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PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
 M3//EN
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20190510T133347Z
DTSTART:20190510T140000Z
DTEND:20190510T150000Z
SUMMARY:Programming languages for matrix computations
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}a1ir-jvi4g0
 as-qxwpb3
DESCRIPTION:Join us for this research seminar\, part of the Numerical ana
 lysis and scientific computing seminar series.\n\nMatrix computations ap
 pear in virtually every domain of science and engineering\, and due to t
 he seemingly unstoppable growth of data science\, are now as widespread 
 as ever. Such a massive demand triggered two distinct developments. On t
 he one hand\, the numerical linear algebra community has put tremendous 
 effort in the identification\, analysis and optimization of a reasonably
  small set of simple operations---such as those included in the BLAS and
  LAPACK libraries---that serve as building blocks for most users' target
  computations. On the other hand\, the computer science community delive
 red several high-level programming languages---such as Matlab\, Julia\, 
 R---that make it possible to code matrix computations at the same level 
 of abstraction at which experts reason about them. Under the cover\, all
  such languages face the problem of expressing a target matrix computati
 on in terms of said building blocks\; we refer to this problem as the "L
 inear Algebra Mapping Problem" (LAMP). In this talk we define the proble
 m\, present the challenges it poses\, and carefully survey how it is (cu
 rrently) solved by the state-of-the-art languages. Finally\, we introduc
 e Linnea\, our compiler for matrix computations.
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Frank Adams 1\, Alan Turing Building\, Manchester
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