Optimizing techniques for saturated arithmetic with first-order linear recurrence

  • Authors:

  • Weihua Zhang;Lili Liu;Chen Zhang;Hongjiong Zhang;Binyu Zang;Chuanqi Zhu

  • Affiliations:

  • Fudan University, Shanghai, China;Fudan University, Shanghai, China;Fudan University, Shanghai, China;Fudan University, Shanghai, China;Fudan University, Shanghai, China;Fudan University, Shanghai, China

  • Venue:
  • Proceedings of the 2009 ACM symposium on Applied Computing
  • Year:
  • 2009

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Abstract

Saturated arithmetic is a typical operation in multimedia applications, most multimedia extensions in the instruction set architecture (ISA) of modern processors provide saturation instructions for such operation. Therefore, extensive researches have focused on how to utilize saturation instructions to optimize programs. Previous algorithms mainly focus on purely saturated arithmetic, however saturated arithmetic is often mingled with first-order linear recurrence (FOLR) in real life applications. When FLOR pattern appears in the program, previous algorithms can not identify the saturated arithmetic as well. In fact, the saturated arithmetic with FOLR (SAWF) is a new and significant pattern, especially, SAWF with one as coefficient is frequently used in multimedia applications. Hence, it is necessary to explore a method with which such pattern can be efficiently vectorized. This paper discusses how to vectorize SAWF, explores the efficient method to vectorize SAWF with one as coefficient and gives its evaluation and implement a library for the optimizing technique. Such an implementation manner can make compilers are able to exploit it more easily. The experimental results shows the optimizing technique can achieve a speedup of 1.19 to 1.46 on Pentium IV processor. At the same time, the optimizing techniques in this paper can also be used to develop a library for SAWF so a programmer can benefit even without changing the compiler.