Parallel Programming Languages: MPI, OpenMPI, OpenMP, CUDA, TTB

In the age of ever-growing devices, massive data and complex computations, the power of multiple processors simultaneously has become crucial. Parallel programming languages and frameworks provide the tools to break down problems into smaller tasks and execute them concurrently, significantly boosting performance. This guide introduces some of the most popular options: MPI, OpenMPI, OpenMP, CUDA, and TTB. We’ll explore their unique strengths, delve into learning resources, and equip you to tackle the exciting world of parallel programming.

Message Passing Interface (MPI)

MPI, or Message Passing Interface, stands as a cornerstone in the realm of parallel programming. It’s a standardized library that allows programmers to write applications that leverage the power of multiple processors or computers working together. Unlike some parallel languages that focus on shared memory within a single machine, MPI excels at distributed-memory systems. This means each processor has its private memory, and communication between them happens by explicitly sending messages. You can visit the detailed tutorial (including videos) on MPI. Here’s a breakdown of what makes MPI so powerful;

Portability: MPI boasts incredible portability across various computer architectures and operating…