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| { |
| "repo_name": "goose", |
| "repo_link": "https://github.com/block/goose", |
| "category": "agent", |
| "github_about_section": "an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM", |
| "homepage_link": "https://block.github.io/goose", |
| "github_topic_closest_fit": "mcp" |
| }, |
| { |
| "repo_name": "ray", |
| "repo_link": "https://github.com/ray-project/ray", |
| "category": "ai compute engine", |
| "github_about_section": "Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.", |
| "homepage_link": "https://ray.io", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "flashinfer-bench", |
| "repo_link": "https://github.com/flashinfer-ai/flashinfer-bench", |
| "category": "benchmark", |
| "github_about_section": "Building the Virtuous Cycle for AI-driven LLM Systems", |
| "homepage_link": "https://bench.flashinfer.ai", |
| "github_topic_closest_fit": "benchmark" |
| }, |
| { |
| "repo_name": "KernelBench", |
| "repo_link": "https://github.com/ScalingIntelligence/KernelBench", |
| "category": "benchmark", |
| "github_about_section": "KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems", |
| "homepage_link": "https://scalingintelligence.stanford.edu/blogs/kernelbench", |
| "github_topic_closest_fit": "benchmark" |
| }, |
| { |
| "repo_name": "SWE-bench", |
| "repo_link": "https://github.com/SWE-bench/SWE-bench", |
| "category": "benchmark", |
| "github_about_section": "SWE-bench: Can Language Models Resolve Real-world Github Issues?", |
| "homepage_link": "https://swebench.com", |
| "github_topic_closest_fit": "benchmark" |
| }, |
| { |
| "repo_name": "terminal-bench", |
| "repo_link": "https://github.com/laude-institute/terminal-bench", |
| "category": "benchmark", |
| "github_about_section": "A benchmark for LLMs on complicated tasks in the terminal", |
| "homepage_link": "https://tbench.ai", |
| "github_topic_closest_fit": "benchmark" |
| }, |
| { |
| "repo_name": "TritonBench", |
| "repo_link": "https://github.com/thunlp/TritonBench", |
| "category": "benchmark", |
| "github_about_section": "TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators", |
| "homepage_link": "https://arxiv.org/abs/2502.14752", |
| "github_topic_closest_fit": "benchmark" |
| }, |
| { |
| "repo_name": "BitBLAS", |
| "repo_link": "https://github.com/microsoft/BitBLAS", |
| "category": "Basic Linear Algebra Subprograms (BLAS)", |
| "github_about_section": "BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.", |
| "github_topic_closest_fit": "matrix-multiplication" |
| }, |
| { |
| "repo_name": "hipBLAS", |
| "repo_link": "https://github.com/ROCm/hipBLAS", |
| "category": "Basic Linear Algebra Subprograms (BLAS)", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "github_topic_closest_fit": "matrix-multiplication" |
| }, |
| { |
| "repo_name": "hipBLASLt", |
| "repo_link": "https://github.com/AMD-AGI/hipBLASLt", |
| "category": "Basic Linear Algebra Subprograms (BLAS)", |
| "github_about_section": "hipBLASLt is a library that provides general matrix-matrix operations with a flexible API and extends functionalities beyond a traditional BLAS library", |
| "homepage_link": "https://rocm.docs.amd.com/projects/hipBLASLt", |
| "github_topic_closest_fit": "matrix-multiplication" |
| }, |
| { |
| "repo_name": "AdaptiveCpp", |
| "repo_link": "https://github.com/AdaptiveCpp/AdaptiveCpp", |
| "category": "compiler", |
| "github_about_section": "Compiler for multiple programming models (SYCL, C++ standard parallelism, HIP/CUDA) for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!", |
| "homepage_link": "https://adaptivecpp.github.io", |
| "github_topic_closest_fit": "compiler" |
| }, |
| { |
| "repo_name": "llvm-project", |
| "repo_link": "https://github.com/llvm/llvm-project", |
| "category": "compiler", |
| "github_about_section": "The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.", |
| "homepage_link": "http://llvm.org", |
| "github_topic_closest_fit": "compiler" |
| }, |
| { |
| "repo_name": "numba", |
| "repo_link": "https://github.com/numba/numba", |
| "category": "compiler", |
| "github_about_section": "NumPy aware dynamic Python compiler using LLVM", |
| "homepage_link": "https://numba.pydata.org", |
| "github_topic_closest_fit": "compiler" |
| }, |
| { |
| "repo_name": "nvcc4jupyter", |
| "repo_link": "https://github.com/andreinechaev/nvcc4jupyter", |
| "category": "compiler", |
| "github_about_section": "A plugin for Jupyter Notebook to run CUDA C/C++ code" |
| }, |
| { |
| "repo_name": "CU2CL", |
