From the course: Python Parallel and Concurrent Programming Part 1
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Shared vs. distributed memory - Python Tutorial
From the course: Python Parallel and Concurrent Programming Part 1
Shared vs. distributed memory
- In addition to a parallel computer's architecture, which can be categorized using Flynn's Taxonomy, another aspect to consider is, uh- - Memory, it's important to understand how the memory's organized and how the computer accesses data. - Right, you could put a billion processors in a computer but if they can't access memory fast enough to get the instructions and data they need then you won't gain anything from having all those processors. Computer memory usually operates at a much slower speed than processors do, and when one processor is reading or writing to memory that often prevents any other processors from accessing that same memory element. There are two main memory architectures that exist for parallel computing, shared memory and distributed memory. In a shared memory system all processors have access to the same memory as part of a global address space. Although each processor operates independently, if…
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