zeroine / cutlass-cute-sample
☆30Updated last year
Alternatives and similar repositories for cutlass-cute-sample:
Users that are interested in cutlass-cute-sample are comparing it to the libraries listed below
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆63Updated 8 months ago
- ☆60Updated this week
- Standalone Flash Attention v2 kernel without libtorch dependency☆108Updated 7 months ago
- Optimize GEMM with tensorcore step by step☆25Updated last year
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆91Updated 3 weeks ago
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆73Updated 3 weeks ago
- Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.☆61Updated 7 months ago
- ☆11Updated last month
- ☆15Updated 3 weeks ago
- ☆88Updated 3 weeks ago
- Tutorials of Extending and importing TVM with CMAKE Include dependency.☆13Updated 6 months ago
- SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs☆42Updated last month
- Implement Flash Attention using Cute.☆76Updated 4 months ago
- play gemm with tvm☆90Updated last year
- Benchmark code for the "Online normalizer calculation for softmax" paper☆91Updated 6 years ago
- llama INT4 cuda inference with AWQ☆54Updated 3 months ago
- Examples of CUDA implementations by Cutlass CuTe☆159Updated 2 months ago
- 使用 CUDA C++ 实现的 llama 模型推理框架☆50Updated 5 months ago
- Performance of the C++ interface of flash attention and flash attention v2 in large language model (LLM) inference scenarios.☆35Updated last month
- ☆115Updated 4 months ago
- A GPU-optimized system for efficient long-context LLMs decoding with low-bit KV cache.☆33Updated 3 weeks ago
- ☆102Updated last month
- This project is about convolution operator optimization on GPU, include GEMM based (Implicit GEMM) convolution.☆29Updated 3 months ago
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆36Updated 3 weeks ago
- ☆28Updated 2 months ago
- Optimize softmax in triton in many cases☆20Updated 7 months ago
- Artifacts of EVT ASPLOS'24☆23Updated last year
- study of cutlass☆21Updated 5 months ago
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆106Updated 9 months ago
- ☆92Updated 7 months ago