| "repo_link": "https://github.com/vtsynergy/CU2CL", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "A prototype CUDA-to-OpenCL source-to-source translator, built on the Clang compiler framework", |
| "homepage_link": "http://chrec.cs.vt.edu/cu2cl", |
| "github_topic_closest_fit": "opencl" |
| }, |
| { |
| "repo_name": "cuda-python", |
| "repo_link": "https://github.com/NVIDIA/cuda-python", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "CUDA Python: Performance meets Productivity", |
| "homepage_link": "https://nvidia.github.io/cuda-python" |
| }, |
| { |
| "repo_name": "OpenCL-SDK", |
| "repo_link": "https://github.com/KhronosGroup/OpenCL-SDK", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "OpenCL SDK", |
| "github_topic_closest_fit": "opencl" |
| }, |
| { |
| "repo_name": "pocl", |
| "repo_link": "https://github.com/pocl/pocl", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "pocl - Portable Computing Language", |
| "homepage_link": "https://portablecl.org", |
| "github_topic_closest_fit": "opencl" |
| }, |
| { |
| "repo_name": "SYCL-Docs", |
| "repo_link": "https://github.com/KhronosGroup/SYCL-Docs", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "SYCL Open Source Specification", |
| "github_topic_closest_fit": "opencl" |
| }, |
| { |
| "repo_name": "triSYCL", |
| "repo_link": "https://github.com/triSYCL/triSYCL", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group", |
| "github_topic_closest_fit": "opencl" |
| }, |
| { |
| "repo_name": "ZLUDA", |
| "repo_link": "https://github.com/vosen/ZLUDA", |
| "category": "CUDA / OpenCL", |
| "github_about_section": "CUDA on non-NVIDIA GPUs", |
| "homepage_link": "https://vosen.github.io/ZLUDA", |
| "github_topic_closest_fit": "cuda" |
| }, |
| { |
| "repo_name": "llama.cpp", |
| "repo_link": "https://github.com/ggml-org/llama.cpp", |
| "category": "inference engine", |
| "github_about_section": "LLM inference in C/C++", |
| "homepage_link": "https://ggml.ai", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "mistral-inference", |
| "repo_link": "https://github.com/mistralai/mistral-inference", |
| "category": "inference engine", |
| "github_about_section": "Official inference library for Mistral models", |
| "homepage_link": "https://mistral.ai", |
| "github_topic_closest_fit": "llm-inference" |
| }, |
| { |
| "repo_name": "ollama", |
| "repo_link": "https://github.com/ollama/ollama", |
| "category": "inference engine", |
| "github_about_section": "Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.", |
| "homepage_link": "https://ollama.com", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "sglang", |
| "repo_link": "https://github.com/sgl-project/sglang", |
| "category": "inference engine", |
| "github_about_section": "SGLang is a fast serving framework for large language models and vision language models.", |
| "homepage_link": "https://docs.sglang.ai", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "TensorRT", |
| "repo_link": "https://github.com/NVIDIA/TensorRT", |
| "category": "inference engine", |
| "github_about_section": "NVIDIA TensorRT is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.", |
| "homepage_link": "https://developer.nvidia.com/tensorrt", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "vllm", |
| "repo_link": "https://github.com/vllm-project/vllm", |
| "category": "inference engine", |
| "github_about_section": "A high-throughput and memory-efficient inference and serving engine for LLMs", |
| "homepage_link": "https://docs.vllm.ai", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "kernels", |
| "repo_link": "https://github.com/huggingface/kernels", |
| "category": "gpu kernels", |
| "github_about_section": "Load compute kernels from the Hub" |
| }, |
| { |
| "repo_name": "kernels-community", |
| "repo_link": "https://github.com/huggingface/kernels-community", |
| "category": "gpu kernels", |
| "homepage_link": "https://huggingface.co/kernels-community", |
| "github_about_section": "Kernel sources for https://huggingface.co/kernels-community" |
| }, |
| { |
| "repo_name": "Liger-Kernel", |
| "repo_link": "https://github.com/linkedin/Liger-Kernel", |
| "category": "kernel examples", |
| "github_about_section": "Efficient Triton Kernels for LLM Training", |
| "homepage_link": "https://openreview.net/pdf?id=36SjAIT42G", |
| "github_topic_closest_fit": "triton" |
| }, |
| { |
| "repo_name": "quack", |
| "repo_link": "https://github.com/Dao-AILab/quack", |
| "category": "kernel examples", |
| "github_about_section": "A Quirky Assortment of CuTe Kernels" |
