High-level data-access analysis for characterisation of (sub)task-level parallelism on Java

Abstract

In the era of future embedded systems the designer is confronted with multi-processor systems both for performance and energy reasons. Exploiting (sub)task-level parallelism is becoming crucial because the instruction-level parallelism alone is insufficient. The challenge is to build compiler tools that support the exploration of the task-level parallelism in the programs. To achieve this goal, we have designed an analysis framework to evaluate the potential parallelism from sequential object-oriented programs. Parallel-performance and data-access analysis are the crucial techniques for estimation of the transformation effects. We have implemented support for platform-independent data-access analysis and profiling of Java programs, which is an extension to our earlier parallel-performance analysis framework. The toolkit comprises automated design-time analysis for performance and data-access characterisation, program instrumentation, program-profiling support and post-processing analysis. We demonstrate the usability of our approach on a number of realistic Java applications.