Commit
·
8dcde9e
1
Parent(s):
0bc5c22
Sorted by unique contributors in 2025
Browse files- PyTorchConference2025_GithubRepos.json +1038 -1038
PyTorchConference2025_GithubRepos.json
CHANGED
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[
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{
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"repo_name": "goose",
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"repo_link": "https://github.com/block/goose",
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"category": "agent",
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"github_about_section": "an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM",
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"homepage_link": "https://block.github.io/goose",
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"repo_name": "ray",
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"repo_link": "https://github.com/ray-project/ray",
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"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.",
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"homepage_link": "https://ray.io",
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},
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{
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"repo_name": "flashinfer-bench",
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"repo_link": "https://github.com/flashinfer-ai/flashinfer-bench",
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"category": "benchmark",
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"github_about_section": "Building the Virtuous Cycle for AI-driven LLM Systems",
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"homepage_link": "https://bench.flashinfer.ai",
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"github_topic_closest_fit": "benchmark",
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{
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"repo_name": "KernelBench",
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"repo_link": "https://github.com/ScalingIntelligence/KernelBench",
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"category": "benchmark",
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"github_about_section": "KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems",
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"homepage_link": "https://scalingintelligence.stanford.edu/blogs/kernelbench",
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"github_topic_closest_fit": "benchmark",
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{
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"repo_name": "SWE-bench",
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"repo_link": "https://github.com/SWE-bench/SWE-bench",
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"category": "benchmark",
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"github_about_section": "SWE-bench: Can Language Models Resolve Real-world Github Issues?",
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"homepage_link": "https://swebench.com",
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"github_topic_closest_fit": "benchmark",
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},
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{
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"repo_name": "terminal-bench",
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"repo_link": "https://github.com/laude-institute/terminal-bench",
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"category": "benchmark",
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"github_about_section": "A benchmark for LLMs on complicated tasks in the terminal",
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"homepage_link": "https://tbench.ai",
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},
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{
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"repo_name": "TritonBench",
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"repo_link": "https://github.com/thunlp/TritonBench",
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"category": "benchmark",
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"github_about_section": "TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators",
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"homepage_link": "https://arxiv.org/abs/2502.14752",
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"repo_name": "BitBLAS",
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"repo_link": "https://github.com/microsoft/BitBLAS",
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"category": "Basic Linear Algebra Subprograms (BLAS)",
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"github_about_section": "BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.",
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"github_topic_closest_fit": "matrix-multiplication",
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{
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"repo_name": "hipBLAS",
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"repo_link": "https://github.com/ROCm/hipBLAS",
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"category": "Basic Linear Algebra Subprograms (BLAS)",
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"github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
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"github_topic_closest_fit": "matrix-multiplication",
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"contributors_all": 72,
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},
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{
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"repo_name": "hipBLASLt",
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"repo_link": "https://github.com/AMD-AGI/hipBLASLt",
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"category": "Basic Linear Algebra Subprograms (BLAS)",
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"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",
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"homepage_link": "https://rocm.docs.amd.com/projects/hipBLASLt",
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"github_topic_closest_fit": "matrix-multiplication",
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"contributors_all": 111,
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"contributors_2025": 69,
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"contributors_2024": 70,
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},
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{
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"repo_name": "AdaptiveCpp",
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"repo_link": "https://github.com/AdaptiveCpp/AdaptiveCpp",
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"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!",
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"homepage_link": "https://adaptivecpp.github.io",
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"contributors_2023": 24
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},
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{
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"repo_name": "llvm-project",
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"repo_link": "https://github.com/llvm/llvm-project",
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"homepage_link": "http://llvm.org",
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"github_topic_closest_fit": "compiler",
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{
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"repo_name": "numba",
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"repo_link": "https://github.com/numba/numba",
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"github_about_section": "NumPy aware dynamic Python compiler using LLVM",
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"homepage_link": "https://numba.pydata.org",
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"contributors_2024": 32,
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},
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{
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"repo_name": "nvcc4jupyter",
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"repo_link": "https://github.com/andreinechaev/nvcc4jupyter",
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"github_about_section": "A plugin for Jupyter Notebook to run CUDA C/C++ code",
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"homepage_link": "https://nvcc4jupyter.readthedocs.io",
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"contributors_all": 9,
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},
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{
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"repo_name": "CU2CL",
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"repo_link": "https://github.com/vtsynergy/CU2CL",
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"github_about_section": "A prototype CUDA-to-OpenCL source-to-source translator, built on the Clang compiler framework",
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"homepage_link": "http://chrec.cs.vt.edu/cu2cl",
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"github_topic_closest_fit": "parallel-programming",
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{
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"repo_name": "cuda-python",
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"repo_link": "https://github.com/NVIDIA/cuda-python",
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"github_about_section": "CUDA Python: Performance meets Productivity",
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"homepage_link": "https://nvidia.github.io/cuda-python",
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"github_topic_closest_fit": "parallel-programming",
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},
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{
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"repo_name": "OpenCL-SDK",
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"repo_link": "https://github.com/KhronosGroup/OpenCL-SDK",
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"github_about_section": "OpenCL SDK",
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"homepage_link": "https://khronos.org/opencl",
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"github_topic_closest_fit": "parallel-programming",
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},
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{
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"repo_name": "pocl",
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"repo_link": "https://github.com/pocl/pocl",
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"github_about_section": "pocl - Portable Computing Language",
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"homepage_link": "https://portablecl.org",
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"github_topic_closest_fit": "parallel-programming",
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},
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{
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"repo_name": "SYCL-Docs",
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"repo_link": "https://github.com/KhronosGroup/SYCL-Docs",
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"github_about_section": "SYCL Open Source Specification",
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"homepage_link": "https://khronos.org/sycl",
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},
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{
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"repo_name": "triSYCL",
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"repo_link": "https://github.com/triSYCL/triSYCL",
