
  Learn CUDA with PyTorch
  ☆92Updated last month
• nil0x9 / flash-muon
  Flash-Muon: An Efficient Implementation of Muon Optimizer
  ☆197Updated 4 months ago
• tspeterkim / paged-attention-minimal
  a minimal cache manager for PagedAttention, on top of llama3.
  ☆124Updated last year
• MekkCyber / CutlassAcademy
  A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS
  ☆233Updated 5 months ago
• Dao-AILab / gemm-cublas
  ☆23Updated 5 months ago