Sciweavers

Share
PLDI
2003
ACM

A comparison of empirical and model-driven optimization

9 years 2 months ago
A comparison of empirical and model-driven optimization
Empirical program optimizers estimate the values of key optimization parameters by generating different program versions and running them on the actual hardware to determine which values give the best performance. In contrast, conventional compilers use models of programs and machines to choose these parameters. It is widely believed that model-driven optimization does not compete with empirical optimization, but few quantitative comparisons have been done to date. To make such a comparison, we replaced the empirical optimization engine in ATLAS (a system for generating a dense numerical linear algebra library called the BLAS) with a model-driven optimization engine that used detailed models to estimate values for optimization parameters, and then measured the relative performance of the two systems on three different hardware platforms. Our experiments show that model-driven optimization can be surprisingly effective, and can generate code whose performance is comparable to that of c...
Kamen Yotov, Xiaoming Li, Gang Ren, Michael Cibuls
Added 05 Jul 2010
Updated 05 Jul 2010
Type Conference
Year 2003
Where PLDI
Authors Kamen Yotov, Xiaoming Li, Gang Ren, Michael Cibulskis, Gerald DeJong, María Jesús Garzarán, David A. Padua, Keshav Pingali, Paul Stodghill, Peng Wu
Comments (0)
books