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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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