| }, |
| { |
| "repo_name": "reference-kernels", |
| "repo_link": "https://github.com/gpu-mode/reference-kernels", |
| "category": "kernel examples", |
| "github_about_section": "Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!", |
| "homepage_link": "https://gpumode.com", |
| "github_topic_closest_fit": "gpu" |
| }, |
| { |
| "repo_name": "pytorch", |
| "repo_link": "https://github.com/pytorch/pytorch", |
| "category": "machine learning framework", |
| "github_about_section": "Tensors and Dynamic neural networks in Python with strong GPU acceleration", |
| "homepage_link": "https://pytorch.org", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "tensorflow", |
| "repo_link": "https://github.com/tensorflow/tensorflow", |
| "category": "machine learning framework", |
| "github_about_section": "An Open Source Machine Learning Framework for Everyone", |
| "homepage_link": "https://tensorflow.org", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "torchdendrite", |
| "repo_link": "https://github.com/sandialabs/torchdendrite", |
| "category": "machine learning framework", |
| "github_about_section": "Dendrites for PyTorch and SNNTorch neural networks" |
| }, |
| { |
| "repo_name": "onnx", |
| "repo_link": "https://github.com/onnx/onnx", |
| "category": "machine learning interoperability", |
| "github_about_section": "Open standard for machine learning interoperability", |
| "homepage_link": "https://onnx.ai", |
| "github_topic_closest_fit": "onnx" |
| }, |
| { |
| "repo_name": "executorch", |
| "repo_link": "https://github.com/pytorch/executorch", |
| "category": "model compiler", |
| "github_about_section": "On-device AI across mobile, embedded and edge for PyTorch", |
| "homepage_link": "https://executorch.ai", |
| "github_topic_closest_fit": "compiler" |
| }, |
| { |
| "repo_name": "cutlass", |
| "repo_link": "https://github.com/NVIDIA/cutlass", |
| "category": "parallel computing", |
| "github_about_section": "CUDA Templates and Python DSLs for High-Performance Linear Algebra", |
| "homepage_link": "https://docs.nvidia.com/cutlass/index.html", |
| "github_topic_closest_fit": "parallel-programming" |
| }, |
| { |
| "repo_name": "ThunderKittens", |
| "repo_link": "https://github.com/HazyResearch/ThunderKittens", |
| "category": "parallel computing", |
| "github_about_section": "Tile primitives for speedy kernels", |
| "homepage_link": "https://hazyresearch.stanford.edu/blog/2024-10-29-tk2", |
| "github_topic_closest_fit": "parallel-programming" |
| }, |
| { |
| "repo_name": "helion", |
| "repo_link": "https://github.com/pytorch/helion", |
| "category": "parallel computing dsl", |
| "github_about_section": "A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.", |
| "homepage_link": "https://helionlang.com", |
| "github_topic_closest_fit": "parallel-programming" |
| }, |
| { |
| "repo_name": "TileIR", |
| "repo_link": "https://github.com/microsoft/TileIR", |
| "category": "parallel computing dsl", |
| "github_about_section": "TileIR (tile-ir) is a concise domain-specific IR designed to streamline the development of high-performance GPU/CPU kernels (e.g., GEMM, Dequant GEMM, FlashAttention, LinearAttention). By employing a Pythonic syntax with an underlying compiler infrastructure on top of TVM, TileIR allows developers to focus on productivity without sacrificing the low-level optimizations necessary for state-of-the-art performance.", |
| "github_topic_closest_fit": "parallel-programming" |
| }, |
| { |
| "repo_name": "tilelang", |
| "repo_link": "https://github.com/tile-ai/tilelang", |
| "category": "parallel computing dsl", |
| "github_about_section": "Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels", |
| "homepage_link": "https://tilelang.com", |
| "github_topic_closest_fit": "parallel-programming" |
| }, |
| { |
| "repo_name": "triton", |
| "repo_link": "https://github.com/triton-lang/triton", |
| "category": "parallel computing dsl", |
| "github_about_section": "Development repository for the Triton language and compiler", |
| "homepage_link": "https://triton-lang.org", |
| "github_topic_closest_fit": "parallel-programming" |
| }, |
| { |
| "repo_name": "cupti", |
| "repo_link": "https://github.com/cwpearson/cupti", |
| "category": "performance testing", |
| "github_about_section": "Profile how CUDA applications create and modify data in memory.", |
| "github_topic_closest_fit": "profiling" |
| }, |
| { |
| "repo_name": "hatchet", |
| "repo_link": "https://github.com/LLNL/hatchet", |
| "category": "performance testing", |
