Single instruction, single data

In computing, single instruction stream, single data stream (SISD) is a computer architecture in which a single uni-core processor executes a single instruction stream, to operate on data stored in a single memory. This corresponds to the von Neumann architecture.

SISD is one of the four main classifications as defined in Flynn's taxonomy. In this system, classifications are based upon the number of concurrent instructions and data streams present in the computer architecture. According to Michael J. Flynn, SISD can have concurrent processing characteristics. Pipelined processors and superscalar processors are common examples found in most modern SISD computers.^[2]^[3]

Instructions are sent to the control unit from the memory module and are decoded and sent to the processing unit which processes on the data retrieved from memory module and sends back to it.

References[edit]

^ Flynn, Michael J. (September 1972). "Some Computer Organizations and Their Effectiveness" (PDF). IEEE Transactions on Computers. C-21 (9): 948–960. doi:10.1109/TC.1972.5009071.
^ Quinn, Michael J. Chapter 2: Parallel Architectures, Parallel Programming in C with MPI and OpenMP. Boston: McGraw Hill, 2004. ISBN 0-07-282256-2
^ Ibaroudene, Djaffer. Chapter 1: Motivation and History, Parallel Processing. St. Mary's University, San Antonio, TX. Spring 2008.

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[flynn-1972-1] Flynn, Michael J. (September 1972). "Some Computer Organizations and Their Effectiveness" (PDF). IEEE Transactions on Computers. C-21 (9): 948–960. doi:10.1109/TC.1972.5009071.

[2] Quinn, Michael J. Chapter 2: Parallel Architectures, Parallel Programming in C with MPI and OpenMP. Boston: McGraw Hill, 2004. ISBN 0-07-282256-2

[3] Ibaroudene, Djaffer. Chapter 1: Motivation and History, Parallel Processing. St. Mary's University, San Antonio, TX. Spring 2008.

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v t e Parallel computing
General	Distributed computing Parallel computing Massively parallel Cloud computing High-performance computing Multiprocessing Manycore processor GPGPU Computer network Systolic array
Levels	Bit Instruction Thread Task Data Memory Loop Pipeline
Multithreading	Temporal Simultaneous (SMT) Simultaneous and heterogenous Speculative (SpMT) Preemptive Cooperative Clustered multi-thread (CMT) Hardware scout
Theory	PRAM model PEM model Analysis of parallel algorithms Amdahl's law Gustafson's law Cost efficiency Karp–Flatt metric Slowdown Speedup
Elements	Process Thread Fiber Instruction window Array
Coordination	Multiprocessing Memory coherence Cache coherence Cache invalidation Barrier Synchronization Application checkpointing
Programming	Stream processing Dataflow programming Models Implicit parallelism Explicit parallelism Concurrency Non-blocking algorithm
Hardware	Flynn's taxonomy SISD SIMD Array processing (SIMT) Pipelined processing Associative processing MISD MIMD Dataflow architecture Pipelined processor Superscalar processor Vector processor Multiprocessor symmetric asymmetric Memory shared distributed distributed shared UMA NUMA COMA Massively parallel computer Computer cluster Beowulf cluster Grid computer Hardware acceleration
APIs	Ateji PX Boost Chapel HPX Charm++ Cilk Coarray Fortran CUDA Dryad C++ AMP Global Arrays GPUOpen MPI OpenMP OpenCL OpenHMPP OpenACC Parallel Extensions PVM pthreads RaftLib ROCm UPC TBB ZPL
Problems	Automatic parallelization Deadlock Deterministic algorithm Embarrassingly parallel Parallel slowdown Race condition Software lockout Scalability Starvation
Category: Parallel computing