Minimal FlashAttention in CUDA C++/CuTe: readable WMMA/CuTe kernels, no NxN workspace, up to 4.5x faster than naive PyTorch
GitHub repository with 21 stars and 1 forks.
Language: Cuda
Topics: attention, cuda, cute, cutlass, flash-attention, flashattention, gpu-kernels, llm, pytorch-extension, tensor-cores
Trending score 1.02, activity score 0.03, stars gained +9, forks gained +1.
2026-06-05: 21 stars and 1 forks.
Minimal FlashAttention in CUDA C++/CuTe: readable WMMA/CuTe kernels, no NxN workspace, up to 4.5x faster than naive PyTorch
GitHub repository with 21 stars and 1 forks.
Trending score: 1.02; stars gained: +9; forks gained: +1.
Language: Cuda
Topics: attention, cuda, cute, cutlass, flash-attention, flashattention
Minimal FlashAttention in CUDA C++/CuTe: readable WMMA/CuTe kernels, no NxN workspace, up to 4.5x faster than naive PyTorch
GitHub repository with 21 stars and 1 forks.
Trending score: 1.02; stars gained: +9; forks gained: +1.
Language: Cuda
Topics: attention, cuda, cute, cutlass, flash-attention, flashattention
"brainflayer" CUDA & private key recovery tool
GitHub repository with 6 stars and 4 forks.
Trending score: 0.05; stars gained: +0; forks gained: +0.
Language: Cuda
Learn CUDA with PyTorch
GitHub repository with 313 stars and 49 forks.
Trending score: 0.04; stars gained: +0; forks gained: +0.
Language: Cuda
GitHub repository with 14 stars and 1 forks.
Trending score: 0.04; stars gained: +0; forks gained: +0.
Language: Cuda
This repository contains the official implementation of Semantic Foam: Unifying Spatial and Semantic Scene Decomposition
GitHub repository with 10 stars and 0 forks.
Trending score: 0.04; stars gained: +0; forks gained: +0.
Language: Cuda
SGLang is a high-performance serving framework for large language models and multimodal models.
GitHub repository with 28,863 stars and 6,350 forks.
Trending score: 1.72; stars gained: -55; forks gained: +18.
Language: Python
Topics: attention, blackwell, cuda, deepseek, diffusion, glm
FlashInfer: Kernel Library for LLM Serving
GitHub repository with 5,752 stars and 1,026 forks.
Trending score: 1.16; stars gained: +15; forks gained: +8.
Language: Python
Topics: attention, cuda, distributed-inference, gpu, jit, large-large-models
Minimal FlashAttention in CUDA C++/CuTe: readable WMMA/CuTe kernels, no NxN workspace, up to 4.5x faster than naive PyTorch
GitHub repository with 21 stars and 1 forks.
Trending score: 1.02; stars gained: +9; forks gained: +1.
Language: Cuda
Topics: attention, cuda, cute, cutlass, flash-attention, flashattention
A hands-on course for building modern LLMs from scratch in PyTorch, with 23 runnable Jupyter Notebooks covering tokenizers, attention, MoE, RLHF, inference, evaluation, and distillation.
GitHub repository with 38 stars and 9 forks.
Trending score: 0.87; stars gained: +1; forks gained: +1.
Language: Jupyter Notebook
Topics: ai, attention, finetune, gpt, large-language-models, llm
TableMamba is a Mamba-based sequential recommender that encodes a user's interaction history with selective state-space blocks and a multi-interest head of M parallel SSM readers at log-spaced timescales, scoring items by their best-matching interest in O(T).
GitHub repository with 9 stars and 0 forks.
Trending score: 0.31; stars gained: +1; forks gained: +0.
Language: Python
Topics: ai, ai-research, attention, deepseek, mamba, ml
🛡️ Develop an external Rust cheat using AI-driven stealth kernel techniques to bypass EAC detection with advanced memory and execution hooks.
GitHub repository with 5 stars and 2 forks.
Trending score: 0.05; stars gained: +0; forks gained: +0.
Language: C++
Topics: attention, aws, compiler, data-structures, dns, dns-controller