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Originally, the computer has been viewed as a sequential machine. Most computer programming languages require
the programmer to specify algorithms as sequence of instruction.
Processor executes programs by executing machine instructions in a sequence and one at a time.
Each instruction is executed in a sequence of operations (fetch instruction, fetch operands, perform operation store
result.)
It is observed that, at the micro operation level, multiple control signals are generated at the same time.
Instruction pipelining, at least to the extent of overlapping fetch and execute operations, has been around for long
time.
By looking into these phenomenons, researcher has look into the matter whether some operations can be performed
in parallel or not.
As computer technology has evolved, and as the cost of computer hardware has dropped, computer designers have
sought more and more opportunities for parallelism, usual to enhance performance and, in some cases, to increase
availability.
The taxonomy first introduced by Flynn is still the most common way of categorizing systems with parallel processing
capability. Flynn proposed the following categories of computer system:
● Single Instruction, Multiple Data (SIMD) system: A single machine instruction controls the simultaneous execution of a number of processing elements on a lockstep basis. Each processing element has an associated data memory, so that each instruction is executed on a different set of data by the different processors. Vector and array processors fall into this category
● Multiple Instruction, Single Data (MISD) system A sequence of data is transmitted to a set of processors, each of which executes a different instruction sequence. This structure has never been implemented.
● Multiple Instruction, Multiple Data (MIMD) system: A set of processors simultaneously execute different instruction sequences on different data sets. SMPs, clusters, and NUMA systems fits into this category. With the MIMD organization, the processors are general purpose; each is able to process all of the instructions necessary to perform the appropriate data transformation. Further MIMD can be subdivided into two main categories:
● Symmetric multiprocessor (SMP): In an SMP, multiple processors share a single memory or a pool of memory by means of a shared bus or other interconnection mechanism. A distinguish feature is that the memory access time to any region of memory is approximately the same for each processor.
● Single Instruction, Multiple Data (SIMD) system: A single machine instruction controls the simultaneous execution of a number of processing elements on a lockstep basis. Each processing element has an associated data memory, so that each instruction is executed on a different set of data by the different processors. Vector and array processors fall into this category
● Multiple Instruction, Single Data (MISD) system A sequence of data is transmitted to a set of processors, each of which executes a different instruction sequence. This structure has never been implemented.
● Multiple Instruction, Multiple Data (MIMD) system: A set of processors simultaneously execute different instruction sequences on different data sets. SMPs, clusters, and NUMA systems fits into this category. With the MIMD organization, the processors are general purpose; each is able to process all of the instructions necessary to perform the appropriate data transformation. Further MIMD can be subdivided into two main categories:
● Symmetric multiprocessor (SMP): In an SMP, multiple processors share a single memory or a pool of memory by means of a shared bus or other interconnection mechanism. A distinguish feature is that the memory access time to any region of memory is approximately the same for each processor.
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