Jacobian sparsity detection using Bloom filters.

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Title: Jacobian sparsity detection using Bloom filters.
Authors: Hovland, Paul D.1 (AUTHOR) hovland@anl.gov
Source: Optimization Methods & Software. Apr2026, Vol. 41 Issue 2, p295-307. 13p.
Subjects: Sparse matrices
Abstract: Determining Jacobian sparsity structure is an important step in the efficient computation of sparse Jacobians. We introduce a new method for determining Jacobian sparsity patterns by combining bit vector probing with Bloom filters. We further refine Bloom filter probing by combining it with hierarchical probing to yield a highly effective strategy for Jacobian sparsity pattern determination. [ABSTRACT FROM AUTHOR]
Copyright of Optimization Methods & Software is the property of Taylor & Francis Ltd 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: Determining Jacobian sparsity structure is an important step in the efficient computation of sparse Jacobians. We introduce a new method for determining Jacobian sparsity patterns by combining bit vector probing with Bloom filters. We further refine Bloom filter probing by combining it with hierarchical probing to yield a highly effective strategy for Jacobian sparsity pattern determination. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Optimization Methods & Software is the property of Taylor & Francis Ltd 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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      – Type: doi
        Value: 10.1080/10556788.2023.2285486
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      – Code: eng
        Text: English
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        PageCount: 13
        StartPage: 295
    Subjects:
      – SubjectFull: Sparse matrices
        Type: general
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      – TitleFull: Jacobian sparsity detection using Bloom filters.
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              Text: Apr2026
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