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Projects using CuPy

Kenichi Maehashi edited this page May 9, 2025 · 40 revisions

Projects using/supporting CuPy

Deep Learning

  • Chainer: Powerful, Flexible, and Intuitive Framework for Neural Networks

  • pytorch-pfn-extras: Supplementary components to accelerate research and development in PyTorch

  • ffcv: Fast Forward Computer Vision - A drop-in data loading system that dramatically increases data throughput in model training

  • Microsoft DeepSpeed: Deep learning optimization library that makes distributed training easy, efficient, and effective

  • vLLM: Easy, fast, and cheap LLM serving for everyone

  • DALI: GPU-accelerated library for data loading and pre-processing to accelerate deep learning applications

Natural Language Processing

  • spaCy: Industrial-strength Natural Language Processing (NLP) with Python and Cython

  • Thinc: Machine Learning library for NLP in Python

Bioinformatics

  • MONAI: AI Toolkit for Healthcare Imaging

  • py4DSTEM: Set of python tools for processing and analysis of four-dimensional scanning transmission electron microscopy (4D-STEM) data

Data Science

  • pomegranate: Fast, flexible and easy to use probabilistic modelling in Python

  • NVIDIA RAPIDS: Open GPU Data Science

    • cuDF: GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data
    • cuML: Suite of libraries that implement machine learning algorithms and mathematical primitives functions
    • cuSignal: GPU-accelerated signal processing library
    • cuCIM: Toolkit providing GPU-accelerated I/O, computer vision & image processing primitives for N-Dimensional images with a focus on biomedical imaging
    • cuxfilter: Framework to connect web visualizations to GPU accelerated crossfiltering
    • kvikio: C++ and Python bindings to cuFile
  • nvmath-python: NVIDIA Math Libraries for the Python Ecosystem

  • CUTLASS: CUDA Templates for Linear Algebra Subroutines

  • NVIDIA Warp: A Python framework for high performance GPU simulation and graphics

  • NVTabular: Feature engineering and preprocessing library for tabular data

  • XGBoost: Scalable, Portable and Distributed Gradient Boosting Library

  • einops: Flexible and powerful tensor operations for readable and reliable code

  • PyLops: A Linear-Operator Library for Python

  • SigPy: Python package for signal processing, with emphasis on iterative methods

  • xarray: N-D labeled arrays and datasets

  • xarray-spatial: Raster-based Spatial Analytics for Python

  • scikit-learn: Machine learning library built on top of SciPy (through Array API support)

  • TensorLy: Tensor Learning in Python

  • Zarr: An implementation of chunked, compressed, N-dimensional arrays for Python.

  • HewlettPackard/CAMPIE: Fast and efficient simulation of CAM hardwares on CUDA

  • HewlettPackard/CountryCrab: Distributed simulator for physics-inspired optimization solvers

  • transferwise/hisel: Feature selection tool based on Hilbert-Schmidt Independence Criterion

High-Performance Computing

  • Dask: Scalable analytics in Python

  • Ray: An open source framework that provides a simple, universal API for building distributed applications

Quantum Computing

  • NVIDIA cuQuantum: SDK of optimized libraries and tools for accelerating quantum computing workflows

  • Optimized Einsum (opt_einsum): A tensor contraction order optimizer

  • qutip-cupy: CuPy backend plug-in for QuTiP (Quantum Toolbox in Python)

  • qibo: A framework for quantum computing with hardware acceleration

  • quimb: Library for quantum information and many-body calculations

  • jpmorganchase/QOKit: Fast CPU and GPU simulators for benchmarking the Quantum Approximate Optimization Algorithm

Visualization

Applications

  • turboSETI: Python based SETI search algorithm

  • 3d-ken-burns: 3D Ken Burns Effect from a Single Image using PyTorch

  • pytorch-qrnn: Quasi-Recurrent Neural Network (QRNN) for PyTorch

  • sony/vct: VCT: Training Consistency Models with Variational Noise Coupling

  • apple/ml-pgdvs: Pseudo-Generalized Dynamic View Synthesis [ICLR 2024]

  • NVIDIA Accelerated Computing Hub: NVIDIA curated collection of educational resources related to general purpose GPU programming

Infrastructure

Others

See repositories tagged with cupy and Dependents to explore more projects using/supporting CuPy.

Major CuPy Forks

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