iclementine / optimize_softmaxLinks
Optimize softmax in triton in many cases
☆21Updated last year
Alternatives and similar repositories for optimize_softmax
Users that are interested in optimize_softmax are comparing it to the libraries listed below
Sorting:
- ☆112Updated 7 months ago
- ☆48Updated last year
- Examples of CUDA implementations by Cutlass CuTe☆263Updated 5 months ago
- ☆59Updated 5 months ago
- 使用 cutlass 实现 flash-attention 精简版,具有教学意义☆52Updated last year
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆78Updated last year
- Implement Flash Attention using Cute.☆98Updated last year
- ☆144Updated last year
- ☆152Updated 11 months ago
- From Minimal GEMM to Everything☆87Updated last month
- ☆20Updated last year
- This project is about convolution operator optimization on GPU, include GEMM based (Implicit GEMM) convolution.☆41Updated 2 months ago
- ☆155Updated last month
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆138Updated 7 months ago
- Optimize GEMM with tensorcore step by step☆36Updated 2 years ago
- ☆70Updated 11 months ago
- ☆119Updated 8 months ago
- CUDA 8-bit Tensor Core Matrix Multiplication based on m16n16k16 WMMA API☆35Updated 2 years ago
- Performance of the C++ interface of flash attention and flash attention v2 in large language model (LLM) inference scenarios.☆43Updated 9 months ago
- 使用 CUDA C++ 实现的 llama 模型推理框架☆63Updated last year
- ☆103Updated last year
- ☆156Updated 11 months ago
- A Easy-to-understand TensorOp Matmul Tutorial☆397Updated 2 months ago
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆96Updated 3 months ago
- Tutorials of Extending and importing TVM with CMAKE Include dependency.☆16Updated last year
- [HPCA 2026] A GPU-optimized system for efficient long-context LLMs decoding with low-bit KV cache.☆71Updated last week
- [ICML 2025] Official PyTorch implementation of "FlatQuant: Flatness Matters for LLM Quantization"☆200Updated last month
- Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.☆70Updated last year
- hands on model tuning with TVM and profile it on a Mac M1, x86 CPU, and GTX-1080 GPU.☆49Updated 2 years ago
- llm theoretical performance analysis tools and support params, flops, memory and latency analysis.☆113Updated 5 months ago