| "github_about_section": "Graph-indexed Pandas DataFrames for analyzing hierarchical performance data", |
| "homepage_link": "https://llnl-hatchet.readthedocs.io", |
| "github_topic_closest_fit": "profiling" |
| }, |
| { |
| "repo_name": "intelliperf", |
| "repo_link": "https://github.com/AMDResearch/intelliperf", |
| "category": "performance testing", |
| "github_about_section": "Automated bottleneck detection and solution orchestration", |
| "homepage_link": "https://arxiv.org/html/2508.20258v1", |
| "github_topic_closest_fit": "profiling" |
| }, |
| { |
| "repo_name": "omnitrace", |
| "repo_link": "https://github.com/ROCm/omnitrace", |
| "category": "performance testing", |
| "github_about_section": "Omnitrace: Application Profiling, Tracing, and Analysis", |
| "homepage_link": "https://rocm.docs.amd.com/projects/omnitrace", |
| "github_topic_closest_fit": "profiling" |
| }, |
| { |
| "repo_name": "jax", |
| "repo_link": "https://github.com/jax-ml/jax", |
| "category": "scientific computing", |
| "github_about_section": "Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more", |
| "homepage_link": "https://docs.jax.dev", |
| "github_topic_closest_fit": "scientific-computing" |
| }, |
| { |
| "repo_name": "numpy", |
| "repo_link": "https://github.com/numpy/numpy", |
| "category": "scientific computing", |
| "github_about_section": "The fundamental package for scientific computing with Python.", |
| "homepage_link": "https://numpy.org", |
| "github_topic_closest_fit": "scientific-computing" |
| }, |
| { |
| "repo_name": "scipy", |
| "repo_link": "https://github.com/scipy/scipy", |
| "category": "scientific computing", |
| "github_about_section": "SciPy library main repository", |
| "homepage_link": "https://scipy.org", |
| "github_topic_closest_fit": "scientific-computing" |
| }, |
| { |
| "repo_name": "elasticsearch", |
| "repo_link": "https://github.com/elastic/elasticsearch", |
| "category": "search engine", |
| "github_about_section": "Free and Open Source, Distributed, RESTful Search Engine", |
| "homepage_link": "https://elastic.co/products/elasticsearch", |
| "github_topic_closest_fit": "search-engine" |
| }, |
| { |
| "repo_name": "jupyterlab", |
| "repo_link": "https://github.com/jupyterlab/jupyterlab", |
| "category": "user interface", |
| "github_about_section": "JupyterLab computational environment.", |
| "homepage_link": "https://jupyterlab.readthedocs.io", |
| "github_topic_closest_fit": "jupyter" |
| }, |
| { |
| "repo_name": "milvus", |
| "repo_link": "https://github.com/milvus-io/milvus", |
| "category": "vector database", |
| "github_about_section": "Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search", |
| "homepage_link": "https://milvus.io", |
| "github_topic_closest_fit": "vector-search" |
| }, |
| { |
| "repo_name": "accelerate", |
| "repo_link": "https://github.com/huggingface/accelerate", |
| "category": "training framework", |
| "github_about_section": "A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support.", |
| "homepage_link": "https://huggingface.co/docs/accelerate", |
| "github_topic_closest_fit": "gpu-acceleration" |
| }, |
| { |
| "repo_name": "aiter", |
| "repo_link": "https://github.com/ROCm/aiter", |
| "category": "ai tensor engine", |
| "github_about_section": "AI Tensor Engine for ROCm", |
| "homepage_link": "https://rocm.blogs.amd.com/software-tools-optimization/aiter-ai-tensor-engine/README.html", |
| "github_topic_closest_fit": "gpu-acceleration" |
| }, |
| { |
| "repo_name": "ao", |
| "repo_link": "https://github.com/pytorch/ao", |
| "github_about_section": "PyTorch native quantization and sparsity for training and inference", |
| "homepage_link": "https://pytorch.org/ao", |
| "github_topic_closest_fit": "quantization" |
| }, |
| { |
| "repo_name": "burn", |
| "repo_link": "https://github.com/tracel-ai/burn", |
| "github_about_section": "Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.", |
| "homepage_link": "https://burn.dev", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "ccache", |
| "repo_link": "https://github.com/ccache/ccache", |
| "github_about_section": "ccache - a fast compiler cache", |
| "homepage_link": "https://ccache.dev" |
| }, |
| { |
| "repo_name": "ComfyUI", |
| "repo_link": "https://github.com/comfyanonymous/ComfyUI", |
| "category": "user interface", |
| "github_about_section": "The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.", |
| "homepage_link": "https://comfy.org", |
| "github_topic_closest_fit": "stable-diffusion" |
| }, |
| { |
| "repo_name": "composable_kernel", |