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"github_about_section": "Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group",
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"homepage_link": "https://trisycl.github.io/triSYCL/Doxygen/triSYCL/html/index.html",
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{
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"repo_name": "ZLUDA",
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"repo_link": "https://github.com/vosen/ZLUDA",
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"github_about_section": "CUDA on non-NVIDIA GPUs",
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"homepage_link": "https://vosen.github.io/ZLUDA",
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{
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"repo_name": "llama.cpp",
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"repo_link": "https://github.com/ggml-org/llama.cpp",
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"category": "inference engine",
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"github_about_section": "LLM inference in C/C++",
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"homepage_link": "https://ggml.ai",
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"github_topic_closest_fit": "inference",
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},
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{
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"repo_name": "mistral-inference",
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"repo_link": "https://github.com/mistralai/mistral-inference",
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"category": "inference engine",
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"github_about_section": "Official inference library for Mistral models",
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"homepage_link": "https://mistral.ai",
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"github_topic_closest_fit": "inference",
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"contributors_all": 29,
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},
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{
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"repo_name": "ollama",
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"repo_link": "https://github.com/ollama/ollama",
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"category": "inference engine",
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"github_about_section": "Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.",
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"homepage_link": "https://ollama.com",
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"github_topic_closest_fit": "inference",
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"contributors_all": 574,
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"contributors_2023": 97
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},
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"repo_name": "sglang",
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"repo_link": "https://github.com/sgl-project/sglang",
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"category": "inference engine",
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"github_about_section": "SGLang is a fast serving framework for large language models and vision language models.",
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"homepage_link": "https://docs.sglang.ai",
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"github_topic_closest_fit": "inference",
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"contributors_all": 937,
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"contributors_2025": 796,
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"contributors_2023": 1
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},
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"repo_name": "TensorRT",
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"repo_link": "https://github.com/NVIDIA/TensorRT",
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"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.",
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"homepage_link": "https://developer.nvidia.com/tensorrt",
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"contributors_all": 104,
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},
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{
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"repo_name": "vllm",
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"contributors_2024": 579,
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"contributors_2023": 145
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},
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"repo_name": "kernels",
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"repo_link": "https://github.com/huggingface/kernels",
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"category": "gpu kernels",
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"github_about_section": "Load compute kernels from the Hub",
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"contributors_all": 15,
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},
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{
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"repo_name": "kernels-community",
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"repo_link": "https://github.com/huggingface/kernels-community",
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"category": "gpu kernels",
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"homepage_link": "https://huggingface.co/kernels-community",
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"github_about_section": "Kernel sources for https://huggingface.co/kernels-community",
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"repo_name": "Liger-Kernel",
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"repo_link": "https://github.com/linkedin/Liger-Kernel",
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"category": "kernel examples",
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"github_about_section": "Efficient Triton Kernels for LLM Training",
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"homepage_link": "https://openreview.net/pdf?id=36SjAIT42G",
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"github_topic_closest_fit": "triton",
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{
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"repo_name": "quack",
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"repo_link": "https://github.com/Dao-AILab/quack",
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"category": "kernel examples",
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|
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"github_about_section": "
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|
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"contributors_2023": 0
|
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|
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{
|
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|
| 988 |
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"repo_link": "https://github.com/OSC/ondemand",
|
| 989 |
-
"github_about_section": "Supercomputing. Seamlessly. Open, Interactive HPC Via the Web",
|
| 990 |
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"homepage_link": "https://openondemand.org",
|
| 991 |
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"github_topic_closest_fit": "hpc",
|
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"contributors_all": 117,
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|
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},
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{
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"repo_name": "oneDPL",
|
| 999 |
"repo_link": "https://github.com/uxlfoundation/oneDPL",
|
|
@@ -1005,102 +918,110 @@
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| 1005 |
"contributors_2023": 28
|
| 1006 |
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|
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{
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|
| 1016 |
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{
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{
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"contributors_2024": 0,
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|
| 1044 |
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{
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"repo_name": "
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|
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{
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|
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|
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{
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"repo_name": "
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{
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"repo_link": "https://github.com/
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"homepage_link": "https://
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"contributors_2024": 20,
|
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{
|
| 1087 |
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"repo_name": "ROCm",
|
| 1088 |
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"repo_link": "https://github.com/ROCm/ROCm",
|
| 1089 |
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"github_about_section": "AMD ROCm Software - GitHub Home",
|
| 1090 |
-
"homepage_link": "https://rocm.docs.amd.com",
|
| 1091 |
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"contributors_all": 166,
|
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"contributors_2025": 67,
|
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"contributors_2024": 61,
|
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"contributors_2023": 44
|
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{
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|
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{
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"repo_name": "rocPRIM",
|
|
@@ -1112,6 +1033,61 @@
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"contributors_2024": 28,
|
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"repo_link": "https://github.com/ROCm/rocRAND",
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{
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"repo_name": "Self-Forcing",
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"repo_link": "https://github.com/guandeh17/Self-Forcing",
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@@ -1165,38 +1218,28 @@
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"homepage_link": "https://spark.apache.org",
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"repo_name": "streamv2v",
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@@ -1207,76 +1250,76 @@
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"github_topic_closest_fit": "diffusion-models",
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{
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| 1328 |
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| 1329 |
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|
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{
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| 1399 |
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| 1400 |
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| 1401 |
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| 1402 |
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| 1403 |
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| 1404 |
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| 1407 |
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