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Parallel Computing: Theory and Practice - A Comprehensive Overview

1. Scientific simulations: Parallel computing is used to simulate complex phenomena like climate change, fluid dynamics, and material science.
2. Data analysis: Parallel computing is used to analyze large datasets in fields like genomics, finance, and social media.
3. Machine learning: Parallel computing is used to train large machine learning models and accelerate their execution.

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