What are some examples of using CuPy in Python?

What are some examples of using CuPy in Python?

CuPy is a library for GPU-accelerated computing in Python. Here are a few examples of its usage:

1. Array Creation: You can create a CuPy array from a NumPy array using cupy.array().
2. Matrix Operations: Perform matrix multiplication with cupy.dot().
3. Element-wise Operations: Use CuPy for element-wise operations like addition and multiplication.
4. Random Number Generation: Generate random numbers with cupy.random.rand().
5. Fourier Transforms: Use cupy.fft.fft() for fast Fourier transforms.

Can you show me a code snippet for matrix multiplication?

Sure! Here's a simple code snippet for matrix multiplication using CuPy:

import cupy as cp

# Create two random matrices
A = cp.random.rand(3, 2)
B = cp.random.rand(2, 3)

# Perform matrix multiplication
C = cp.dot(A, B)
print(C)

This will multiply matrix A (3x2) with matrix B (2x3) and store the result in C.

How does CuPy compare to NumPy?

CuPy is designed to be a drop-in replacement for NumPy, but it leverages GPU acceleration. While NumPy runs on the CPU, CuPy runs on the GPU, which can significantly speed up computations for large datasets. The API is very similar, so transitioning from NumPy to CuPy is usually straightforward.

What are the prerequisites for using CuPy?

To use CuPy, you need to have a compatible NVIDIA GPU and the CUDA toolkit installed. Additionally, you should have Python and the CuPy library installed, which you can do via pip with pip install cupy.