Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
☆545Sep 8, 2024Updated last year
Alternatives and similar repositories for cuda_hgemm
Users that are interested in cuda_hgemm are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A Easy-to-understand TensorOp Matmul Tutorial☆438Mar 5, 2026Updated 2 months ago
- ☆160Dec 26, 2024Updated last year
- Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.☆74Sep 8, 2024Updated last year
- A simple high performance CUDA GEMM implementation.☆434Jan 4, 2024Updated 2 years ago
- Yinghan's Code Sample☆364Jul 25, 2022Updated 3 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.☆417Jan 2, 2025Updated last year
- This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several…☆1,303Jul 29, 2023Updated 2 years ago
- ☆267Jul 11, 2024Updated last year
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆47Jun 11, 2025Updated 11 months ago
- Performance of the C++ interface of flash attention and flash attention v2 in large language model (LLM) inference scenarios.☆45Feb 27, 2025Updated last year
- flash attention tutorial written in python, triton, cuda, cutlass☆517Jan 20, 2026Updated 4 months ago
- Fastest kernels written from scratch☆578Sep 18, 2025Updated 8 months ago
- An extension library of WMMA API (Tensor Core API)☆113Jul 12, 2024Updated last year
- how to optimize some algorithm in cuda.☆3,038Updated this week
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- CUDA Matrix Multiplication Optimization☆271Jul 19, 2024Updated last year
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆155May 10, 2025Updated last year
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆81Aug 12, 2024Updated last year
- ☆179May 11, 2026Updated 2 weeks ago
- row-major matmul optimization☆727May 14, 2026Updated 2 weeks ago
- Step-by-step optimization of CUDA SGEMM☆469Mar 30, 2022Updated 4 years ago
- Examples of CUDA implementations by Cutlass CuTe☆275Jul 1, 2025Updated 10 months ago
- ☆154Mar 18, 2024Updated 2 years ago
- Implement Flash Attention using Cute.☆108Dec 17, 2024Updated last year
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- ☆49Apr 15, 2024Updated 2 years ago
- ☆121May 16, 2025Updated last year
- CUDA Templates and Python DSLs for High-Performance Linear Algebra☆9,772Updated this week
- ☆189May 7, 2025Updated last year
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆96Feb 20, 2026Updated 3 months ago
- Matrix Multiply-Accumulate with CUDA and WMMA( Tensor Core)☆147Aug 18, 2020Updated 5 years ago
- Fast CUDA matrix multiplication from scratch☆1,196Sep 2, 2025Updated 8 months ago
- Use tensor core to calculate back-to-back HGEMM (half-precision general matrix multiplication) with MMA PTX instruction.☆13Nov 3, 2023Updated 2 years ago
- A practical way of learning Swizzle☆39Feb 3, 2025Updated last year
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- Standalone Flash Attention v2 kernel without libtorch dependency☆113Sep 10, 2024Updated last year
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆764Aug 6, 2025Updated 9 months ago
- ☆114Apr 19, 2024Updated 2 years ago
- 📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉☆11,118Updated this week
- collection of benchmarks to measure basic GPU capabilities☆520Oct 24, 2025Updated 7 months ago
- CUTLASS and CuTe Examples☆135Nov 30, 2025Updated 5 months ago
- FlashInfer: Kernel Library for LLM Serving☆5,666Updated this week