Increased computational performance for vector operations on BLAS-1

Authors

  • José Antonio Muñoz Gómez Universidad de Guadalajara, México
  • Abimael Jiménez Pérez Universidad Autónoma de Ciudad Juárez, México
  • Gustavo Rodríguez Gómez Instituto Nacional de Astrofísica, Óptica y Electrónica, México

Keywords:

Scientific computing, BLAS-1, unroll technique, vector programming

Abstract

The functions library, called Basic Linear Algebra Subprograms (BLAS-1), is considered the programming standard in scientific computing. In this work, we focus on the analysis of various code optimization techniques to increase the computational performance of BLAS-1. In particular, we address a combinational approach to explore possible methods of encoding using unroll technique with di
erent levels of depth, vector data programming with MMX and SSE for Intel processors. Using the main functions of BLAS-1, it was determined numerically a computational increase, expressed in mega-ops, up to 52% compared to the optimized BLAS-1 ATLAS library

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Author Biographies

José Antonio Muñoz Gómez, Universidad de Guadalajara, México

Departamento de Ingeniería, Universidad de Guadalajara, Jalisco

Abimael Jiménez Pérez, Universidad Autónoma de Ciudad Juárez, México

Departamento de Electrónica y Computación

Gustavo Rodríguez Gómez, Instituto Nacional de Astrofísica, Óptica y Electrónica, México

Departamento de Ciencias Computacionales

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Publicaciones en Ciencias y Tecnología Vol 8 Nro 1 años 2014

Published

2015-01-31

How to Cite

[1]
J. A. Muñoz Gómez, A. Jiménez Pérez, and G. Rodríguez Gómez, “Increased computational performance for vector operations on BLAS-1”, Publ.Cienc.Tecnol, vol. 8, no. 1, pp. 31-44, Jan. 2015.

Issue

Vol. 8 No. 1 (2014): January - June

Section

Research Article

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