Collaborative Research: DOT -- Distributed Optical Testbed to Facilitate the Development of Techniques for Efficient Execution of Distributed Applications

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EIA- 0224427Taylor, ValerieChoudhary, Alok; Dinda, Peter A.; Mambretti, Joel J.Northwestern University Title: CISE RR: (Collaborative) DOT--Distributed Optical Testbed to Facilitate the Development of Techniques for Efficient Execution of Distributed Applications This collaborative proposal with Illinois Institute of Technology (Sun, 02-24377) and the University of Chicago (Foster, 02-24187), acquiring data nodes and compute nodes at five sites, contributes to build a Distributed Optical Testbed (DOT). The DOT system, a product of the paradigm shift from large-scale applications running on large parallel systems at single sites to those running on distributed systems, has come about by the availability of high-speed optical networks (E.g., Starlight, TeraGrid 40 Gb/s network, the PacificRail 10 Gb/s network). This shift necessitates techniques that allow applications to efficiently utilize distributed systems. In contrast to parallel systems, these systems must exploit two characteristics:Heterogeneity of resources (processors and networks) and Dynamic changes in performance of shared resources, especially wide area networks. The system, consisting of Linux clusters at six geographically different sites interconnected via two existing research DWDM networks, I-WIRE and OMNInet, involves the following sites: Argonne National Laboratory (ANL), Illinois Institute of Technology (IIT), National Center for Supercomputer Applications (NCSA), Northwester University Chicago Campus (NU-C), Northwestern University Evanston Campus (NU-E), and the University of Chicago (UC). DOT will facilitate the following research activities in the area of distributed applications:Dynamic Load Balancing (Taylor)Performance Monitoring and Prediction (Dinda, Sun, Taylor)Data Management (Choudhary, Foster)The first activity develops techniques utilizing network performance predictions that take into consideration the heterogeneity of the processors and networks of distributed systems to dynamically balance the load during execution. The second extends performance monitoring, modeling and prediction techniques that have been focused on parallel systems and broadband network to distributed systems with optical networks and different topologies. The last develops techniques that manage the distributed data such that the actual data location is transparent and the data is accessed efficiently. These research activities are driven by three applications that have been parallelized using MPI, such that the applications can be easily ported to DOT:ENZO, an adaptive cosmological application,Cactus, an open framework used to solve Einstein's equations, andAudioVoice, a virtualized distributed audio application with physical simulations that have real-time deadlines and varying computational demands.Each application presents challenges, which include adaptivity, flexible framework, and simulations with real-time deadlines.