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🚀 Efficient implementations of state-of-the-art linear attention models in Torch and Triton
FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
Distributed Compiler Based on Triton for Parallel Systems
Fast and memory-efficient exact attention
Ongoing research training transformer models at scale
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory…
SGLang is a fast serving framework for large language models and vision language models.
Production-tested AI infrastructure tools for efficient AGI development and community-driven innovation
Analyze computation-communication overlap in V3/R1.
A bidirectional pipeline parallelism algorithm for computation-communication overlap in V3/R1 training.
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
DeepEP: an efficient expert-parallel communication library
Tile primitives for speedy kernels
Important concepts in numerical linear algebra and related areas
A PyTorch native platform for training generative AI models
Development repository for the Triton language and compiler
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more