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Symmetric multiprocessing system. Systems operating under a single OS (operating system) with two or more homogeneous processors and with a centralized shared main memory. A symmetric multiprocessor system (SMP) is a system with a pool of homogeneous processors running under a single OS with a centralized, shared main memory.
In computer engineering, instruction pipelining is a technique for implementing instruction-level parallelism within a single processor. Pipelining attempts to keep every part of the processor busy with some instruction by dividing incoming instructions into a series of sequential steps (the eponymous "pipeline") performed by different processor units with different parts of instructions ...
Amazon Simple Queue Service (Amazon SQS) is a distributed message queuing service introduced by Amazon.com as a beta in late 2004, and generally available in mid 2006. [1] [2] It supports programmatic sending of messages via web service applications as a way to communicate over the Internet.
Multiprocessing is the use of two or more central processing units (CPUs) within a single computer system. [ 1 ] [ 2 ] The term also refers to the ability of a system to support more than one processor or the ability to allocate tasks between them.
These methods can be used to help prevent single-event upsets caused by transient errors. [70] Although additional measures may be required in embedded or specialized systems, this method can provide a cost-effective approach to achieve n-modular redundancy in commercial off-the-shelf systems.
Multiple dispatch or multimethods is a feature of some programming languages in which a function or method can be dynamically dispatched based on the run-time (dynamic) type or, in the more general case, some other attribute of more than one of its arguments. [1]
OpenMP (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows.
Exploitation of the concept of data parallelism started in 1960s with the development of the Solomon machine. [1] The Solomon machine, also called a vector processor, was developed to expedite the performance of mathematical operations by working on a large data array (operating on multiple data in consecutive time steps).