Shared memory

In computer science, shared memory is memory that may be simultaneously accessed by multiple programs with an intent to provide communication among them or avoid redundant copies. Shared memory is an efficient means of passing data between programs. Depending on context, programs may run on a single processor or on multiple separate processors. Using memory for communication inside a single program, e.g. among its multiple threads, is also referred to as shared memory. In computer hardware, shared memory refers to a (typically large) block of random access memory (RAM) that can be accessed by several different central processing units (CPUs) in a multiprocessor computer system. Shared memory systems may use: uniform memory access (UMA): all the processors share the physical memory uniformly; non-uniform memory access (NUMA): memory access time depends on the memory location relative to a processor; cache-only memory architecture (COMA): the local memories for the processors at each node is used as cache instead of as actual main memory. A shared memory system is relatively easy to program since all processors share a single view of data and the communication between processors can be as fast as memory accesses to the same location. The issue with shared memory systems is that many CPUs need fast access to memory and will likely cache memory, which has two complications: access time degradation: when several processors try to access the same memory location it causes contention. Trying to access nearby memory locations may cause false sharing. Shared memory computers cannot scale very well. Most of them have ten or fewer processors; lack of data coherence: whenever one cache is updated with information that may be used by other processors, the change needs to be reflected to the other processors, otherwise the different processors will be working with incoherent data. Such cache coherence protocols can, when they work well, provide extremely high-performance access to shared information between multiple processors.