PPT-Routing Algorithms for FPGAs with Sparse Intra-cluster Rout

Author : jane-oiler | Published Date : 2016-03-12

Yehdhih Ould Mohammed Moctar 1 Guy GF Lemieux 2 Philip Brisk 1 1 University of California Riverside 2 University of British Columbia 22 nd International Conference

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Routing Algorithms for FPGAs with Sparse Intra-cluster Rout: Transcript

Yehdhih Ould Mohammed Moctar 1 Guy GF Lemieux 2 Philip Brisk 1 1 University of California Riverside 2 University of British Columbia 22 nd International Conference on Field Programmable Logic and Applications. Such matrices has several attractive properties they support algorithms with low computational complexity and make it easy to perform in cremental updates to signals We discuss applications to several areas including compressive sensing data stream Least Absolute Shrinkage via . The . CLASH. Operator. Volkan. Cevher. Laboratory. for Information . . and Inference Systems – . LIONS / EPFL. http://lions.epfl.ch . . & . Idiap. Research Institute. &. Miriam . Leeser. Dana Brooks. mel@coe.neu.edu brooks@ece.neu.edu. 1. This . work . is supported by: . NSF . CenSSIS. - The Center for Subsurface Sensing and Imaging. Raja . Giryes. ICASSP 2011. Volkan. Cevher. Agenda. The sparse approximation problem. Algorithms and pre-run guarantees. Online performance guarantees. Performance bound. Parameter selection. 2. Sparse approximation. Point Mantissa Alignment and . Normalization in FPGAs. Yehdhih. . Ould. Mohammed Moctar. 1. . Nithin. George. 2. . Hadi. Parandeh-Afshar. 2. . Paolo Ienne. 2. . Guy G.F. Lemieux. 3. . Philip Brisk. S. tate . D. istance:. A Path-based Metric for. Network Analysis. Natali. . Ruchansky. Gonca. . Gürsun. , . Evimaria. . Terzi. , and Mark . Crovella. Shortest Path Distance. Distance Metrics for Analyzing Routing. . Zhang, . Bhaskar. D. . Rao. University of California, San Diego. March . 28, 2012. Recovery of Block Sparse Signals Using the Framework of Block Sparse Bayesian Learning. 1. Outline. Introduction. Network Layer. 4-. 1. 4-. 2. Hierarchical Routing. scale:. . with > . 200 million destinations:. can’t store all . dest’s. in routing tables!. routing table exchange would swamp links!. . administrative autonomy. -Poulin - 4073219. CEG 4136 – Computer Architecture III. November 16. th. , 2010. Questions/Topics. Describe several algorithms used for adaptive . routing.. Describe . problems and advantages of these routing . . Outline. Background. Classification of Routing Protocols. Data Centric Protocols. Flooding and Gossiping. SPIN. Directed Diffusion. Rumor Routing. Background. Sensor . nodes. Small. , wireless, battery . Applications. Lecture 5. : Sparse optimization. Zhu Han. University of Houston. Thanks Dr. . Shaohua. Qin’s efforts on slides. 1. Outline (chapter 4). Sparse optimization models. Classic solvers and omitted solvers (BSUM and ADMM). F. an Li, Yu Wang. IEEE Vehicular Technology Magazine, June 2007. Speaker: . Le . Wang. . Outline. 1. Motivation and overview . 2. . Routing Protocols. Ad Hoc Routing. Position-Based Routing. Cluster-Based Routing. Jim . Demmel. EECS & Math Departments. UC Berkeley. Why avoid communication? . Communication = moving data. Between level of memory hierarchy. Between processors over a network. Running time of an algorithm is sum of 3 terms:. (. 18ISCNPCWN). Dr. N. Sandeep Varma. Routing in Ad Ho Networks – Ad Hoc Environment. Dynamically . changing topology; . Absence . of fixed infrastructure and centralized administration. ;. Bandwidth .

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