datarinnakkaisuus
Datarinnakkaisuus, also known as data parallelism, is a technique used in parallel computing to speed up computations by distributing the data across multiple processors. Instead of processing a single large dataset on one machine, the data is divided into smaller chunks, and each chunk is processed independently by a separate processor. This approach is particularly effective for tasks that involve performing the same operation on many elements of a dataset, such as in machine learning training or scientific simulations.
The core idea of data parallelism is to replicate the computational task across multiple processing units.
Implementing data parallelism typically involves a framework or library that handles the distribution of data and
Challenges in data parallelism can include the overhead associated with data distribution and communication between processors.