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LOCATION:Track 4
DTSTART;TZID=America/New_York:20201119T100000
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UID:submissions.supercomputing.org_SC20_sess171@linklings.com
SUMMARY:Data Analysis and Reduction
DESCRIPTION:Paper\n\nForesight: Analysis That Matters for Data Reduction\n
 \nGrosset, Biwer, Pulido, Mohan, Biswas...\n\nAs the computational power o
 f supercomputers increases, so does simulation size, which in turn produce
 s orders-of-magnitude more data. Because generated data often exceed the s
 imulation’s disk quota, many simulations would stand to benefit from data-
 reduction techniques to reduce storage requirement...\n\n-----------------
 ----\nMoHA: A Composable System for Efficient In-Situ Analytics on Heterog
 eneous HPC Systems\n\nXing, Agrawal, Ramnath\n\nHeterogeneous, dense compu
 ting architectures consisting of several accelerators, such as GPUs, attac
 hed to general-purpose CPUs are now integral to high-performance computing
  (HPC) systems.  These architectures, however, pose severe memory and I/O 
 constraints to computations involving in-situ analyt...\n\n---------------
 ------\nJob Characteristics on Large-Scale Systems: Long-Term Analysis, Qu
 antification and Implications\n\nPatel, Liu, Kettimuthu, Rich, Allcock...\
 n\nHPC workload analysis and resource consumption characteristics are the 
 key to driving better operation practices, system procurement decisions an
 d designing effective resource management techniques. Unfortunately, the H
 PC community does not have easy accessibility to long-term introspective w
 orkload...\n\n\nTag: Data Analytics, Compression, and Management, Performa
 nce/Productivity Measurement and Evaluation, Resource Management and Sched
 uling\n\nRegistration Category: Tech Program Reg Pass
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