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BEGIN:VEVENT
DTSTAMP:20210916T132447Z
LOCATION:Ernesto Bertarelli
DTSTART;TZID=Europe/Stockholm:20210709T113000
DTEND;TZID=Europe/Stockholm:20210709T120000
UID:submissions.pasc-conference.org_PASC21_sess189_pap_mar102@linklings.co
 m
SUMMARY:Automatic Generation of Efficient Linear Algebra Programs
DESCRIPTION:Paper\n\nAutomatic Generation of Efficient Linear Algebra Prog
 rams\n\nBarthels, Psarras, Bientinesi\n\nThe level of abstraction at which
  application experts reason about linear algebra computations and the leve
 l of abstraction used by developers of high-performance numerical linear a
 lgebra libraries do not match. The former is conveniently captured by high
 -level languages and libraries such as Matlab and Eigen, while the latter 
 expresses the kernels included in the BLAS and LAPACK libraries.  Unf
 ortunately, the translation from a high-level computation to an efficient 
 sequence of kernels is a task, far from trivial, that requires extensive k
 nowledge of both linear algebra and high-performance computing. Internally
 , almost all high-level languages and libraries use efficient kernels; how
 ever, the translation algorithms are too simplistic and thus lead to a sub
 optimal use of said kernels, with significant performance losses.  In
  order to both achieve the productivity that comes with high-level languag
 es, and make use of the efficiency of low level kernels, we are developing
  Linnea, a code generator for linear algebra problems. As input, Linnea ta
 kes a high-level description of a linear algebra problem and produces as o
 utput an efficient sequence of calls to high-performance kernels.In 25 app
 lication problems, the code generated by Linnea always outperforms Matlab,
  Julia, Eigen and Armadillo, with speedups up to and exceeding 10x.\n\nDom
 ain: CS and Math
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