parallel computing

Data Science

Mastering Large Data Processing with mpi4py in Python

Explore the power of mpi4py for simplifying data distribution in parallel computing with its efficient broadcast functionality, which seamlessly sends data from one process to all others, enabling synchronized operations across multiple processors.

Utpal Kumar
June 1, 2024

Data Science, Techniques

Speeding Up Your Code with Parallel Computing in Python

macro photography of black circuit board

Parallel computing is essential for handling large datasets efficiently. In this post, we explore Python's threading, multiprocessing, and joblib libraries to speed up code execution. Learn the differences between threading and multiprocessing, and understand how to use joblib for optimized parallel processing, especially with NumPy arrays.

Utpal Kumar
January 6, 2021