nvixnu / pmpp__programming_massively_parallel_processorsLinks
Examples and exercises from the book Programming Massively Parallel Processors - A Hands-on Approach. David B. Kirk and Wen-mei W. Hwu (Third Edition)
☆67Updated 4 years ago
Alternatives and similar repositories for pmpp__programming_massively_parallel_processors
Users that are interested in pmpp__programming_massively_parallel_processors are comparing it to the libraries listed below
Sorting:
- CUDA Matrix Multiplication Optimization☆188Updated 10 months ago
- Matrix Multiply-Accumulate with CUDA and WMMA( Tensor Core)☆134Updated 4 years ago
- Cataloging released Triton kernels.☆226Updated 4 months ago
- Benchmark code for the "Online normalizer calculation for softmax" paper☆93Updated 6 years ago
- A Easy-to-understand TensorOp Matmul Tutorial☆359Updated 8 months ago
- ring-attention experiments☆143Updated 7 months ago
- Step-by-step optimization of CUDA SGEMM☆327Updated 3 years ago
- ☆109Updated 3 weeks ago
- CUTLASS and CuTe Examples☆52Updated 5 months ago
- We invite you to visit and follow our new repository at https://github.com/microsoft/TileFusion. TiledCUDA is a highly efficient kernel …☆182Updated 4 months ago
- Solution of Programming Massively Parallel Processors☆47Updated last year
- A simple high performance CUDA GEMM implementation.☆374Updated last year
- ☆208Updated 10 months ago
- ☆73Updated 2 weeks ago
- ☆105Updated 2 months ago
- ☆79Updated 6 months ago
- A lightweight design for computation-communication overlap.☆132Updated 3 weeks ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆127Updated this week
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆79Updated 3 weeks ago
- 📚 A curated list of awesome matrix-matrix multiplication (A * B = C) frameworks, libraries and software☆35Updated 3 months ago
- ☆204Updated 6 months ago
- flash attention tutorial written in python, triton, cuda, cutlass☆368Updated 3 weeks ago
- Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.☆62Updated 8 months ago
- Examples of CUDA implementations by Cutlass CuTe☆188Updated 4 months ago
- Standalone Flash Attention v2 kernel without libtorch dependency☆109Updated 8 months ago
- ☆86Updated 5 months ago
- Implement Flash Attention using Cute.☆85Updated 5 months ago
- Fastest kernels written from scratch☆269Updated 2 months ago
- 📚FFPA(Split-D): Extend FlashAttention with Split-D for large headdim, O(1) GPU SRAM complexity, 1.8x~3x↑🎉 faster than SDPA EA.☆183Updated 3 weeks ago
- ☆169Updated last year