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  • Overview
  • Installation
  • User Guide
  • API Reference
  • Contribution Guide
  • Upgrade Guide
  • License

CuPy – NumPy & SciPy for GPU¶

  • Overview
    • Project Goal
  • Installation
    • Requirements
    • Installing CuPy
    • Uninstalling CuPy
    • Upgrading CuPy
    • Reinstalling CuPy
    • Using CuPy inside Docker
    • FAQ
  • Using CuPy on AMD GPU (experimental)
    • Requirements
    • Environment Variables
    • Docker
    • Installing Binary Packages
    • Building CuPy for ROCm From Source
    • Limitations
  • User Guide
    • Basics of CuPy
    • User-Defined Kernels
    • Accessing CUDA Functionalities
    • Fast Fourier Transform with CuPy
    • Memory Management
    • Performance Best Practices
    • Interoperability
    • Differences between CuPy and NumPy
    • API Compatibility Policy
  • API Reference
    • The N-dimensional array (ndarray)
    • Universal functions (cupy.ufunc)
    • Routines (NumPy)
    • Routines (SciPy)
    • CuPy-specific functions
    • Low-level CUDA support
    • Custom kernels
    • Distributed
    • Environment variables
    • Comparison Table
    • Python Array API Support

Development

  • Contribution Guide
    • Classification of Contributions
    • Development Cycle
    • Issues and Pull Requests
    • Coding Guidelines
    • Unit Testing
    • Documentation
    • Tips for Developers

Misc Notes

  • Upgrade Guide
    • CuPy v11
    • CuPy v10
    • CuPy v9
    • CuPy v8
    • CuPy v7
    • CuPy v6
    • CuPy v5
    • CuPy v4
    • CuPy v2
    • Compatibility Matrix
  • License
    • NumPy
    • SciPy
Overview

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