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Increased system variability and irregularity of parallelism in applications put increasing demands on the ef- ficiency of dynamic task schedulers. This paper presents a new design for a work-stealing scheduler supporting both Cilk- style recursively parallel code and parallelism deduced from dataflow dependences. Initial evaluation on a set of linear algebra kernels demonstrates that our scheduler outperforms PLASMA’s QUARK scheduler by up to 12% on a 16-thread Intel Xeon and by up to 50% on a 32-thread AMD Bulldozer.
|Title of host publication||Proceedings of the Exascale Applications and Software Conference 2015|
|Place of Publication||Edinburgh|
|Publisher||The University of Edinburgh|
|Number of pages||6|
|Publication status||Published - Jul 2015|
|Event||Exascale Applications and Software Conference 2015 - Edinburgh, United Kingdom|
Duration: 21 Apr 2015 → 23 Apr 2015
|Conference||Exascale Applications and Software Conference 2015|
|Period||21/04/2015 → 23/04/2015|
FingerprintDive into the research topics of 'Efficiently Scheduling Task Dataflow Parallelism: A Comparison Between Swan and QUARK'. Together they form a unique fingerprint.
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