Alternatives and similar repositories for APPy:

Users that are interested in APPy are comparing it to the libraries listed below

• GindaChen / FlexFlashAttention3
  FlexAttention w/ FlashAttention3 Support
  ☆26Updated 6 months ago
• feifeibear / ChituAttention
  Quantized Attention on GPU
  ☆45Updated 4 months ago
• glassroom / heinsen_attention
  Reference implementation of "Softmax Attention with Constant Cost per Token" (Heinsen, 2024)
  ☆24Updated 9 months ago
• feifeibear / Odysseus-Transformer
  Odysseus: Playground of LLM Sequence Parallelism
  ☆68Updated 9 months ago
• pytorch-labs / tritonbench
  Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.
  ☆107Updated this week
• IBM / triton-dejavu
  Framework to reduce autotune overhead to zero for well known deployments.
  ☆63Updated last week
• hazan-lab / flash-stu
  PyTorch implementation of the Flash Spectral Transform Unit.
  ☆16Updated 6 months ago
• tridao / flash-attention-wheels
  ☆46Updated last year
• NX-AI / flashrnn
  FlashRNN - Fast RNN Kernels with I/O Awareness
  ☆76Updated last week
• BBuf / flash-rwkv
  ☆30Updated 10 months ago
• INT-FlashAttention2024 / INT-FlashAttention
  ☆68Updated 2 months ago
• dame-cell / Triformer
  Transformers components but in Triton
  ☆32Updated 2 weeks ago
• Aleph-Alpha / NeurIPS-WANT-submission-efficient-parallelization-layouts
  ☆22Updated last year
• LeiWang1999 / AutoGPTQ.tvm
  GPTQ inference TVM kernel
  ☆38Updated 11 months ago
• sustcsonglin / fla-tilelang
  ☆19Updated 3 weeks ago
• TiledTensor / TiledBench
  Benchmark tests supporting the TiledCUDA library.
  ☆16Updated 4 months ago
• microsoft / TileFusion
  TileFusion is an experimental C++ macro kernel template library that elevates the abstraction level in CUDA C for tile processing.
  ☆74Updated this week
• microsoft / AttentionEngine
  ☆55Updated this week
• tgale96 / grouped_gemm
  PyTorch bindings for CUTLASS grouped GEMM.
  ☆77Updated 5 months ago
• Bruce-Lee-LY / decoding_attention
  Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.
  ☆35Updated 3 weeks ago
• facebookresearch / MODel_opt
  Memory Optimizations for Deep Learning (ICML 2023)
  ☆62Updated last year
• WaveSpeedAI / QuantumAttention
  [WIP] Better (FP8) attention for Hopper
  ☆26Updated last month
• Doraemonzzz / Awesome-Triton-Resources
  Awesome Triton Resources
  ☆23Updated last week
• ademeure / DeeperGEMM
  DeeperGEMM: crazy optimized version
  ☆64Updated this week
• IST-DASLab / QIGen
  Repository for CPU Kernel Generation for LLM Inference
  ☆25Updated last year
• alexzhang13 / Triton-Puzzles-Solutions
  Personal solutions to the Triton Puzzles
  ☆18Updated 8 months ago
• BlinkDL / LinearAttentionArena
  Here we will test various linear attention designs.
  ☆60Updated 11 months ago
• PipeFusion / PipeFusion
  A Suite for Parallel Inference of Diffusion Transformers (DiTs) on multi-GPU Clusters
  ☆44Updated 8 months ago
• graphcore-research / out-of-the-box-fp8-training
  Demo of the unit_scaling library, showing how a model can be easily adapted to train in FP8.
  ☆45Updated 8 months ago
• Raincleared-Song / sparse_gpu_operator
  GPU operators for sparse tensor operations
  ☆31Updated last year