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A Study on Vectorization Methods for Multicore SIMD Architecture Provided by Compilers

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 248)

Abstract

SIMD vectorization has received important attention within the last few years as a vital technique to accelerate multimedia, scientific applications and embedded applications on SIMD architectures. SIMD has extensive applications; though the majority and focus has been on multimedia. As a result of it is an area of computing that desires the maximum amount of computing power as possible, and in most of the cases, it is necessary to compute plenty of data at one go. This makes it an honest candidate for parallelization. There are many compiler frameworks which allow vectorization such as Intel ICC, GNU GCC and LLVM etc. In this paper, we will discuss about GNU GCC and LLVM compilers, optimization methods, vectorization methods and evaluate the impact of various vectorization methods supported by these compilers and at last note we will discuss about the methods to enhance the vectorization process.

Keywords

Intel ICC GNU GCC LLVM SIMD Vectorization 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringDr. B.R. Ambedkar National Institute of TechnologyJalandharIndia

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