Open AccessSierra Center of Excellence: Lessons learned
Author(s) -
Johann Dahm,
David F. Richards,
A. P. Black,
Adam Bertsch,
Lea T. Grinberg,
Ian Karlin,
Sara I. L. Kokkila Schumacher,
Edgar A. León,
John R. Neely,
Ramesh Pankajakshan,
Olga Pearce
Publication year - 2020
Publication title -
ibm journal of research and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 95
eISSN - 2151-8556
pISSN - 0018-8646
DOI - 10.1147/jrd.2019.2961069
Subject(s) - ibm , center of excellence , supercomputer , excellence , national laboratory , computer science , software engineering , software , work (physics) , operating system , engineering management , center (category theory) , stack (abstract data type) , process (computing) , best practice , systems engineering , engineering , management , political science , database , engineering physics , mechanical engineering , chemistry , materials science , law , crystallography , nanotechnology , economics
The introduction of heterogeneous computing via GPUs from the Sierra architecture represented a significant shift in direction for computational science at Lawrence Livermore National Laboratory (LLNL), and therefore required significant preparation. Over the last five years, the Sierra Center of Excellence (CoE) has brought employees with specific expertise from IBM and NVIDIA together with LLNL ...
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