AlibabaPAI / FLASHNN
☆93Updated 7 months ago
Alternatives and similar repositories for FLASHNN:
Users that are interested in FLASHNN are comparing it to the libraries listed below
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆64Updated 8 months ago
- ☆66Updated 2 weeks ago
- Performance of the C++ interface of flash attention and flash attention v2 in large language model (LLM) inference scenarios.☆36Updated 2 months ago
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆74Updated last month
- ☆57Updated last week
- PyTorch bindings for CUTLASS grouped GEMM.☆87Updated last week
- ☆70Updated 4 months ago
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆91Updated this week
- Implement Flash Attention using Cute.☆78Updated 4 months ago
- Standalone Flash Attention v2 kernel without libtorch dependency☆108Updated 7 months ago
- ☆84Updated last month
- ☆90Updated last month
- ☆104Updated last month
- DeeperGEMM: crazy optimized version☆68Updated this week
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆106Updated 9 months ago
- We invite you to visit and follow our new repository at https://github.com/microsoft/TileFusion. TiledCUDA is a highly efficient kernel …☆181Updated 3 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆120Updated 4 months ago
- A lightweight design for computation-communication overlap.☆35Updated last week
- ☆202Updated 9 months ago
- ☆139Updated last year
- ☆68Updated 3 months ago
- Benchmark code for the "Online normalizer calculation for softmax" paper☆91Updated 6 years ago
- Examples of CUDA implementations by Cutlass CuTe☆170Updated 3 months ago
- ☆73Updated 2 weeks ago
- [USENIX ATC '24] Accelerating the Training of Large Language Models using Efficient Activation Rematerialization and Optimal Hybrid Paral…☆53Updated 9 months ago
- ☆148Updated 3 months ago
- An easy-to-use package for implementing SmoothQuant for LLMs☆97Updated 3 weeks ago
- SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs☆43Updated last month
- A GPU-optimized system for efficient long-context LLMs decoding with low-bit KV cache.☆34Updated last week
- QQQ is an innovative and hardware-optimized W4A8 quantization solution for LLMs.☆120Updated 3 weeks ago