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Distributed Triton for Parallel Systems
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
LLMs-from-scratch项目中文翻译
how to optimize some algorithm in cuda.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
A high-throughput and memory-efficient inference and serving engine for LLMs
GPU programming related news and material links
Implementation of FlashAttention in PyTorch
FlashMLA: Efficient MLA decoding kernels
Development repository for the Triton language and compiler
📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA/Tensor Cores Kernels, HGEMM, FA-2 MMA etc.🔥
SGLang is a fast serving framework for large language models and vision language models.
My learning notes/codes for ML SYS.
A 120-day CUDA learning plan covering daily concepts, exercises, pitfalls, and references (including “Programming Massively Parallel Processors”). Features six capstone projects to solidify GPU par…
A collection of simple Bash scripts
A visualized debugging framework to aid in understanding the Linux kernel.
The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++