| "repo_link": "https://github.com/ROCm/composable_kernel", |
| "category": "gpu kernels", |
| "github_about_section": "Composable Kernel: Performance Portable Programming Model for Machine Learning Tensor Operators", |
| "homepage_link": "https://rocm.docs.amd.com/projects/composable_kernel" |
| }, |
| { |
| "repo_name": "cudnn-frontend", |
| "repo_link": "https://github.com/NVIDIA/cudnn-frontend", |
| "github_about_section": "cudnn_frontend provides a c++ wrapper for the cudnn backend API and samples on how to use it" |
| }, |
| { |
| "repo_name": "cuJSON", |
| "repo_link": "https://github.com/AutomataLab/cuJSON", |
| "category": "library leveraging parallel compute", |
| "github_about_section": "cuJSON: A Highly Parallel JSON Parser for GPUs", |
| "github_topic_closest_fit": "json-parser" |
| }, |
| { |
| "repo_name": "DeepSpeed", |
| "repo_link": "https://github.com/deepspeedai/DeepSpeed", |
| "category": "training framework", |
| "github_about_section": "DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.", |
| "homepage_link": "https://deepspeed.ai", |
| "github_topic_closest_fit": "gpu-acceleration" |
| }, |
| { |
| "repo_name": "dstack", |
| "repo_link": "https://github.com/dstackai/dstack", |
| "category": "gpu provisioning and orchestration", |
| "github_about_section": "dstack is an open-source control plane for running development, training, and inference jobs on GPUs-across hyperscalers, neoclouds, or on-prem.", |
| "homepage_link": "https://dstack.ai", |
| "github_topic_closest_fit": "orchestration" |
| }, |
| { |
| "repo_name": "flashinfer", |
| "repo_link": "https://github.com/flashinfer-ai/flashinfer", |
| "category": "gpu kernels", |
| "github_about_section": "FlashInfer: Kernel Library for LLM Serving", |
| "homepage_link": "https://flashinfer.ai", |
| "github_topic_closest_fit": "attention" |
| }, |
| { |
| "repo_name": "FTorch", |
| "repo_link": "https://github.com/Cambridge-ICCS/FTorch", |
| "github_about_section": "A library for directly calling PyTorch ML models from Fortran.", |
| "homepage_link": "https://cambridge-iccs.github.io/FTorch", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "GEAK-agent", |
| "repo_link": "https://github.com/AMD-AGI/GEAK-agent", |
| "github_about_section": "It is an LLM-based AI agent, which can write correct and efficient gpu kernels automatically." |
| }, |
| { |
| "repo_name": "hhvm", |
| "repo_link": "https://github.com/facebook/hhvm", |
| "github_about_section": "A virtual machine for executing programs written in Hack.", |
| "homepage_link": "https://hhvm.com", |
| "github_topic_closest_fit": "hack" |
| }, |
| { |
| "repo_name": "hip", |
| "repo_link": "https://github.com/ROCm/hip", |
| "github_about_section": "HIP: C++ Heterogeneous-Compute Interface for Portability", |
| "homepage_link": "https://rocmdocs.amd.com/projects/HIP", |
| "github_topic_closest_fit": "hip" |
| }, |
| { |
| "repo_name": "hipCUB", |
| "repo_link": "https://github.com/ROCm/hipCUB", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries" |
| }, |
| { |
| "repo_name": "IMO2025", |
| "repo_link": "https://github.com/harmonic-ai/IMO2025", |
| "category": "formal mathematical reasoning", |
| "github_about_section": "Harmonic's model Aristotle achieved gold medal performance, solving 5 problems. This repository contains the lean statement files and proofs for Problems 1-5.", |
| "homepage_link": "https://harmonic.fun", |
| "github_topic_closest_fit": "lean" |
| }, |
| { |
| "repo_name": "kubernetes", |
| "repo_link": "https://github.com/kubernetes/kubernetes", |
| "category": "container orchestration", |
| "github_about_section": "Production-Grade Container Scheduling and Management", |
| "homepage_link": "https://kubernetes.io", |
| "github_topic_closest_fit": "kubernetes" |
| }, |
| { |
| "repo_name": "lapack", |
| "repo_link": "https://github.com/Reference-LAPACK/lapack", |
| "github_about_section": "LAPACK development repository", |
| "github_topic_closest_fit": "linear-algebra" |
| }, |
| { |
| "repo_name": "lean4", |
| "repo_link": "https://github.com/leanprover/lean4", |
| "category": "theorem prover", |
| "github_about_section": "Lean 4 programming language and theorem prover", |
| "homepage_link": "https://lean-lang.org", |
| "github_topic_closest_fit": "lean" |
| }, |
| { |
| "repo_name": "letta", |
| "repo_link": "https://github.com/letta-ai/letta", |
| "github_about_section": "Letta is the platform for building stateful agents: open AI with advanced memory that can learn and self-improve over time.", |
