In computer science, distributed shared memory (DSM) is a form of memory architecture where physically separated memories can be addressed as a single shared address space. The term "shared" does not mean that there is a single centralized memory, but that the address space is shared—i.e., the same physical address on two processors refers to the same location in memory. Distributed global address space (DGAS), is a similar term for a wide class of software and hardware implementations, in which each node of a cluster has access to shared memory in addition to each node's private (i.e., not shared) memory.
Overview
A distributed-memory system, often called a multicomputer, consists of multiple independent processing nodes with local memory modules which is connected by a general interconnection network. Software DSM systems can be implemented in an operating system, or as a programming library and can be thought of as extensions of the underlying virtual memory architecture. When implemented in the operating system, such systems are transparent to the developer; which means that the underlying distributed memory is completely hidden from the users. In contrast, software DSM systems implemented at the library or language level are not transparent and developers usually have to program them differently. However, these systems offer a more portable approach to DSM system implementations. A DSM system implements the shared-memory model on a physically distributed memory system.
DSM can be achieved via software as well as hardware. Hardware examples include cache coherence circuits and network interface controllers. There are three ways of implementing DSM: Page-based approach using virtual memory Shared-variable approach using routines to access shared variables Object-based approach, ideally accessing shared data through object-oriented discipline
Advantages
Scales well with a large number of nodes
Message passing is hidden
Can handle complex and large databases without replication or sending the data to processes Generally cheaper than using a multiprocessor system Provides large virtual memory space Programs are more portable due to common programming interfaces Shield programmers from sending or receiving primitives
Disadvantages
Generally slower to access than non-distributed shared memory
Must provide additional protection against simultaneous accesses to shared data
May incur a performance penalty
Little programmer control over actual messages being generated
Programmers need to understand consistency models to write correct programs
Comparison with message passing
Software DSM systems also have the flexibility to organize the shared memory region in different ways. The page based approach organizes shared memory into pages of fixed size. In contrast, the object based approach organizes the shared memory region as an abstract space for storing shareable objects of variable sizes. Another commonly seen implementation uses a tuple space, in which the unit of sharing is a tuple.
Shared memory architecture may involve separating memory into shared parts distributed amongst nodes and main memory; or distributing all memory between nodes. A coherence protocol, chosen in accordance with a consistency model, maintains memory coherence.
Directory memory coherence
Memory coherence is necessary such that the system which organizes the DSM is able to track and maintain the state of data blocks in nodes across the memories comprising the system. A directory is one such mechanism which maintains the state of cache blocks moving around the system.
States
A basic DSM will track at least three states among nodes for any given block in the directory. There will be some state to dictate the block as uncached (U), a state to dictate a block as exclusively owned or modified owned (EM), and a state to dictate a block as shared (S). As blocks come into the directory organization, they will transition from U to EM (ownership state) in the initial node. The state can transition to S when other nodes begin reading the block.
There are two primary methods for allowing the system to track where blocks are cached and in what condition across each node. Home-centric request-response uses the home to service requests and drive states, whereas requester-centric allows each node to drive and manage its own requests through the home.