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Sparse triangular solves for ILU revisited: data layout crucial to better performance.

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Názov: Sparse triangular solves for ILU revisited: data layout crucial to better performance.
Autori: Smith, Barry, Zhang, Hong
Zdroj: International Journal of High Performance Computing Applications; Nov2011, Vol. 25 Issue 4, p386-391, 6p
Predmety: MACRO processors, DATA, COMPUTER storage devices, BUFFER storage (Computer science), CYBERNETICS
Abstrakt: A key to good processor utilization for sparse matrix computations is storing the data in the format that is most conducive to fast access by the memory system. In particular, for sparse matrix triangular solves the traditional compressed sparse matrix format is poor, and minor adjustments to the data structure can increase the processor utilization dramatically. Such adjustments involve storing the L and U factors separately and storing the U rows ‘backwards' so that they are accessed in a simple streaming fashion during the triangular solves. Changes to the PETSc libraries to use this modified storage format resulted in over twice the floating-point rate for some matrices. This improvement can be accounted for by a decrease in the cache misses and TLB (transaction lookaside buffer) misses in the modified code. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of High Performance Computing Applications is the property of Sage Publications Inc. 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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  Label: Title
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  Data: Sparse triangular solves for ILU revisited: data layout crucial to better performance.
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  Data: <searchLink fieldCode="AR" term="%22Smith%2C+Barry%22">Smith, Barry</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Hong%22">Zhang, Hong</searchLink>
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  Data: International Journal of High Performance Computing Applications; Nov2011, Vol. 25 Issue 4, p386-391, 6p
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  Data: <searchLink fieldCode="DE" term="%22MACRO+processors%22">MACRO processors</searchLink><br /><searchLink fieldCode="DE" term="%22DATA%22">DATA</searchLink><br /><searchLink fieldCode="DE" term="%22COMPUTER+storage+devices%22">COMPUTER storage devices</searchLink><br /><searchLink fieldCode="DE" term="%22BUFFER+storage+%28Computer+science%29%22">BUFFER storage (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22CYBERNETICS%22">CYBERNETICS</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: A key to good processor utilization for sparse matrix computations is storing the data in the format that is most conducive to fast access by the memory system. In particular, for sparse matrix triangular solves the traditional compressed sparse matrix format is poor, and minor adjustments to the data structure can increase the processor utilization dramatically. Such adjustments involve storing the L and U factors separately and storing the U rows ‘backwards' so that they are accessed in a simple streaming fashion during the triangular solves. Changes to the PETSc libraries to use this modified storage format resulted in over twice the floating-point rate for some matrices. This improvement can be accounted for by a decrease in the cache misses and TLB (transaction lookaside buffer) misses in the modified code. [ABSTRACT FROM PUBLISHER]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of High Performance Computing Applications is the property of Sage Publications Inc. 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: 10.1177/1094342010389857
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      – SubjectFull: DATA
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      – SubjectFull: COMPUTER storage devices
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      – SubjectFull: BUFFER storage (Computer science)
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              Text: Nov2011
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