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Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. [1] Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism.
Single instruction, multiple threads (SIMT) is an execution model used in parallel computing where single instruction, multiple data (SIMD) is combined with multithreading. It is different from SPMD in that all instructions in all "threads" are executed in lock-step.
In the study of parallel algorithms, the massively parallel communication model or MPC model is a theoretical model of computing, intended as an abstraction for parallel computing systems that use frameworks such as MapReduce, and frequently applied to algorithmic problems in graph theory.
Atanasoff–Berry computer, the first computer with parallel processing [1] Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically, ILP refers to the average number of instructions run per step of this parallel execution. [2]: 5
The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures. Where a sequential program will iterate over the data structure and operate on indices one at a time, a program exploiting loop-level parallelism will use multiple threads or processes which operate on some or all ...
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation.
The bulk synchronous parallel (BSP) abstract computer is a bridging model for designing parallel algorithms. It is similar to the parallel random access machine (PRAM) model, but unlike PRAM, BSP does not take communication and synchronization for granted. In fact, quantifying the requisite synchronization and communication is an important part ...
Parallel I/O, in the context of a computer, means the performance of multiple input/output operations at the same time, for instance simultaneously outputs to storage devices and display devices. [1] It is a fundamental feature of operating systems .