Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Performance Characterization of Optimizing Compilers

Rafael H. Saavedra and Alan Jay Smith

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-92-699
August 1992

http://www.eecs.berkeley.edu/Pubs/TechRpts/1992/CSD-92-699.pdf

Optimizing compilers have become an essential component in achieving high levels of performance. Various simple and sophisticated optimizations are implemented at different stages of compilation to yield significant improvements, but little work has been done in characterizing the effectiveness of optimizers, or in understanding where most of this improvement comes from.

In this paper we study the performance impact of optimization in the context of our methodology for CPU performance characterization based on the abstract machine model. The abstract machine model considers all machines to be different implementations of the same high level language machine; in previous research, we have used this model as a basis to analyze machine and benchmark performance. In this paper, we: 1) show that our model can be extended to characterize the performance improvement provided by optimizers and to predict the run time of optimized programs; 2) measure the effectiveness of several optimizing compilers in implementing different optimization techniques; and 3) analyze the optimization opportunities present in the Fortran SPEC benchmarks and other benchmarks.


BibTeX citation:

@techreport{Saavedra:CSD-92-699,
    Author = {Saavedra, Rafael H. and Smith, Alan Jay},
    Title = {Performance Characterization of Optimizing Compilers},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {1992},
    Month = {Aug},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/1992/5275.html},
    Number = {UCB/CSD-92-699},
    Abstract = {Optimizing compilers have become an essential component in achieving high levels of performance. Various simple and sophisticated optimizations are implemented at different stages of compilation to yield significant improvements, but little work has been done in characterizing the effectiveness of optimizers, or in understanding where most of this improvement comes from. <p>In this paper we study the performance impact of optimization in the context of our methodology for CPU performance characterization based on the abstract machine model. The abstract machine model considers all machines to be different implementations of the same high level language machine; in previous research, we have used this model as a basis to analyze machine and benchmark performance. In this paper, we: 1) show that our model can be extended to characterize the performance improvement provided by optimizers and to predict the run time of optimized programs; 2) measure the effectiveness of several optimizing compilers in implementing different optimization techniques; and 3) analyze the optimization opportunities present in the Fortran SPEC benchmarks and other benchmarks.}
}

EndNote citation:

%0 Report
%A Saavedra, Rafael H.
%A Smith, Alan Jay
%T Performance Characterization of Optimizing Compilers
%I EECS Department, University of California, Berkeley
%D 1992
%@ UCB/CSD-92-699
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/1992/5275.html
%F Saavedra:CSD-92-699