cupyndarray

A cupy.ndarray is the fundamental data structure in CuPy, a NumPy-compatible array library accelerated by NVIDIA CUDA. It represents a multi-dimensional array residing in GPU memory, allowing for highly parallel computations. Similar to NumPy's ndarray, cupy.ndarray supports various data types, shapes, and strides, enabling efficient storage and manipulation of data. Operations performed on cupy.ndarray objects are executed on the GPU, significantly speeding up numerical computations compared to CPU-based array operations. This makes it ideal for tasks such as deep learning, scientific simulations, and large-scale data analysis where performance is critical. Users can seamlessly transition between NumPy and CuPy by replacing `numpy` imports with `cupy`, often with minimal code changes, leveraging familiar NumPy syntax for GPU acceleration. Data can be transferred between host (CPU) and device (GPU) memory using methods like `cupy.asarray()` and `cupy.asnumpy()`.