Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
SUIF Explorer: an interactive and interprocedural parallelizer
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
NaraView: an interactive 3D visualization system for parallelization of programs
International Journal of Parallel Programming - Special issue on internation symposium on high preformance computing '97. Part I
Interactive Parallel Programming using the ParaScope Editor
IEEE Transactions on Parallel and Distributed Systems
A Performance Advisor Tool for Shared-Memory Parallel Programming
LCPC '00 Proceedings of the 13th International Workshop on Languages and Compilers for Parallel Computing-Revised Papers
Semi-automatic composition of loop transformations for deep parallelism and memory hierarchies
International Journal of Parallel Programming
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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.