Parallel processing is a computational technique where multiple tasks are executed simultaneously to enhance processing speed and efficiency. This approach divides large problems into smaller sub-problems, which are solved concurrently by multiple processors. It contrasts with serial processing, where tasks are executed sequentially, one after another.

Key Concepts and Mechanisms

Parallel processing relies on architectures like shared memory, distributed memory, and hybrid memory systems. Shared memory systems allow multiple processors to access the same memory space, while distributed memory systems use separate memory for each processor, connected via a network. Hybrid systems combine these approaches for advanced applications like supercomputers.

Tasks in parallel processing are distributed across multiple functional units, such as arithmetic, logic, and floating-point units, allowing independent operations to occur simultaneously. This improves resource utilization and overall system throughput.