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School: University of Illinois, Urbana-Champaign Year in Fellowship: 4 Practicum: Sandia National Laboratories (2006) Lawrence Livermore National Laboratory (2007)
Field of Study: Computer Science
Contact:
idooley@isaacdooley.com
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Summary of Research My research interest is to improve the performance and scalability of scientific simulations by developing better adaptive runtime systems. For my dissertation, I am developing a learning framework that adaptively optimizes the performance of parallel applications by finding the best communication algorithms and values for exposed application parameters. Optimal choices for communication algorithms and application parameters vary from machine to machine. Adaptive parallel runtime systems already dynamically balance computational load or overall communication volumes, but my research extends to new capabilities for such runtime systems. Publications Orion Lawlor, Hari Govind, Isaac Dooley, Michael Breitenfeld, and Laxmikant Kale; Performance Degradation in the Presence of Subnormal Floating-Point Values; in In OSIHPA Workshop, at PACT05, September 2005. Orion Lawlor, Sayantan Chakravorty, Terry Wilmarth, Nilesh Choudhury, Isaac Dooley, Gengbin Zheng, and Laxmikant Kale; ParFUM: A Parallel Framework for Unstructured Meshes for Scalable Dynamic Physics Applications; in Engineering with Computers, Journal, 2006. Isaac Dooley and Laxmikant Kale; Quantifying the Interference Caused by Subnormal Floating-Point Values; in In OSIHPA Workshop, at PACT06, September 2006. Isaac Dooley; Automated Source-to-Source Translations to Assist Parallel Programmers; in Master's Thesis, Department of Computer Science, University of Illinois 2006. Isaac Dooley, Sandhya Mangala, Laxmikant Kale and Philippe Geubelle; Parallel Simulations of Dynamic Fracture Using Extrinsic Cohesive Elements; in Journal of Scientific Computing, 2008. Isaac Dooley and Laxmikant V. Kale; Control Points for Adaptive Parallel Performance Tuning; in PPL Technical Report, 2008. Isaac Dooley, Chao Mei, Laxmikant V. Kale; NoiseMiner: An Algorithm for Scalable Automatic Computational Noise and Software Interference Detection; Proceedings of HIPS Workshop at IEEE International Parallel and Distributed Processing Symposium 2008. |
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