NDLI: Efficient data compression methods for multidimensional sparse array operations based on the EKMR scheme

Content Provider	IEEE Xplore Digital Library
Author	Chun-Yuan Lin Yeh-Ching Chung Jen-Shiuh Liu
Copyright Year	1968
Abstract	We have proposed the extended Karnaugh map representation (EKMH) scheme for multidimensional array representation. We propose two data compression schemes, EKMR compressed row/column storage (ECRS/ECCS), for multidimensional sparse arrays based on the EKMR scheme. To evaluate the proposed schemes, we compare them to the CRS/CCS schemes. Both theoretical analysis and experimental tests were conducted. In the theoretical analysis, we analyze the CRS/CCS and the ECRS/ECCS schemes in terms of the time complexity, the space complexity, and the range of their usability for practical applications. In experimental tests, we compare the compressing time of sparse arrays and the execution time of matrix-matrix addition and matrix-matrix multiplication based on the CRS/CCS and the ECRS/ECCS schemes. The theoretical analysis and experimental results show that the ECRS/ECCS schemes are superior to the CRS/CCS schemes for all the evaluated criteria, except the space complexity in some case.
Sponsorship	IEEE Computer Society Technical Committee on Distributed Process IEEE Computer Society Technical Committee on VLSI IEEE Technical Committee on Computer Architecture IEEE Computer Society
Starting Page	1640
Ending Page	1646
Page Count	7
File Size	332646
File Format	PDF
ISSN	00189340
Volume Number	52
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data compression Sparse matrices Complexity theory Matrix multiplication Parallel processing
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Software Hardware and Architecture

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Efficient data parallel algorithms for multidimensional array operations based on the EKMR scheme for distributed memory multicomputers

Efficient representation scheme for multidimensional array operations

An Extended Compression Format for the Optimization of Sparse Matrix-Vector Multiplication

Modular Matrix Multiplication on a Linear Array

Efficient VLSI Networks for Parallel Processing Based on Orthogonal Trees

A Preprocessing High-Speed Memory System

Hypergraph-partitioning-based decomposition for parallel sparse-matrix vector multiplication

A Novel Parallel Scan for Multicore Processors and Its Application in Sparse Matrix-Vector Multiplication

Divide-and-Conquer for Parallel Processing

Efficient data compression methods for multidimensional sparse array operations based on the EKMR scheme

Similar Documents

Efficient data parallel algorithms for multidimensional array operations based on the EKMR scheme for distributed memory multicomputers

Efficient representation scheme for multidimensional array operations

An Extended Compression Format for the Optimization of Sparse Matrix-Vector Multiplication

Modular Matrix Multiplication on a Linear Array

Efficient VLSI Networks for Parallel Processing Based on Orthogonal Trees

A Preprocessing High-Speed Memory System

Hypergraph-partitioning-based decomposition for parallel sparse-matrix vector multiplication

A Novel Parallel Scan for Multicore Processors and Its Application in Sparse Matrix-Vector Multiplication

Divide-and-Conquer for Parallel Processing

Efficient data compression methods for multidimensional sparse array operations based on the EKMR scheme