| "homepage_link": "https://docs.letta.com", |
| "github_topic_closest_fit": "ai-agents" |
| }, |
| { |
| "repo_name": "lightning-thunder", |
| "repo_link": "https://github.com/Lightning-AI/lightning-thunder", |
| "github_about_section": "PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own." |
| }, |
| { |
| "repo_name": "LMCache", |
| "repo_link": "https://github.com/LMCache/LMCache", |
| "github_about_section": "Supercharge Your LLM with the Fastest KV Cache Layer", |
| "homepage_link": "https://lmcache.ai", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "mcp-agent", |
| "repo_link": "https://github.com/lastmile-ai/mcp-agent", |
| "github_about_section": "Build effective agents using Model Context Protocol and simple workflow patterns", |
| "github_topic_closest_fit": "ai-agents" |
| }, |
| { |
| "repo_name": "metaflow", |
| "repo_link": "https://github.com/Netflix/metaflow", |
| "github_about_section": "Build, Manage and Deploy AI/ML Systems", |
| "homepage_link": "https://metaflow.org", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "MIOpen", |
| "repo_link": "https://github.com/ROCm/MIOpen", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries" |
| }, |
| { |
| "repo_name": "modelcontextprotocol", |
| "repo_link": "https://github.com/modelcontextprotocol/modelcontextprotocol", |
| "github_about_section": "Specification and documentation for the Model Context Protocol", |
| "homepage_link": "https://modelcontextprotocol.io" |
| }, |
| { |
| "repo_name": "modular", |
| "repo_link": "https://github.com/modular/modular", |
| "github_about_section": "The Modular Platform (includes MAX & Mojo)", |
| "homepage_link": "https://docs.modular.com", |
| "github_topic_closest_fit": "mojo" |
| }, |
| { |
| "repo_name": "monarch", |
| "repo_link": "https://github.com/meta-pytorch/monarch", |
| "github_about_section": "PyTorch Single Controller", |
| "homepage_link": "https://meta-pytorch.org/monarch" |
| }, |
| { |
| "repo_name": "Mooncake", |
| "repo_link": "https://github.com/kvcache-ai/Mooncake", |
| "github_about_section": "Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.", |
| "homepage_link": "https://kvcache-ai.github.io/Mooncake", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "nccl", |
| "repo_link": "https://github.com/NVIDIA/nccl", |
| "github_about_section": "Optimized primitives for collective multi-GPU communication", |
| "homepage_link": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/index.html" |
| }, |
| { |
| "repo_name": "neuronx-distributed-inference", |
| "repo_link": "https://github.com/aws-neuron/neuronx-distributed-inference" |
| }, |
| { |
| "repo_name": "nixl", |
| "repo_link": "https://github.com/ai-dynamo/nixl", |
| "github_about_section": "NVIDIA Inference Xfer Library (NIXL)" |
| }, |
| { |
| "repo_name": "ome", |
| "repo_link": "https://github.com/sgl-project/ome", |
| "github_about_section": "OME is a Kubernetes operator for enterprise-grade management and serving of Large Language Models (LLMs)", |
| "homepage_link": "http://docs.sglang.ai/ome", |
| "github_topic_closest_fit": "k8s" |
| }, |
| { |
| "repo_name": "ondemand", |
| "repo_link": "https://github.com/OSC/ondemand", |
| "github_about_section": "Supercomputing. Seamlessly. Open, Interactive HPC Via the Web", |
| "homepage_link": "https://openondemand.org", |
| "github_topic_closest_fit": "hpc" |
| }, |
| { |
| "repo_name": "oneDPL", |
| "repo_link": "https://github.com/uxlfoundation/oneDPL", |
| "github_about_section": "oneAPI DPC++ Library (oneDPL)", |
| "homepage_link": "https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/dpc-library.html" |
| }, |
| { |
| "repo_name": "openevolve", |
| "repo_link": "https://github.com/codelion/openevolve", |
| "github_about_section": "Open-source implementation of AlphaEvolve", |
| "github_topic_closest_fit": "genetic-algorithm" |
| }, |
| { |
| "repo_name": "ort", |
| "repo_link": "https://github.com/pytorch/ort", |
| "github_about_section": "Accelerate PyTorch models with ONNX Runtime" |
| }, |
| { |
| "repo_name": "peft", |
| "repo_link": "https://github.com/huggingface/peft", |
| "github_about_section": "PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.", |
| "homepage_link": "https://huggingface.co/docs/peft", |
| "github_topic_closest_fit": "lora" |
| }, |
| { |
| "repo_name": "Primus-Turbo", |
| "repo_link": "https://github.com/AMD-AGI/Primus-Turbo" |
| }, |
| { |
| "repo_name": "pybind11", |
| "repo_link": "https://github.com/pybind/pybind11", |
