Parallelization: meaning, definitions and examples
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parallelization
[ ˌpærəˌlɛlɪˈzeɪʃən ]
computing process
Parallelization refers to the process of dividing a computational task into smaller parts that can be processed simultaneously across multiple processors or cores. This technique is commonly used in high-performance computing to improve efficiency and speed, enabling large problems to be solved more quickly than they could be with sequential processing.
Synonyms
concurrency, distribution, multithreading.
Examples of usage
- The team used parallelization to speed up the data analysis.
- Effective parallelization can significantly reduce the total run time of applications.
- Parallelization of tasks allows for better resource management.
Etymology
The term 'parallelization' is derived from 'parallel' and the suffix '-ization'. The word 'parallel' comes from the Greek word 'parallelos', meaning 'beside one another'. This concept evolved in mathematics and physics to describe lines or planes that run alongside each other and never meet. As computers began to evolve in the mid-20th century, the necessity for more efficient methods of processing data emerged. Thus, the process of dividing tasks into smaller, simultaneous operations (parallelization) was developed. The suffix '-ization' indicates the act or process of making something into a particular state or condition, which in this case refers to the act of making processes run in parallel. Despite being a relatively modern concept in the computational field, parallelization is foundational in the era of multi-core processors and cloud computing.