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QR Decomposition: Demonstration of Distributed Computing on Wireless Sensor Networks By Sherine Abdelhak, Soumik Ghosh, Rabi Chaudhuri, Magdy Bayoumi (A) Approved for public release; distribution is unlimited. CACS, University of Louisiana at Lafayette Lafayette, LA 70504 {spa9242, sxg5317, rxc2763, mab} @ cacs.louisiana.edu High Performance Embedded Computing (HPEC) Workshop 22−23 September 2009
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Decomposition: Demonstration of Distributed Computing on WSN QR Kernel for distributed numerical algorithms on Energy and Resource- constrained Wireless Embedded Platforms Wireless Sensor Network is an example of a severely resource constrained platform Introduction Scope QR-based least mean square (LMS) QR-based recursive least mean square (RLS) RLS and LMS in adaptive filtering and beamforming QR in WSN Blend of Householder reflections, Givens rotations, and AllReduce Proposed QR
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Decomposition: Demonstration of Distributed Computing on WSN QR Contributions Develop a new distributed QR algorithm Achieve a balanced tradeoff between degree of parallelism and communication cost Propose a resource-aware distribution Achieve 2x speedup and 2x energy savings per node vs. centralized (single node) approach Introduction
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Decomposition: Demonstration of Distributed Computing on WSN QR Proposed Scheme Introduction Givens Phase Proposed Algorithm
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Decomposition: Demonstration of Distributed Computing on WSN QR Proposed Scheme Introduction Proposed Distribution on WSN
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