| Document Date: 1999-03-30 10:03:12
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City Projects Agency / Rome / Charlotte / MILAN / Services / / Company IBM / Distribute Computing Systems / MIT Press / Rome Laboratory / / / Facility Zvi Kedem Courant Institute of Mathematical Sciences New York University / California Institute of Technology / / IndustryTerm distributed computing system / soft realtime applications / search distance parameters / parallel applications / tunable junction-detection algorithm / tunable image processing application / search distance / continuous media / soft real-time constraints requiring completion / junction detection algorithm / tunable applications / predictable applications / predictable parallel resource management / generalpurpose applications / image-processing applications / resource intensive algorithm / computing / real-time requirements / compute-intensive algorithm / compression algorithms / web-based metacomputing infrastructure / parallel and real-time systems / arbitrator scheduling algorithms / continuous media application / search distance metric / media processing / latter applications / predictable guarantees to applications / / MarketIndex milan/index. / / Organization California Institute of Technology / New York University / New York / National Science Foundation / MIT / Zvi Kedem Courant Institute / / Person M. Rabin / Z. Kedem / P. Dasgupta / S. Sardesai / Vijay Karamcheti / / Position author / QoS arbitrator The QoS arbitrator / QoS Arbitrator / arbitrator / representative / r3 Q2 r3 d2 d3 Q3 Request Allocation Q3 d3 QoS Arbitrator / programmer / / Product Harman On Time Radio / / ProgrammingLanguage C++ / / ProvinceOrState Illinois / California / / Technology resource intensive algorithm / system to the QoS / tunable junction-detection algorithm / virtual reality / QoS arbitrator scheduling algorithms / compression algorithms / compute-intensive algorithm / simulation / Quality of Service / junction detection algorithm / shared memory / image processing / parallel processing / / URL http /
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Exploiting Application Tunability for Efficient, Predictable Parallel Resource Management Fangzhe Chang, Vijay Karamcheti, and Zvi Kedem Courant Institute of Mathematical Sciences New York University, New York, NY 10012