repo_name stringlengths 3 23 | repo_link stringlengths 27 60 | category stringlengths 3 39 ⌀ | github_about_section stringlengths 22 415 | homepage_link stringlengths 14 89 ⌀ |
|---|---|---|---|---|
NVSHMEM | https://github.com/NVIDIA/nvshmem | distributed computing | GPU-initiated communication for scalable NVIDIA GPU clusters. | https://developer.nvidia.com/nvshmem |
flashinfer-bench | https://github.com/flashinfer-ai/flashinfer-bench | benchmark | Building the Virtuous Cycle for AI-driven LLM Systems | https://bench.flashinfer.ai |
Primus-Turbo | https://github.com/AMD-AGI/Primus-Turbo | training framework | Primus-Turbo is a high-performance acceleration library dedicated to large-scale model training on AMD GPUs. Built and optimized for the AMD ROCm platform, it covers the full training stack — including core compute operators (GEMM, Attention, GroupedGEMM), communication primitives, optimizer modules, low-precision comp... | null |
BitBLAS | https://github.com/microsoft/BitBLAS | Basic Linear Algebra Subprograms (BLAS) | BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment. | null |
kernels-community | https://github.com/huggingface/kernels-community | gpu kernels | Kernel sources for https://huggingface.co/kernels-community | https://huggingface.co/kernels-community |
omnitrace | https://github.com/ROCm/omnitrace | performance testing | Omnitrace: Application Profiling, Tracing, and Analysis | https://rocm.docs.amd.com/projects/omnitrace |
PipelineRL | https://github.com/ServiceNow/PipelineRL | reinforcement learning | A scalable asynchronous reinforcement learning implementation with in-flight weight updates. | https://arxiv.org/abs/2509.19128 |
kraken | https://github.com/meta-pytorch/kraken | kernel examples | Triton-based Symmetric Memory operators and examples | null |
TileIR | https://github.com/microsoft/TileIR | parallel computing dsl | 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 productiv... | null |
intelliperf | https://github.com/AMDResearch/intelliperf | performance testing | Automated bottleneck detection and solution orchestration | https://arxiv.org/html/2508.20258v1 |
tilus | https://github.com/NVIDIA/tilus | parallel computing | Tilus is a tile-level kernel programming language with explicit control over shared memory and registers. | https://nvidia.github.io/tilus |
gemlite | https://github.com/dropbox/gemlite | gpu kernels | Fast low-bit matmul kernels in Triton | null |
TritonBench | https://github.com/thunlp/TritonBench | benchmark | TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators | https://arxiv.org/abs/2502.14752 |
triton-runner | https://github.com/toyaix/triton-runner | debugger | Multi-Level Triton Runner supporting Python, IR, PTX, and cubin. | https://triton-runner.org |
Megatron-LM | https://github.com/NVIDIA/Megatron-LM | null | Ongoing research training transformer models at scale | https://docs.nvidia.com/megatron-core/developer-guide/latest/index.html |
fairscale | https://github.com/facebookresearch/fairscale | null | PyTorch extensions for high performance and large scale training. | null |
ColossalAI | https://github.com/hpcaitech/ColossalAI | null | Making large AI models cheaper, faster and more accessible | https://colossalai.org/ |
NeMo RL | https://github.com/nvidia-nemo/rl | null | Scalable toolkit for efficient model reinforcement | https://docs.nvidia.com/nemo/rl/latest/index.html |
slime | https://github.com/THUDM/slime | null | slime is an LLM post-training framework for RL Scaling. | https://thudm.github.io/slime/ |
RAGEN | https://github.com/mll-lab-nu/RAGEN | null | RAGEN leverages reinforcement learning to train LLM reasoning agents in interactive, stochastic environments. | https://ragen-ai.github.io/ |
slurm | https://github.com/SchedMD/slurm | null | Slurm: A Highly Scalable Workload Manager | https://slurm.schedmd.com/ |
Open Thoughts | https://github.com/open-thoughts/open-thoughts | null | Fully open data curation for reasoning models | https://www.open-thoughts.ai/ |
Optimum | https://github.com/huggingface/optimum | null | Accelerate inference and training of Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools | https://huggingface.co/docs/optimum/main/en/index |
ultralytics | https://github.com/ultralytics/ultralytics | null | Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking | https://platform.ultralytics.com |
NVIDIA FLARE | https://github.com/nvidia/nvflare | null | NVIDIA Federated Learning Application Runtime Environment | https://nvidia.github.io/NVFlare/ |
pip | https://github.com/pypa/pip | null | The Python package installer | https://pip.pypa.io/ |
Maven | https://github.com/apache/maven | null | Apache Maven is a software project management and comprehension tool. Based on the concept of a project object model (POM), Maven can manage a project's build, reporting and documentation from a central piece of information. | https://maven.apache.org |
SpecForge | https://github.com/sgl-project/SpecForge | null | Train speculative decoding models effortlessly and port them smoothly to SGLang serving. | https://sgl-project.github.io/SpecForge/ |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.