Parallel Programming

Parallel programming is a programming technique that allows multiple processors to work together on a single problem, dividing the workload among them to achieve faster and more efficient processing. In parallel programming, a program is broken down into smaller tasks that can be executed simultaneously on different processors, allowing for faster execution times. Parallel programming is commonly used in data science and artificial intelligence applications, where large datasets and complex algorithms require significant processing power. Parallel programming can be implemented using a variety of programming languages and frameworks, including MPI, OpenMP, and CUDA.
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