Parallel Simulation Experiments on a Personal Computer - Randall L. Eubank

Parallel simulation is usually presented as a supercomputing topic, wrapped in clusters, schedulers, and specialized languages. Parallel Simulation Experiments on a Personal Computer argues the opposite: the multicore laptop or desktop you already own is enough to run serious simulation experiments, quickly and reproducibly, in both R and Python.

The book is built around sim_template, a compact, extensible program presented in matching R and Python versions, that distributes a simulation across worker processes while giving each worker its own high-quality random number stream. From that foundation the book works through complete, honest examples, with timing tables, missteps, and diagnostics included, showing not just how to parallelize a simulation but how to trust the numbers that come back.

Key Features:

Written for applied statisticians, data scientists, and graduate students who use simulation in their work, the book assumes only basic statistics and some familiarity with R or Python. No parallel computing background is required.