Parallel computing systems refer to architectures and technologies that allow multiple processors or computing units to work together simultaneously to solve a single problem or perform a task. These systems are designed to increase computational speed and efficiency by dividing the workload among multiple processing elements, known as parallelism.
There are various types of parallel computing systems, including:
1. Shared Memory Systems: In these systems, multiple processors share a common memory space. Each processor can access any memory location directly, which simplifies programming but requires mechanisms to manage access conflicts.
2. Distributed Memory Systems: In these systems, each processor has its own memory space, and communication between processors occurs explicitly through message passing. This architecture is more scalable but requires more complex programming models.
3. Hybrid Systems: These systems combine aspects of shared and distributed memory architectures, often using a combination of both shared-memory and message-passing paradigms.
Parallel computing systems are used in various applications, including scientific simulations, data analytics, artificial intelligence, and more. They can range from small-scale multi-core processors in consumer devices to large-scale supercomputers consisting of thousands of processors interconnected by high-speed networks.