| "github_about_section": "Seamless operability between C++11 and Python", |
| "homepage_link": "https://pybind11.readthedocs.io", |
| "github_topic_closest_fit": "bindings" |
| }, |
| { |
| "repo_name": "RaBitQ", |
| "repo_link": "https://github.com/gaoj0017/RaBitQ", |
| "github_about_section": "[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search", |
| "homepage_link": "https://github.com/VectorDB-NTU/RaBitQ-Library", |
| "github_topic_closest_fit": "nearest-neighbor-search" |
| }, |
| { |
| "repo_name": "rdma-core", |
| "repo_link": "https://github.com/linux-rdma/rdma-core", |
| "github_about_section": "RDMA core userspace libraries and daemons", |
| "github_topic_closest_fit": "linux-kernel" |
| }, |
| { |
| "repo_name": "rocFFT", |
| "repo_link": "https://github.com/ROCm/rocFFT", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries", |
| "github_topic_closest_fit": "hip" |
| }, |
| { |
| "repo_name": "ROCm", |
| "repo_link": "https://github.com/ROCm/ROCm", |
| "github_about_section": "AMD ROCm Software - GitHub Home", |
| "homepage_link": "https://rocm.docs.amd.com", |
| "github_topic_closest_fit": "documentation" |
| }, |
| { |
| "repo_name": "rocm-systems", |
| "repo_link": "https://github.com/ROCm/rocm-systems", |
| "github_about_section": "super repo for rocm systems projects" |
| }, |
| { |
| "repo_name": "rocPRIM", |
| "repo_link": "https://github.com/ROCm/rocPRIM", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries", |
| "github_topic_closest_fit": "hip" |
| }, |
| { |
| "repo_name": "rocRAND", |
| "repo_link": "https://github.com/ROCm/rocRAND", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries", |
| "github_topic_closest_fit": "hip" |
| }, |
| { |
| "repo_name": "rocSOLVER", |
| "repo_link": "https://github.com/ROCm/rocSOLVER", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries", |
| "github_topic_closest_fit": "rocm" |
| }, |
| { |
| "repo_name": "rocSPARSE", |
| "repo_link": "https://github.com/ROCm/rocSPARSE", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries" |
| }, |
| { |
| "repo_name": "roctracer", |
| "repo_link": "https://github.com/ROCm/roctracer", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-systems repo", |
| "homepage_link": "https://github.com/ROCm/rocm-systems" |
| }, |
| { |
| "repo_name": "Self-Forcing", |
| "repo_link": "https://github.com/guandeh17/Self-Forcing", |
| "category": "video generation", |
| "github_about_section": "Official codebase for \"Self Forcing: Bridging Training and Inference in Autoregressive Video Diffusion\" (NeurIPS 2025 Spotlight)", |
| "homepage_link": "https://self-forcing.github.io", |
| "github_topic_closest_fit": "diffusion-models" |
| }, |
| { |
| "repo_name": "server", |
| "repo_link": "https://github.com/triton-inference-server/server", |
| "github_about_section": "The Triton Inference Server provides an optimized cloud and edge inferencing solution.", |
| "homepage_link": "https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/index.html", |
| "github_topic_closest_fit": "inference" |
| }, |
| { |
| "repo_name": "spark", |
| "repo_link": "https://github.com/apache/spark", |
| "github_about_section": "Apache Spark - A unified analytics engine for large-scale data processing", |
| "homepage_link": "https://spark.apache.org", |
| "github_topic_closest_fit": "big-data" |
| }, |
| { |
| "repo_name": "StreamDiffusion", |
| "repo_link": "https://github.com/cumulo-autumn/StreamDiffusion", |
| "category": "image generation", |
| "github_about_section": "StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation", |
| "homepage_link": "https://arxiv.org/abs/2312.12491", |
| "github_topic_closest_fit": "diffusion-models" |
| }, |
| { |
| "repo_name": "streamv2v", |
| "repo_link": "https://github.com/Jeff-LiangF/streamv2v", |
| "category": "video generation", |
| "github_about_section": "Official Pytorch implementation of StreamV2V.", |
| "homepage_link": "https://jeff-liangf.github.io/projects/streamv2v", |
| "github_topic_closest_fit": "diffusion-models" |
| }, |
| { |
| "repo_name": "synthetic-data-kit", |
| "repo_link": "https://github.com/meta-llama/synthetic-data-kit", |
| "category": "synthetic data generation", |
| "github_about_section": "Tool for generating high quality Synthetic datasets", |
| "homepage_link": "https://pypi.org/project/synthetic-data-kit", |
| "github_topic_closest_fit": "synthetic-dataset-generation" |
| }, |
| { |
| "repo_name": "Tensile", |
| "repo_link": "https://github.com/ROCm/Tensile", |
| "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo", |
