Workload characterization: motivation, goals and methodology

Abstract

Understanding the characteristics of workloads is extremely important in the design of efficient computer architectures. Accurate characterization of workload behavior leads to the design of improved architectures. The characterization of applications allows one to tune the processor micro-architecture, memory hierarchy and system architecture to suit particular features in programs. Workload characterization also has a significant impact on performance evaluation. Understanding the nature of the workload and its intrinsic features can help to interpret performance measurements and simulation results. Identifying and characterizing the intrinsic properties of an application in terms of its memory access behavior, locality, control flow behavior, instruction-level parallelism, etc. can eventually lead to a program behavior model, which can be used in conjunction with a processor model to do analytical performance modeling of computer systems. In this paper, we describe the objectives of workload characterization and emphasize the importance of obtaining architecture-independent metrics for workloads. A study of memory reference locality using some generic metrics is presented as an example.