Analytic Models and Empirical Search: A Hybrid Approach to Code Optimization

Compilers employ system models, sometimes implicitly, to make code optimization decisions. These models are analytic; they reflect their implementor’s understanding and beliefs of the system. While their decisions can be made almost instantaneously, unless the model is perfect their decisions may be flawed. To avoid exercising unique characteristics of a particular machine, such models are necessarily general and conservative. An alternative is to construct an empirical model. Building an empirical model involves extensive search of a parameter space to determine optimal settings. But this search is performed on the actual machine on which the compiler is to be deployed so that, once constructed, its decisions automatically reflect any eccentricities of the target system. Unfortunately, constructing accurate empirical models is expensive and, therefore, their applicability is limited to library generators such as ATLAS and FFTW. Here the high up-front installation cost can amortiz...

• Type: Conference
• Year: 2005
• Where: LCPC
• Authors: Arkady Epshteyn, María Jesús Garzarán, Gerald DeJong, David A. Padua, Gang Ren, Xiaoming Li, Kamen Yotov, Keshav Pingali
• Keywords: Analytic Model, Code Optimization Decisions, Empirical Model, LCPC 2005