CuPy is a CUDA array computing library that implements a NumPy-compatible interface for executing array operations and numerical computing on NVIDIA GPUs. It serves as a GPU-accelerated numerical library and a CUDA-based SciPy implementation, offloading heavy calculations to graphics hardware to increase processing speed for scientific and engineering workloads.
The library enables multi-framework tensor exchange, allowing data buffers to be shared between different deep learning frameworks using standardized memory layouts to avoid memory copies. It also supports custom GPU kernel integration, allowing array data to be connected to low-level APIs for precise control over hardware execution.
Broadly, the project covers high-performance array processing and scientific computing workflows. Its capabilities include accelerating array computations and providing tools for large-scale numerical calculations.