並列処理（Parallelism）
多くのことを同時に行うこと。
Parallelism involves dividing a large problem into smaller sub-problems, which are solved concurrently on multiple processors or cores. Unlike concurrency (which deals with managing multiple tasks at once), parallelism is about doing multiple tasks at the same time. It is key to high-performance computing and leveraging modern multi-core CPUs.
graph LR
Center["並列処理（Parallelism）"]:::main
Rel_concurrency["concurrency"]:::related -.-> Center
click Rel_concurrency "/terms/concurrency"
Rel_continuous_integration_ci["continuous-integration-ci"]:::related -.-> Center
click Rel_continuous_integration_ci "/terms/continuous-integration-ci"
Rel_multiprocessing["multiprocessing"]:::related -.-> Center
click Rel_multiprocessing "/terms/multiprocessing"
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🧒 5歳でもわかるように説明
1人で100個のジャガイモの皮をむくのは大変です。でも、友達を4人呼んで全員でバラバラに、同時に皮をむき始めれば、ずっと早く終わりますよね。[CPU](/ja/terms/cpu)という「手」をたくさん使って、一斉に仕事をすることを並列処理といいます。
🤓 Expert Deep Dive
Data Parallelism distributes data across different nodes, while Task Parallelism distributes different sub-functions. Amdahl's Law limits the maximum speedup achievable through parallelism based on the sequential fraction of the code. Massive parallelism is achieved via GPUs (thousands of cores) and MPI clusters (thousands of nodes).