Published in Zhu, M., Wu, Q., & Rao, N. S. V. (2008). Computational monitoring and steering using network-optimized visualization and Ajax web server. IEEE International Symposium on Parallel and Distributed Processing, 2008. IPDPS 2008, 1-12. doi: 10.1109/IPDPS.2008.4536260 ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.


We describe a system for computational monitoring and steering of an on-going computation or visualization on a remote host such as workstation or supercomputer. Unlike the conventional “launch-and-leave” batch computations, this system enables: (i) continuous monitoring of variables of an on-going remote computation using visualization tools, and (ii) interactive specification of chosen computational parameters to steer the computation. The visualization and control streams are supported over wide-area networks using transport protocols based on stochastic approximation methods to provide stable throughput. Using performance models for transport channels and visualization modules, we develop a visualization pipeline configuration solution that minimizes end-to-end delay over wide-area connections. The user interface utilizes Asynchronous JavaScript and XML (Ajax) technologies to provide an interactive environment that can be accessed by multiple remote users using web browsers. We present experimental results on a geographically distributed deployment to illustrate the effectiveness of the proposed system.