Distributed Memory
Distributed memory is a parallel computing architecture where each processor in a system has its own private memory, and processors communicate by passing messages over a network. This contrasts with shared memory systems, where all processors access a common memory space. It is fundamental to building scalable high-performance computing (HPC) clusters and distributed systems.
Developers should learn distributed memory for applications requiring massive scalability, such as scientific simulations, big data processing, and cloud-based services, as it allows systems to scale beyond the limits of single machines. It is essential when working with clusters, supercomputers, or distributed frameworks like Apache Spark, where data is partitioned across nodes to handle large datasets efficiently.