Distributedmemoryjärjestelmissä

Distributed memory systems, known in Finnish as hajautetun muistin järjestelmät, are a class of parallel computing architectures where each processor has its own private memory. Unlike shared memory systems where all processors can access a single, common memory space, in distributed memory systems, processors communicate with each other by explicitly sending and receiving messages over a network. This lack of shared memory means that data must be explicitly moved between the memories of different processors to be processed by them.

The primary advantage of distributed memory systems is their scalability. Since there's no contention for a single shared memory resource, these systems can be built with a very large number of processors. This makes them suitable for tackling extremely large and computationally intensive problems, such as those found in scientific simulations, weather forecasting, and complex data analysis. However, programming for distributed memory systems can be more challenging. Developers must carefully manage data distribution and communication patterns to achieve efficient performance. Common programming models and libraries for distributed memory systems include MPI (Message Passing Interface), which provides a standardized way to send and receive messages between processes. The network interconnect plays a crucial role in the performance of these systems, as the speed and latency of communication directly impact the overall execution time of parallel applications.