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Storage Reorganization Techniques for Matrix Computation in a Paging Environment.

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Title: Storage Reorganization Techniques for Matrix Computation in a Paging Environment.
Authors: Fischer, Patrick C.1, Probert, Robert L.2, Rivest, R.
Source: Communications of the ACM. Jul1979, Vol. 22 Issue 7, p405-415. 11p. 7 Diagrams, 1 Chart.
Subjects: Paging (Computer science), Computer science, Matrices (Mathematics), Algorithms, Computer programming
Abstract: In order to multiply matrices while minimizing the number of page fetches required, it is often more efficient to reorganize the data into submatrix form and to use block multiplication rather than to use the best known algorithms which leave the matrices stored in row-(or column-)oriented form. An efficient method for accomplishing this reorganization is given. This also makes possible the derivation of an asymptotically better bound for multiplication of matrices given in row-oriented form by adapting the technique of Strassen to the reorganized data. The reorganization/block multiplication scheme is shown to be advantageous for matrices and pages of realistic size; the Strassen adaptation is not. The former scheme is also shown to be advantageous even if the transpose of one of the matrices is available at no additional cost. [ABSTRACT FROM AUTHOR]
Copyright of Communications of the ACM is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Storage Reorganization Techniques for Matrix Computation in a Paging Environment.
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  Data: <searchLink fieldCode="JN" term="%22Communications+of+the+ACM%22">Communications of the ACM</searchLink>. Jul1979, Vol. 22 Issue 7, p405-415. 11p. 7 Diagrams, 1 Chart.
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  Data: <searchLink fieldCode="DE" term="%22Paging+%28Computer+science%29%22">Paging (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+science%22">Computer science</searchLink><br /><searchLink fieldCode="DE" term="%22Matrices+%28Mathematics%29%22">Matrices (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink>
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  Data: In order to multiply matrices while minimizing the number of page fetches required, it is often more efficient to reorganize the data into submatrix form and to use block multiplication rather than to use the best known algorithms which leave the matrices stored in row-(or column-)oriented form. An efficient method for accomplishing this reorganization is given. This also makes possible the derivation of an asymptotically better bound for multiplication of matrices given in row-oriented form by adapting the technique of Strassen to the reorganized data. The reorganization/block multiplication scheme is shown to be advantageous for matrices and pages of realistic size; the Strassen adaptation is not. The former scheme is also shown to be advantageous even if the transpose of one of the matrices is available at no additional cost. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Communications of the ACM is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1145/359131.359134
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 405
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      – SubjectFull: Paging (Computer science)
        Type: general
      – SubjectFull: Computer science
        Type: general
      – SubjectFull: Matrices (Mathematics)
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Computer programming
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      – TitleFull: Storage Reorganization Techniques for Matrix Computation in a Paging Environment.
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              M: 07
              Text: Jul1979
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              Y: 1979
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