ademeure / DeeperGEMMLinks
DeeperGEMM: crazy optimized version
☆73Updated 7 months ago
Alternatives and similar repositories for DeeperGEMM
Users that are interested in DeeperGEMM are comparing it to the libraries listed below
Sorting:
- ☆65Updated 7 months ago
- An experimental communicating attention kernel based on DeepEP.☆35Updated 4 months ago
- ☆52Updated 7 months ago
- NVSHMEM‑Tutorial: Build a DeepEP‑like GPU Buffer☆147Updated 3 months ago
- Framework to reduce autotune overhead to zero for well known deployments.☆90Updated 3 months ago
- TileFusion is an experimental C++ macro kernel template library that elevates the abstraction level in CUDA C for tile processing.☆105Updated 5 months ago
- A lightweight design for computation-communication overlap.☆196Updated 2 months ago
- Debug print operator for cudagraph debugging☆14Updated last year
- Tile-based language built for AI computation across all scales☆98Updated last week
- ☆114Updated 7 months ago
- ☆67Updated this week
- ☆103Updated last year
- Building the Virtuous Cycle for AI-driven LLM Systems☆98Updated last week
- ☆83Updated 10 months ago
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆138Updated 7 months ago
- ☆31Updated 5 months ago
- ☆38Updated 5 months ago
- ☆39Updated last week
- DLSlime: Flexible & Efficient Heterogeneous Transfer Toolkit☆84Updated this week
- Quantized Attention on GPU☆44Updated last year
- ☆39Updated 4 months ago
- DeepXTrace is a lightweight tool for precisely diagnosing slow ranks in DeepEP-based environments.☆75Updated this week
- ☆99Updated last year
- Implement Flash Attention using Cute.☆98Updated last year
- PyTorch bindings for CUTLASS grouped GEMM.☆135Updated 6 months ago
- DeepSeek-V3.2-Exp DSA Warmup Lightning Indexer training operator based on tilelang☆37Updated last month
- ☆125Updated 4 months ago
- Autonomous GPU Kernel Generation via Deep Agents☆187Updated this week
- A Triton JIT runtime and ffi provider in C++☆29Updated last week
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆123Updated last year