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DTSTART;TZID=America/Denver:20191117T091000
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UID:submissions.supercomputing.org_SC19_sess112_pec233@linklings.com
SUMMARY:WORKS19 Keynote: Priority Research Directions for In Situ Data Man
 agement: Enabling Scientific Discovery from Diverse Data Sources
DESCRIPTION:Workshop\n\nWORKS19 Keynote: Priority Research Directions for 
 In Situ Data Management: Enabling Scientific Discovery from Diverse Data S
 ources\n\nPeterka\n\nScientific computing will increasingly incorporate a 
 number of different tasks that need to be managed along with the main simu
 lation or experimental tasks—ensemble analysis, data-driven science, artif
 icial intelligence, machine learning, surrogate modeling, and graph analyt
 ics—all nontraditional applications unheard of in HPC just a few years ago
 . Many of these tasks will need to execute concurrently, that is, in situ,
  with simulations and experiments sharing the same computing resources.\n\
 nThere are two primary, interdependent motivations for processing and mana
 ging data in situ. The first motivation is the need to decrease data volum
 e. The in situ methodology can make critical contributions to managing lar
 ge data from computations and experiments to minimize data movement, save 
 storage space, and boost resource efficiency—often while simultaneously in
 creasing scientific precision. The second motivation is that the in situ m
 ethodology can enable scientific discovery from a broad range of data sour
 ces—HPC simulations, experiments, scientific instruments, and sensor netwo
 rks—over a wide scale of computing platforms: leadership-class HPC, cluste
 rs, clouds, workstations, and embedded devices at the edge.\n\nThe success
 ful development of in situ data management capabilities can potentially be
 nefit real-time decision making, design optimization, and data-driven scie
 ntific discovery. This talk will feature six priority research directions 
 that highlight the components and capabilities needed for in situ data man
 agement to be successful for a wide variety of applications: making in sit
 u data management more pervasive, controllable, composable, and transparen
 t, with a focus on greater coordination with the software stack, and a div
 ersity of fundamentally new data algorithms.\n\nTag: Workshop Reg Pass, Ex
 treme Scale Computing, Scalable Computing, Scientific Workflows\n\nRegistr
 ation Category: Workshop Reg Pass, Extreme Scale Computing, Scalable Compu
 ting, Scientific Workflows
URL:https://sc19.supercomputing.org/presentation/?id=pec233&sess=sess112
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