Fast parallel algorithms for the maximum sum problem
A problem in pattern recognition is to find the maximum sum over all rectangular subregions of a given ( n × n) matrix of real numbers. The problem has one-dimensional (1D) and two-dimensional (2D) versions. For the 1D version, it is to find the maximum sum over all contiguous subvectors of a given...
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| Veröffentlicht in: | Parallel computing 1995, Vol.21 (3), p.461-466 |
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| container_title | Parallel computing |
| container_volume | 21 |
| creator | Wen, Zhaofang |
| description | A problem in pattern recognition is to find the maximum sum over all rectangular subregions of a given (
n ×
n) matrix of real numbers. The problem has one-dimensional (1D) and two-dimensional (2D) versions. For the 1D version, it is to find the maximum sum over all contiguous subvectors of a given vector of
n real numbers. We give an algorithm for the 1D version running in
O(log
n) time using
O(
(n)
(
log n)
)
processors on the EREW PRAM, and an algorithm for the 2D version which takes
O(log
n) time using
O(
(n
3)
(
log n)
)
processors on the EREW PRAM. |
| doi_str_mv | 10.1016/0167-8191(94)00063-G |
| format | Article |
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n ×
n) matrix of real numbers. The problem has one-dimensional (1D) and two-dimensional (2D) versions. For the 1D version, it is to find the maximum sum over all contiguous subvectors of a given vector of
n real numbers. We give an algorithm for the 1D version running in
O(log
n) time using
O(
(n)
(
log n)
)
processors on the EREW PRAM, and an algorithm for the 2D version which takes
O(log
n) time using
O(
(n
3)
(
log n)
)
processors on the EREW PRAM.</description><identifier>ISSN: 0167-8191</identifier><identifier>EISSN: 1872-7336</identifier><identifier>DOI: 10.1016/0167-8191(94)00063-G</identifier><identifier>CODEN: PACOEJ</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithmics. Computability. Computer arithmetics ; Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; Matrix ; Maximum sum ; Parallel algorithms ; Pattern recognition. Digital image processing. Computational geometry ; Theoretical computing ; Vector</subject><ispartof>Parallel computing, 1995, Vol.21 (3), p.461-466</ispartof><rights>1995</rights><rights>1995 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c364t-e2461de0cf89d515c653cf5f1977623bc45540b7cb7c5770eb76fdd5a0088ac73</citedby><cites>FETCH-LOGICAL-c364t-e2461de0cf89d515c653cf5f1977623bc45540b7cb7c5770eb76fdd5a0088ac73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/0167-8191(94)00063-G$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=3435558$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Wen, Zhaofang</creatorcontrib><title>Fast parallel algorithms for the maximum sum problem</title><title>Parallel computing</title><description>A problem in pattern recognition is to find the maximum sum over all rectangular subregions of a given (
n ×
n) matrix of real numbers. The problem has one-dimensional (1D) and two-dimensional (2D) versions. For the 1D version, it is to find the maximum sum over all contiguous subvectors of a given vector of
n real numbers. We give an algorithm for the 1D version running in
O(log
n) time using
O(
(n)
(
log n)
)
processors on the EREW PRAM, and an algorithm for the 2D version which takes
O(log
n) time using
O(
(n
3)
(
log n)
)
processors on the EREW PRAM.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Matrix</subject><subject>Maximum sum</subject><subject>Parallel algorithms</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Theoretical computing</subject><subject>Vector</subject><issn>0167-8191</issn><issn>1872-7336</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1995</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LAzEQxYMoWKvfwMMeRPSwmmz-7kWQYqtQ8KLnkM1ObCTbrclW9NubtcWjMI-5_N4M7yF0TvANwUTcZslSkZpc1ewaYyxouThAE6JkVUpKxSGa_CHH6CSl9xFiCk8Qm5s0FBsTTQgQChPe-uiHVZcK18diWEHRmS_fbbsiZW1i3wToTtGRMyHB2X5P0ev84WX2WC6fF0-z-2VpqWBDCRUTpAVsnapbTrgVnFrHHamlFBVtLOOc4UbaPFxKDI0Urm25wVgpYyWdosvd3fz3Ywtp0J1PFkIwa-i3SVeSKlrjOoNsB9rYpxTB6U30nYnfmmA9VqTH_HrMr2umfyvSi2y72N83yZrgollbn_68lFHOucrY3Q6DnPXTQ9TJelhbaH0EO-i29___-QEUTXlm</recordid><startdate>1995</startdate><enddate>1995</enddate><creator>Wen, Zhaofang</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>1995</creationdate><title>Fast parallel algorithms for the maximum sum problem</title><author>Wen, Zhaofang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-e2461de0cf89d515c653cf5f1977623bc45540b7cb7c5770eb76fdd5a0088ac73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Algorithmics. Computability. Computer arithmetics</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Matrix</topic><topic>Maximum sum</topic><topic>Parallel algorithms</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Theoretical computing</topic><topic>Vector</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wen, Zhaofang</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Parallel computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wen, Zhaofang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fast parallel algorithms for the maximum sum problem</atitle><jtitle>Parallel computing</jtitle><date>1995</date><risdate>1995</risdate><volume>21</volume><issue>3</issue><spage>461</spage><epage>466</epage><pages>461-466</pages><issn>0167-8191</issn><eissn>1872-7336</eissn><coden>PACOEJ</coden><abstract>A problem in pattern recognition is to find the maximum sum over all rectangular subregions of a given (
n ×
n) matrix of real numbers. The problem has one-dimensional (1D) and two-dimensional (2D) versions. For the 1D version, it is to find the maximum sum over all contiguous subvectors of a given vector of
n real numbers. We give an algorithm for the 1D version running in
O(log
n) time using
O(
(n)
(
log n)
)
processors on the EREW PRAM, and an algorithm for the 2D version which takes
O(log
n) time using
O(
(n
3)
(
log n)
)
processors on the EREW PRAM.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/0167-8191(94)00063-G</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0167-8191 |
| ispartof | Parallel computing, 1995, Vol.21 (3), p.461-466 |
| issn | 0167-8191 1872-7336 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_27383909 |
| source | Elsevier ScienceDirect Journals Complete |
| subjects | Algorithmics. Computability. Computer arithmetics Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Matrix Maximum sum Parallel algorithms Pattern recognition. Digital image processing. Computational geometry Theoretical computing Vector |
| title | Fast parallel algorithms for the maximum sum problem |
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