---
res:
  bibo_abstract:
  - We present a parallel algorithm for computing the persistent homology of a filtered
    chain complex. Our approach differs from the commonly used reduction algorithm
    by first computing persistence pairs within local chunks, then simplifying the
    unpaired columns, and finally applying standard reduction on the simplified matrix.
    The approach generalizes a technique by Günther et al., which uses discrete Morse
    Theory to compute persistence; we derive the same worst-case complexity bound
    in a more general context. The algorithm employs several practical optimization
    techniques, which are of independent interest. Our sequential implementation of
    the algorithm is competitive with state-of-the-art methods, and we further improve
    the performance through parallel computation.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Ulrich
      foaf_name: Bauer, Ulrich
      foaf_surname: Bauer
      foaf_workInfoHomepage: http://www.librecat.org/personId=2ADD483A-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-9683-0724
  - foaf_Person:
      foaf_givenName: Michael
      foaf_name: Kerber, Michael
      foaf_surname: Kerber
    orcid: 0000-0002-8030-9299
  - foaf_Person:
      foaf_givenName: Jan
      foaf_name: Reininghaus, Jan
      foaf_surname: Reininghaus
      foaf_workInfoHomepage: http://www.librecat.org/personId=4505473A-F248-11E8-B48F-1D18A9856A87
  bibo_doi: 10.1007/978-3-319-04099-8_7
  dct_date: 2014^xs_gYear
  dct_language: eng
  dct_publisher: Springer@
  dct_title: 'Clear and Compress: Computing Persistent Homology in Chunks@'
...