Tulipse: A visualization framework for user-guided parallelization

Abstract

Parallelization of existing code for modern multicore processors is tedious as the person performing these tasks must understand the algorithms, data structures and data dependencies in order to do a good job. Current options available to the programmer include either automatic parallelization or a complete rewrite in a parallel programming language. However, there are limitations with these options. In this paper, we propose a framework that enables the programmer to visualize information critical for semi-automated parallelization. The framework, called Tulipse, offers a program structure view that is augmented with key performance information, and a loop-nest dependency view that can be used to visualize data dependencies gathered from static or dynamic analyses. Our paper will demonstrate how these two new perspectives aid in the parallelization of code. © 2012 Springer-Verlag.