A Visualization Framework for Parallelization

Abstract

Since the advent of multicore processors, developers struggle with the parallelization of legacy software. Automatic methods are only appropriate to identify parallelism at instruction level or within simple loops. For most applications, however, a scalable redesign require profound comprehension of the underlying software architecture and its dynamic aspects. This leads to an increasing demand for interactive tools that foster parallelization at various granularity levels. To cope with this problem, we propose a visualization framework, and three tailored views for parallelism detection. The framework is part of Parceive, a tool that utilizes dynamic binary instrumentation to trace C/C++ and C# programs. The cooperative views allow identification and analysis of potential parallelism scenarios using seamless navigation, abstraction, and filtering. In this paper, we motivate our approach, illustrate the architecture of the visualization framework, and highlight the key features of the views. A case study demonstrates the usefulness of Parceive.