Java Workload Characterization
This presentation describes a white-box approach to workload characterization applied to Java workloads. We will investigate techniques for computing differences between individual Java benchmarks and describe two models: a model based on bytecode frequencies and execution times, and a model that uses only bytecode frequencies. These models are useful for decomposition and aggregation of Java workloads and for design and evaluation of Java benchmarks at various levels of granularity. Procedures for classifying benchmarks according to granularity and complexity are explained, and illustrated through application to the SPEC JVM98 benchmarks.
Carl Herder is a Masters candidate in Computer Science at SFSU. He has fifteen years of broad software engineering experience, having worked for IBM, internet startups, and much of what is in between. Carl received his BS in Computer Science from SFSU in 1992.