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How AI and DA combined with HPC shape innovation in Exascale architectures

<!--HTML-->Major efforts to build an exascale class computer are under way in four regions of the world. This time, the game changer compared with the previous decade—sustained PF—is the impressive growth of Deep Learning/Ai/Data analytics in all industry segments. This sustained growth and in...

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Autor principal: Sawley, Marie-Christine
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:http://cds.cern.ch/record/2691462
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author Sawley, Marie-Christine
author_facet Sawley, Marie-Christine
author_sort Sawley, Marie-Christine
collection CERN
description <!--HTML-->Major efforts to build an exascale class computer are under way in four regions of the world. This time, the game changer compared with the previous decade—sustained PF—is the impressive growth of Deep Learning/Ai/Data analytics in all industry segments. This sustained growth and inflexion towards data-centric workflows is having a significant impact on the architectural features, from HW and SW perspectives, of an Exascale class computer. At very coarse grain, the main questions raised by this change are: how to move data faster; where to store data in the most efficient and cost effective way possible; how to process complex workflows and how to compute at unprecedented large scale and high performance. For each of these questions we will share how selected technology bricks help us building a powerful and sustainable solution. This talk will also share the importance of collaborations with the community to helped tracing the path up to this new chapter of HPC and Data analytics.
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institution Organización Europea para la Investigación Nuclear
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publishDate 2019
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spelling cern-26914622022-11-02T22:24:40Zhttp://cds.cern.ch/record/2691462engSawley, Marie-ChristineHow AI and DA combined with HPC shape innovation in Exascale architecturesIXPUG 2019 Annual Conference at CERNother events or meetings<!--HTML-->Major efforts to build an exascale class computer are under way in four regions of the world. This time, the game changer compared with the previous decade—sustained PF—is the impressive growth of Deep Learning/Ai/Data analytics in all industry segments. This sustained growth and inflexion towards data-centric workflows is having a significant impact on the architectural features, from HW and SW perspectives, of an Exascale class computer. At very coarse grain, the main questions raised by this change are: how to move data faster; where to store data in the most efficient and cost effective way possible; how to process complex workflows and how to compute at unprecedented large scale and high performance. For each of these questions we will share how selected technology bricks help us building a powerful and sustainable solution. This talk will also share the importance of collaborations with the community to helped tracing the path up to this new chapter of HPC and Data analytics.oai:cds.cern.ch:26914622019
spellingShingle other events or meetings
Sawley, Marie-Christine
How AI and DA combined with HPC shape innovation in Exascale architectures
title How AI and DA combined with HPC shape innovation in Exascale architectures
title_full How AI and DA combined with HPC shape innovation in Exascale architectures
title_fullStr How AI and DA combined with HPC shape innovation in Exascale architectures
title_full_unstemmed How AI and DA combined with HPC shape innovation in Exascale architectures
title_short How AI and DA combined with HPC shape innovation in Exascale architectures
title_sort how ai and da combined with hpc shape innovation in exascale architectures
topic other events or meetings
url http://cds.cern.ch/record/2691462
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AT sawleymariechristine ixpug2019annualconferenceatcern