phonism / genesisLinks
Gensis is a lightweight deep learning framework written from scratch in Python, with Triton as its backend for high-performance computing.
☆22Updated this week
Alternatives and similar repositories for genesis
Users that are interested in genesis are comparing it to the libraries listed below
Sorting:
- Implement Flash Attention using Cute.☆94Updated 8 months ago
- ☆141Updated last month
- ☆98Updated 3 months ago
- ☆97Updated 11 months ago
- 🤖FFPA: Extend FlashAttention-2 with Split-D, ~O(1) SRAM complexity for large headdim, 1.8x~3x↑🎉 vs SDPA EA.☆211Updated 2 weeks ago
- A practical way of learning Swizzle☆25Updated 6 months ago
- ☆91Updated last week
- ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, Achieve Peak⚡️ Performance.☆100Updated 3 months ago
- ☆145Updated 5 months ago
- Code release for book "Efficient Training in PyTorch"☆83Updated 4 months ago
- Triton Documentation in Chinese Simplified / Triton 中文文档☆80Updated 4 months ago
- Tile-based language built for AI computation across all scales☆46Updated this week
- ☆92Updated 4 months ago
- LLM Inference with Deep Learning Accelerator.☆49Updated 7 months ago
- ☆78Updated 4 months ago
- gLLM: Global Balanced Pipeline Parallelism System for Distributed LLM Serving with Token Throttling☆37Updated last week
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆74Updated last year
- SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs☆52Updated 5 months ago
- DeeperGEMM: crazy optimized version☆71Updated 3 months ago
- We invite you to visit and follow our new repository at https://github.com/microsoft/TileFusion. TiledCUDA is a highly efficient kernel …☆183Updated 6 months ago
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆94Updated 2 weeks ago
- 使用 CUDA C++ 实现的 llama 模型推理框架☆60Updated 9 months ago
- Triton adapter for Ascend. Mirror of https://gitee.com/ascend/triton-ascend☆64Updated this week
- ☆43Updated last year
- GPTQ inference TVM kernel☆40Updated last year
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆40Updated 2 months ago
- ☆39Updated last year
- A prefill & decode disaggregated LLM serving framework with shared GPU memory and fine-grained compute isolation.☆104Updated 3 months ago
- ☆61Updated 3 months ago
- ☆138Updated last year