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DTSTAMP:20230831T095746Z
LOCATION:Davos
DTSTART;TZID=Europe/Stockholm:20230627T100800
DTEND;TZID=Europe/Stockholm:20230627T100900
UID:submissions.pasc-conference.org_PASC23_sess110_pos151@linklings.com
SUMMARY:P37 - LIBRSB: Multicore Sparse Matrix Performance Across Languages
  and Architectures
DESCRIPTION:Poster\n\nMichele Martone (Leibniz Supercomputing Centre)\n\nL
 IBRSB (http://librsb.sf.net/) is a highly interoperable multicore CPU-orie
 nted library for sparse matrix computations.<br />It serves as a component
  in sparse linear solvers. LIBRSB builds upon its "RSB" hierarchical and c
 oarse-grained sparse matrices storage. The RSB data structure and algorith
 ms are geared for efficient "Sparse BLAS"-like operations, namely variants
  of sparse multiply and triangular solution. In addition to Sparse BLAS, L
 IBRSB also provides the operations commonly required by interpreted langua
 ges. Thanks to that, it can serve the needs of higher level numerical lang
 uages like GNU Octave or Python, without sacrificing much of its performan
 ce characteristics. This poster presents an overview of usage modes, their
  advantages, and what's in the works. Emphasis is on multi-language suppor
 t, as well as the different portability aspects.\n\nSession Chair: Jibonan
 anda Sanyal (National Renewable Energy Laboratory)
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