Cupynumpy

CuPy is an open-source array library that implements a NumPy-compatible Python API on top of NVIDIA CUDA. Its primary purpose is to accelerate numerical computations by leveraging the parallel processing capabilities of NVIDIA GPUs. CuPy provides a high-performance alternative to NumPy for scientific computing, data analysis, and machine learning tasks.

The API of CuPy is designed to be largely compatible with NumPy, meaning that much of the existing NumPy code can be used with CuPy with minimal modifications. This compatibility allows users to easily switch between CPU and GPU computation by simply changing the import statement from 'import numpy as np' to 'import cupy as np'. CuPy supports a wide range of NumPy functions, including array creation, manipulation, mathematical operations, and linear algebra.

Key features of CuPy include its ability to perform element-wise operations, reductions, and complex linear algebra routines on the GPU. It also offers efficient memory management for GPU arrays and can interoperate with other CUDA-enabled libraries. By offloading computations to the GPU, CuPy can achieve significant speedups for large datasets and computationally intensive tasks, making it a valuable tool for researchers and developers working with large-scale numerical problems.