Parallelism
Parallelism is a computing concept where multiple tasks or processes are executed simultaneously, typically across multiple processors, cores, or machines, to improve performance and efficiency. It involves dividing a problem into smaller sub-problems that can be processed concurrently, often used in high-performance computing, data processing, and real-time systems. This contrasts with sequential execution, where tasks are performed one after another.
Developers should learn parallelism to handle computationally intensive tasks, such as scientific simulations, big data analytics, and machine learning model training, where sequential processing would be too slow. It is essential for building scalable applications that can leverage multi-core processors and distributed systems to achieve faster execution times and better resource utilization. Understanding parallelism helps optimize performance in areas like video rendering, financial modeling, and web server handling of concurrent requests.