Application Workload Modelling via Run-Time Performance Statistics

Abstract

Modern mobile nomadic devices for example internet tablets and high end mobile phones support diverse distributed and stand-alone applications that were supported by single devices a decade back. Furthermore the complex heterogeneous platforms supporting these applications contain multi-core processors, hardware accelerators and IP cores and all these components can possibly be integrated into a single integrated circuit (chip). The high complexity of both the platform and the applications makes the design space very complex due to the availability of several alternatives. Therefore the system designer must be able to quickly evaluate the performance of different application architectures and implementations on potential platforms. The most popular technique employed nowadays is termed as system-level-performance evaluation which uses abstract workload and platform capacity models. The platform capacity models and application workload models reside at a higher abstraction-level. The platform and application workload models can be instantiated with reduced modeling effort and also operate at a higher simulation speed. This article presents a novel run-time statistics based application workload model extraction and platform configuration technique. This technique is called platform COnfiguration and woRkload generatIoN via code instrumeNtation and performAnce counters (CORINNA) which offers several advantages over compiler based technique called ABSINTH, and also provides automatic configuration of the platform processor models for example cache-hits and misses obtained during the application execution.