PPT-Parallelization of Sparse

Author : tatyana-admore | Published Date : 2019-12-01

Parallelization of Sparse Coding amp Dictionary Learning Univeristy of Colorado Denver Parallel Distributed System Fall 2016 Huynh Manh 11152016 1 Contents Introduction

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Parallelization of Sparse" is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Parallelization of Sparse: Transcript

Parallelization of Sparse Coding amp Dictionary Learning Univeristy of Colorado Denver Parallel Distributed System Fall 2016 Huynh Manh 11152016 1 Contents Introduction to Sparse Coding Applications of Sparse Representation. 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 Kaushik. . Rajan. Abhishek. . Udupa. William Thies. Rigorous Software Engineering. Microsoft Research, India. Parallelization Reconsidered. Are there dependences between loop iterations?. No. Yes. DOALL Parallelism. From Theory to Practice . Dina . Katabi. O. . Abari. , E. . Adalsteinsson. , A. Adam, F. . adib. , . A. . Agarwal. , . O. C. . Andronesi. , . Arvind. , A. . Chandrakasan. , F. Durand, E. . Hamed. , H. . to Multiple Correspondence . Analysis. G. Saporta. 1. , . A. . . Bernard. 1,2. , . C. . . Guinot. 2,3. 1 . CNAM, Paris, France. 2 . CE.R.I.E.S., Neuilly sur Seine, France. 3 . Université. . François Rabelais. Full storage:. . 2-dimensional array.. (nrows*ncols) memory.. 31. 0. 53. 0. 59. 0. 41. 26. 0. 31. 41. 59. 26. 53. 1. 3. 2. 3. 1. Sparse storage:. . Compressed storage by columns . (CSC).. Three 1-dimensional arrays.. Recovery. . (. Using . Sparse. . Matrices). Piotr. . Indyk. MIT. Heavy Hitters. Also called frequent elements and elephants. Define. HH. p. φ. . (. x. ) = { . i. : |x. i. | ≥ . φ. ||. x||. p. Kaushik. . Rajan. Abhishek. . Udupa. William Thies. Rigorous Software Engineering. Microsoft Research, India. Parallelization Reconsidered. Are there dependences between loop iterations?. No. Yes. DOALL Parallelism. on Single-chip Shared-memory Multicores. Masab. Ahmad, . Kartik. . Lakhsminrarsimhan. , Omer Khan. University of Connecticut. Agenda. Motivation. Characterization Methodology. Characterization Results. ECE 751, Fall 2015. Peng . Liu. 1. Overview. What? JavaScript . Engine optimization. How? Light-weight . software speculation mechanism. 2. [1] Heine. , David, et al. Software and hardware for exploiting speculative parallelism with a multiprocessor. Computer Systems Laboratory, Stanford University, 1997. to Multiple Correspondence . Analysis. G. Saporta. 1. , . A. . . Bernard. 1,2. , . C. . . Guinot. 2,3. 1 . CNAM, Paris, France. 2 . CE.R.I.E.S., Neuilly sur Seine, France. 3 . Université. . François Rabelais. Author: . Vikas. . Sindhwani. and . Amol. . Ghoting. Presenter: . Jinze. Li. Problem Introduction. we are given a collection of N data points or signals in a high-dimensional space R. D. : xi ∈ . Dina . Katabi. O. . Abari. , E. . Adalsteinsson. , A. Adam, F. . adib. , . A. . Agarwal. , . O. C. . Andronesi. , . Arvind. , A. . Chandrakasan. , F. Durand, E. . Hamed. , H. . Hassanieh. , P. . Indyk. Iterative Local Searches. Martin . Burtscher. 1. and Hassan Rabeti. 2. 1. Department of Computer Science, Texas State University-San Marcos. 2. Department of Mathematics, Texas State University-San Marcos. Iterative Local Searches. Martin . Burtscher. 1. and Hassan Rabeti. 2. 1. Department of Computer Science, Texas State University-San Marcos. 2. Department of Mathematics, Texas State University-San Marcos.

Download Document

Here is the link to download the presentation.
"Parallelization of Sparse"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.