Dataparallellisuudessa
Dataparallellisuudessa refers to the concept of data parallelism in computing. It is a technique used to speed up computations by dividing a large dataset into smaller chunks and processing these chunks simultaneously on multiple processing units. This approach is particularly effective for tasks that involve repetitive operations on large amounts of data, such as in scientific simulations, machine learning, and big data analytics.
The core idea of data parallelism is to distribute the data across different processors or cores. Each
Implementing data parallelism typically involves frameworks or libraries that handle the distribution of data and the