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Python High Performance Programming by Gabriele Lanaro

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Chapter 4. Parallel Processing

With parallel processing you can increase the amount of calculations your program can do in a given time without needing a faster processor. The main idea is to divide a task into many sub-units and employ multiple processors to solve them independently.

CPUs containing several cores (2, 4, 6, 8, ...) have become a common trend in technology. Increasing the speed of a single processor is costly and problematic; while leveraging the parallel capabilities of cheaper multi-core processors is a feasible route to increase performance.

Parallel processing lets you tackle large scale problems. Scientists and engineers commonly run parallel code on supercomputers—huge networks of standard processors—to simulate massive systems. ...

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