BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:James Demmel (University of California at Berkeley) DTSTART:20200624T140000Z DTEND:20200624T150000Z DTSTAMP:20260423T041525Z UID:E-NLA/10 DESCRIPTION:Title: C ommunication-Avoiding Algorithms for Linear Algebra\, Machine Learning\, a nd Beyond\nby James Demmel (University of California at Berkeley) as p art of E-NLA - Online seminar series on numerical linear algebra\n\n\nAbst ract\nAlgorithms have two costs: arithmetic and communication\, i.e. movin g data between levels of a memory hierarchy or processors over a network. Communication costs (measured in time or energy per operation) already gre atly exceed arithmetic costs\, and the gap is growing over time following technological trends. Thus our goal is to design algorithms that minimize communication. We present new algorithms that communicate asymptotically l ess than their classical counterparts\, for a variety of linear algebra an d machine learning problems\, demonstrating large speedups on a variety of architectures. Some of these algorithms attain provable lower bounds on c ommunication. We describe generalizations of these bounds\, and optimal al gorithms\, to arbitrary code that can be expressed as nested loops accessi ng arrays\, and to account for arrays having different precisions.\n LOCATION:https://researchseminars.org/talk/E-NLA/10/ END:VEVENT END:VCALENDAR