PPT-Compressed Sparse Matrix Storage

Full storage 2dimensional array nrowsncols 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 1dimensional arrays. 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 A Main Memory Compression Framework with . Low Complexity and Low Latency . Gennady Pekhimenko. , . Vivek. . Seshadri. . , . Yoongu. Kim, . Hongyi. . Xin. , . Onur. . Mutlu. , . Todd C. . Mowry. Compressed gas description . Definition of a . compressed gas – . any gas, or mixture . of gases, that is . pressurized and . contained in a . cylinder or tank.. 1a. Compressed gas description . Examples of compressed gases. Yang Lu. April. . 2014. Imperial College London. Outline. Introduction to Synthetic Aperture Radar (SAR) . Background of Compressed Sensing. Reconstruct Radar Image by CS methods. Introduction . to SAR . Exploiting . Spatial Locality . for Energy-Optimized . Compressed Caching. Somayeh. . Sardashti. and . David . A. . Wood. University . of Wisconsin-Madison. 1. 2. 3. Where does energy go?. Communication vs. Computation. 11720026 Daisuke Ishikawa. Introduction. Methods of storing hydrogen. “. L. iquid hydrogen or . Compressed . hydrogen. ”. “. Chemical storage. ”. Metal hydrides, Carbohydrates. “. Physical storage. . Sparse matrix data structures, graphs. , manipulation. Xiaoye . Sherry Li. Lawrence Berkeley National . Laboratory. , . USA. xsli@. lbl.gov. crd-legacy.lbl.gov. /~. xiaoye. /G2S3. /. 4. th. Gene . Student : . Shenghan. TSAI. Advisor : . Hsuan. -Jung Su and . Pin-. Hsun. Lin. Date : M. ay 02, . 2014. 1. Outline. Introduction. Signal---Sparse and Compressible. . - . Sparse & Compressible. Tianzhu . Zhang. 1,2. , . Adel Bibi. 1. , . Bernard Ghanem. 1. 1. 2. Circulant. Primal . Formulation. 3. Dual Formulation. Fourier Domain. Time . Domain. Here, the inverse Fourier transform is for each . Sabareesh Ganapathy. Manav Garg. Prasanna. . Venkatesh. Srinivasan. Convolutional Neural Network. State of the art in Image classification. Terminology – Feature Maps, Weights. Layers - Convolution, . Shreya. Current Query Methods. Data Scans: Loads file into memory and scans. Column oriented stores. Low memory, high latency. Index based scan: the file is preprocessed and stored in memory with indices.. Contents. Problem Statement. Motivation. Types . of . Algorithms. Sparse . Matrices. Methods to solve Sparse Matrices. Problem Statement. Problem Statement. The . solution . of . the linear system is the values of the unknown vector . Disclaimer: . this safety moment is designed to prevent similar incidents occurring. All guidance herein is provided in good faith and Step Change in Safety nor its member companies accept responsibility for any inaccuracies or omissions contained within this safety moment.. John R. Gilbert (. gilbert@cs.ucsb.edu. ). www.cs.ucsb.edu/~gilbert/. cs219. Systems of linear equations:. . Ax = . b. Eigenvalues and eigenvectors:. Aw = . λw. Systems of linear equations: Ax = b.