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What is Single Instruction Multiple Data

Handbook of Research on Scalable Computing Technologies
Single Instruction Multiple Data (SIMD) is a technique used to achieve data level parallelism, the same instruction applied to multiple data. It is one category of processor architecture proposed in Flynn’s taxonomy. SIMD was popular in large-scale supercomputers with vector processors. Now, smaller-scale SIMD operations have become widespread in general-purpose computers, such as SSE instructions in regular Intel processors and SIMD instruction set in Cell/B.E. processors.
Published in Chapter:
Cell Processing for Two Scientific Computing Kernels
Meilian Xu (University of Manitoba, Canada), Parimala Thulasiraman (University of Manitoba, Canada), and Ruppa K. Thulasiram (University of Manitoba, Canada)
Copyright: © 2010 |Pages: 25
DOI: 10.4018/978-1-60566-661-7.ch014
Abstract
This chapter uses two scientific computing kernels to illustrate challenges of designing parallel algorithms for one heterogeneous multi-core processor, the Cell Broadband Engine processor (Cell/B.E.). It describes the limitation of the current parallel systems using single-core processors as building blocks. The limitation deteriorates the performance of applications which have data-intensive and computationintensive kernels such as Finite Difference Time Domain (FDTD) and Fast Fourier Transform (FFT). FDTD is a regular problem with nearest neighbour comminuncation pattern under synchronization constraint. FFT based on indirect swap network (ISN) modifies the data mapping in traditional Cooley- Tukey butterfly network to improve data locality, hence reducing the communication and synchronization overhead. The authors hope to unleash the Cell/B.E. and design parallel FDTD and parallel FFT based on ISN by taking into account unique features of Cell/B.E. such as its eight SIMD processing units on the single chip and its high-speed on-chip bus.
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