| "homepage_link": "https://github.com/ROCm/rocm-libraries", |
| "github_topic_closest_fit": "gpu" |
| }, |
| { |
| "repo_name": "tflite-micro", |
| "repo_link": "https://github.com/tensorflow/tflite-micro", |
| "github_about_section": "Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors)." |
| }, |
| { |
| "repo_name": "torchdynamo", |
| "repo_link": "https://github.com/pytorch/torchdynamo", |
| "github_about_section": "A Python-level JIT compiler designed to make unmodified PyTorch programs faster." |
| }, |
| { |
| "repo_name": "torchtitan", |
| "repo_link": "https://github.com/pytorch/torchtitan", |
| "github_about_section": "A PyTorch native platform for training generative AI models" |
| }, |
| { |
| "repo_name": "torchtitan", |
| "repo_link": "https://github.com/AMD-AGI/torchtitan", |
| "github_about_section": "A PyTorch native platform for training generative AI models" |
| }, |
| { |
| "repo_name": "transformers", |
| "repo_link": "https://github.com/huggingface/transformers", |
| "github_about_section": "Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.", |
| "homepage_link": "https://huggingface.co/transformers" |
| }, |
| { |
| "repo_name": "Triton-distributed", |
| "repo_link": "https://github.com/ByteDance-Seed/Triton-distributed", |
| "github_about_section": "Distributed Compiler based on Triton for Parallel Systems", |
| "homepage_link": "https://triton-distributed.readthedocs.io" |
| }, |
| { |
| "repo_name": "triton-runner", |
| "repo_link": "https://github.com/toyaix/triton-runner", |
| "github_about_section": "Multi-Level Triton Runner supporting Python, IR, PTX, and cubin.", |
| "homepage_link": "https://triton-runner.org", |
| "github_topic_closest_fit": "triton" |
| }, |
| { |
| "repo_name": "tritonparse", |
| "repo_link": "https://github.com/meta-pytorch/tritonparse", |
| "github_about_section": "TritonParse: A Compiler Tracer, Visualizer, and Reproducer for Triton Kernels", |
| "homepage_link": "https://meta-pytorch.org/tritonparse", |
| "github_topic_closest_fit": "triton" |
| }, |
| { |
| "repo_name": "trl", |
| "repo_link": "https://github.com/huggingface/trl", |
| "github_about_section": "Train transformer language models with reinforcement learning.", |
| "homepage_link": "http://hf.co/docs/trl" |
| }, |
| { |
| "repo_name": "truss", |
| "repo_link": "https://github.com/basetenlabs/truss", |
| "github_about_section": "The simplest way to serve AI/ML models in production", |
| "homepage_link": "https://truss.baseten.co", |
| "github_topic_closest_fit": "machine-learning" |
| }, |
| { |
| "repo_name": "unsloth", |
| "repo_link": "https://github.com/unslothai/unsloth", |
| "github_about_section": "Fine-tuning & Reinforcement Learning for LLMs. Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.", |
| "homepage_link": "https://docs.unsloth.ai" |
| }, |
| { |
| "repo_name": "verl", |
| "repo_link": "https://github.com/volcengine/verl", |
| "github_about_section": "verl: Volcano Engine Reinforcement Learning for LLMs", |
| "homepage_link": "https://verl.readthedocs.io" |
| }, |
| { |
| "repo_name": "Vulkan-Hpp", |
| "repo_link": "https://github.com/KhronosGroup/Vulkan-Hpp", |
| "category": "graphics api", |
| "github_about_section": "Open-Source Vulkan C++ API", |
| "homepage_link": "https://vulkan.org", |
| "github_topic_closest_fit": "vulkan" |
| }, |
| { |
| "repo_name": "Vulkan-Tools", |
| "repo_link": "https://github.com/KhronosGroup/Vulkan-Tools", |
| "category": "graphics api", |
| "github_about_section": "Vulkan Development Tools", |
| "homepage_link": "https://vulkan.org", |
| "github_topic_closest_fit": "vulkan" |
| }, |
| { |
| "repo_name": "Vulkan-Docs", |
| "repo_link": "https://github.com/KhronosGroup/Vulkan-Docs", |
| "category": "graphics api", |
| "github_about_section": "The Vulkan API Specification and related tools", |
| "homepage_link": "https://vulkan.org", |
| "github_topic_closest_fit": "vulkan" |
| }, |
| { |
| "repo_name": "Wan2.2", |
| "repo_link": "https://github.com/Wan-Video/Wan2.2", |
| "category": "video generation", |
| "github_about_section": "Wan: Open and Advanced Large-Scale Video Generative Models", |
| "homepage_link": "https://wan.video", |
| "github_topic_closest_fit": "diffusion-models" |
| }, |
| { |
| "repo_name": "warp", |
| "repo_link": "https://github.com/NVIDIA/warp", |
| "github_about_section": "A Python framework for accelerated simulation, data generation and spatial computing.", |
| "homepage_link": "https://nvidia.github.io/warp/", |
| "github_topic_closest_fit": "gpu" |
| } |
| ] |
