My interests are primarily in the area of Distributed Resource Management. To this end, I am currently involved in: constructing a distributed computing solution for the neutron science community; bringing massive neutron source data to the TeraGrid; leading the development of distributed storage solutions: desktop storage aggregation, addressing data availability and the I/O bandwidth bottleneck for the petaflop storage subsystems, checkpoint storage system, end-user data delivery and dynamic staging grounds using SSDs. My doctoral work was on Globus Data Grid development—built techniques to locate data in highly replicated environments; developed performance prediction strategies for bulk Data Grid transfers aiding data transfer schedules; developed co-allocation middleware enabling parallel and fast access to replicated data, etc. Prior to this, I led the design and development of a performance oriented Linux Cluster—with kernel level modifications—to achieve enhanced throughput.
A Doctorate in Computer Science with specialization in massively distributed Grid storage systems.
Research experience in Grids, distributed storage systems, HPC I/O, file systems, clusters, schedulers, distributed operating systems, etc.
Obtained around four million dollars in research funding as PI and co-PI on projects.
Key contributor of a core team building distributed computing/data management solution for US DOE’s Spallation Neutron Source, a billion dollar infrastructure.
Currently leading an effort to address data availability and I/O bandwidth bottleneck for petascale storage subsystem for leadership class supercomputers; Leading the design and development of distributed storage systems (such as the FreeLoader storage scavenging and stdchk checkpoint storage systems), dynamic staging architecture using SSDs to accelerate I/O pipelines; Previously, led the development of a distributed OS for the Linux kernel.
Research contributions to premier open source projects such as Globus, Linux, etc.
Publications in several peer reviewed conferences and journals in the area of distributed supercomputing
PhD, Computer Science, University of Mississippi, 2003
MS, Computer Science, Universityof Mississippi, 1998
BS, Computer Science, Karnatak Univeristy, India, 1996
X. Ma, S.S. Vazhkudai, Z. Zhang, “Improving Data Availability for Better Access Performance: A Study on Caching Scientific Data on Distributed Desktop Workstations”, Journal of Grid Computing - Special Issue on Volunteer Computing and Desktop Grids, 2009.
S.A. Kiswany, M. Ripeanu, A. Iamnitchi, S. Vazhkudai, “Beyond Music Sharing: An Evaluation of Peer-to-Peer Data Dissemination Techniques in Large Scientific Collaborations”, Journal of Grid Computing, Vol. 7, No. 1, pp. 91-114, March 2009.
M. Ripeanu, M. P. Singh, and S. S. Vazhkudai, “Virtual Organizations”, Guest Editors' Introduction to IEEE Internet Computing: Special Issue on Virtual Organizations, March/April 2008.
S. Vazhkudai, X. Ma, "Recovering Transient Data: Automated On-demand Data Reconstruction and Offloading on Supercomputers", Operating Systems Review: Special Issue on File and Storage Systems, Vol. 41, No. 1, pp. 14-18, January 2007.
J.W. Cobb, A. Geist, J.A. Kohl, S.D. Miller, P.F. Peterson, G.G. Pike, M.A. Reuter, T.Swain, S.S. Vazhkudai, N.N. Vijayakumar, “The Neutron Science TeraGrid Gateway, a TeraGrid Science Gateway to Support the Spallation Neutron Source”, in the Journal of Concurrency and Computation: Practice and Experience, Vol. 19, pp. 809-826, 2007.
V.W. Freeh, X. Ma, S. Vazhkudai, J. Strickland, "Controlling Impact While Aggressively Scavenging Idle Resources" in the Journal of Cluster Computing, Oct 2006.
S. Vazhkudai, X. Ma, V. Freeh, J. Strickland, N. Tammineedi, T.A. Simon, S.L. Scott, "Constructing Collaborative Desktop Storage Caches for Large Scientific Datasets" in the ACM Transactions on Storage (TOS),Vol. 2, No. 3, pp. 221-254, August 2006.
S. Vazhkudai, “Distributed Downloads of Bulk, Replicated Grid Data”, in the International Journal of Grid Computing, Vol. 2, pp. 31-42, 2004.
S. Vazhkudai, J. Schopf, "Using Regression Techniques to Predict Large Data Transfers", in the International Journal of High Performance Computing Applications - Special Issue on Grid Computing: Infrastructure and Applications, Volume 17, No. 3, pp. 249-268, Fall 2003.
S. Vazhkudai, J.M. Syed, P.T. Maginnis, "PODOS - The Design and Implementation of a Performance Oriented Linux Cluster", in the Journal of Future Generation Computer Systems - Special Issue on Cluster Computing, Volume 18, Issue 3, pp. 335-352, January 2002.