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Projects using CuPy
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Chainer: Powerful, Flexible, and Intuitive Framework for Neural Networks
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pytorch-pfn-extras: Supplementary components to accelerate research and development in PyTorch
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ffcv: Fast Forward Computer Vision - A drop-in data loading system that dramatically increases data throughput in model training
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Microsoft DeepSpeed: Deep learning optimization library that makes distributed training easy, efficient, and effective
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vLLM: Easy, fast, and cheap LLM serving for everyone
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spaCy: Industrial-strength Natural Language Processing (NLP) with Python and Cython
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Thinc: Machine Learning library for NLP in Python
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MONAI: AI Toolkit for Healthcare Imaging
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py4DSTEM: Set of python tools for processing and analysis of four-dimensional scanning transmission electron microscopy (4D-STEM) data
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pomegranate: Fast, flexible and easy to use probabilistic modelling in Python
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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
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NVTabular: Feature engineering and preprocessing library for tabular data
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XGBoost: Scalable, Portable and Distributed Gradient Boosting Library
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einops: Flexible and powerful tensor operations for readable and reliable code
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PyLops: A Linear-Operator Library for Python
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SigPy: Python package for signal processing, with emphasis on iterative methods
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xarray: N-D labeled arrays and datasets
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xarray-spatial: Raster-based Spatial Analytics for Python
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scikit-learn: Machine learning library built on top of SciPy (through Array API support)
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TensorLy: Tensor Learning in Python
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Zarr: An implementation of chunked, compressed, N-dimensional arrays for Python.
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Dask: Scalable analytics in Python
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Ray: An open source framework that provides a simple, universal API for building distributed applications
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NVIDIA cuQuantum: SDK of optimized libraries and tools for accelerating quantum computing workflows
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Optimized Einsum (opt_einsum): A tensor contraction order optimizer
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qutip-cupy: CuPy backend plug-in for QuTiP (Quantum Toolbox in Python)
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qibo: A framework for quantum computing with hardware acceleration
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quimb: Library for quantum information and many-body calculations
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vaex: High Performance Data Visualization
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PyQtGraph: A pure-Python graphics library for PyQt5/PyQt6/PySide2/PySide6
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napari-cupy-image-processing: napari Plug-in for GPU-accelerated image processing
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turboSETI: Python based SETI search algorithm
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3d-ken-burns: 3D Ken Burns Effect from a Single Image using PyTorch
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pytorch-qrnn: Quasi-Recurrent Neural Network (QRNN) for PyTorch
See repositories tagged with cupy and Dependents to explore more projects using/supporting CuPy.
- NLCPy by NEC Corporation: CuPy for SX-Aurora TSUBASA
- ClPy by Fixstars: CuPy for OpenCL (inactive)
- cupy-ibmopt by IBM: CuPy optimized for POWER architecture (inactive)