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DTSTART;TZID=America/Denver:20231117T103000
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UID:submissions.supercomputing.org_SC23_sess460_misc334@linklings.com
SUMMARY:Tensor Cores for Matrix Multiplication Are on the Rise – Is There 
 Any Hope for Sparse Operations?
DESCRIPTION:Hartwig Anzt\n\nIn response to the demands from the machine le
 arning community, an increasing number of hardware architectures feature t
 ensor cores for high performance dense matrix multiplication in low precis
 ion. This is increasing the peak performance and power draw - and the expe
 ctation that applications achieve higher performance. But at the same time
 , many application sparse linear algebra is generally unable to exploit th
 e high performance tensor cores. Is there any hope for improved performanc
 e in applications based on sparse linear algebra?\n\nTag: Graph Algorithms
  and Frameworks, Linear Algebra, Programming Frameworks and System Softwar
 e, State of the Practice\n\nRegistration Category: Workshop Reg Pass\n\nSe
 ssion Chairs: Xing Cai (University of Oslo, Norway; Simula Research Labora
 tory/University of Oslo); Aleksandar Ilic (INESC-ID, IST, University of Li
 sbon; University of Lisbon, Portugal); Kamer Kaya (Sabancı University, Tur
 key); and Didem Unat (Koç University, Turkey)\n\n
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