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DTSTAMP:20230124T171525Z
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DTSTART;TZID=America/Chicago:20221113T110000
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UID:submissions.supercomputing.org_SC22_sess431_miscc194@linklings.com
SUMMARY:Position Paper: A Quantitative Approach for Guiding Data Managemen
 t on Complex Memory Architectures
DESCRIPTION:Workshop\n\nPosition Paper: A Quantitative Approach for Guidin
 g Data Management on Complex Memory Architectures\n\nKammerdiener\n\nRecen
 t trends have led to an increased reliance on more diverse and heterogeneo
 us device technologies to continue performance scaling. As a result, many 
 supercomputers now include memory systems with multiple types of memory st
 orage, each with different power, performance, and capacity characteristic
 s. The community urgently needs new strategies to adapt mission critical a
 pplications to such complex memory architectures. In this talk, we will de
 scribe a quantitative approach that leverages lightweight application moni
 toring to derive and enforce effective runtime management for complex memo
 ry platforms, without requiring any developer effort or even recompilation
  of target programs. Additionally, we will present an evaluation that show
 s our approach can enable substantial performance benefits for a variety o
 f memory intensive applications on real and complex memory hardware.\n\nSe
 ssion Format: Recorded\n\nTag: Architectures, Data Analytics, Datacenter, 
 Extreme Scale Computing, HPC Community Collaboration, Machine Learning and
  Artificial Intelligence, Performance, Resource Management and Scheduling,
  System Software\n\nRegistration Category: Workshop Reg Pass
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