Performance Prediction by Benchmark and Machine Analysis

We present a new methodology for CPU performance evaluation based on the concept of an abstract machine model and contrast it with benchmarking. The model consists of a set of abstract parameters representing the basic operations and constructs supported by a particular programming language. The model is machine-independent, and is thus a convenient medium for comparing machines with different instruction sets. A special program, called the machine characterizer, is used to measure the execution times of all abstract parameters. Frequency counts of parameter executions are obtained by instrumenting and running programs of interest. By combining the machine and program characterizations we can and do obtain accurate execution time predictions. This abstract model also permits us to formalize concepts like machine and program similarity.