parallelising

Parallelising refers to the technique of performing multiple computations simultaneously. This is in contrast to sequential processing, where operations are carried out one after another. The fundamental goal of parallelising is to speed up computation by dividing a large problem into smaller, independent sub-problems that can be solved concurrently. This can be achieved through various means, such as using multiple processors on a single computer, distributing tasks across multiple computers in a network, or leveraging specialized hardware like GPUs.

The effectiveness of parallelising often depends on the nature of the problem being solved. Some problems are inherently amenable to parallelisation, known as "embarrassingly parallel" problems, where sub-problems have no dependencies on each other. Other problems require more complex coordination and communication between parallel processes, which can introduce overhead and limit the overall speedup. Common applications of parallelising include scientific simulations, data analysis, machine learning, and graphics rendering. The development of parallel programs requires careful consideration of algorithms, data structures, and inter-process communication to maximise efficiency and avoid issues like race conditions or deadlocks.