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An asymmetric multiprocessing (AMP or ASMP) system is a multiprocessor computer system where not all of the multiple interconnected central processing units (CPUs) are treated equally. For example, a system might allow (either at the hardware or operating system level) only one CPU to execute operating system code or might allow only one CPU to ...
The term "multiprocessor" can be confused with the term "multiprocessing". While multiprocessing is a type of processing in which two or more processors work together to execute multiple programs simultaneously, multiprocessor refers to a hardware architecture that allows multiprocessing. [5]
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.
Massively parallel is the term for using a large number of computer processors (or separate computers) to simultaneously perform a set of coordinated computations in parallel.
In Auguin’s SPMD model, the same (parallel) task (“same program”) is executed on different (SIMD) processors (“operating in lock-step mode” [1] acting on a part (“slice”) of the data-vector. Specifically, in their 1985 paper [2] (and similarly in [3] [1]) is stated: “we consider the SPMD (Single Program, Multiple Data) operating ...
In computing, multiple instruction, multiple data (MIMD) is a technique employed to achieve parallelism. Machines using MIMD have a number of processor cores that function asynchronously and independently. At any time, different processors may be executing different instructions on different pieces of data.
Essentially, a GPGPU pipeline is a kind of parallel processing between one or more GPUs and CPUs that analyzes data as if it were in image or other graphic form. While GPUs operate at lower frequencies, they typically have many times the number of cores. Thus, GPUs can process far more pictures and graphical data per second than a traditional CPU.
As an example, if a problem can be described as a pipeline where data x is processed subsequently through functions f, g, h, etc. (the result is h(g(f(x)))), then this can be expressed as a distributed memory problem where the data is transmitted first to the node that performs f that passes the result onto the second node that computes g, and ...