Adapt or Become Extinct!: The Case for a Unified Framework for Deployment-Time Optimization

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2011

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The High-Performance Computing ecosystem consists of a large variety of execution platforms that demonstrate a wide diversity in hardware characteristics such as CPU architecture, memory organization, interconnection network, accelerators, etc. This environment also presents a number of hard boundaries (walls) for applications which limit software development (parallel programming wall), performance (memory wall, communication wall) and viability (power wall). The only way to survive in such a demanding environment is by adaptation. In this paper we discuss how dynamic information collected during the execution of an application can be utilized to adapt the execution context and may lead to performance gains beyond those provided by static information and compile-time adaptation. We consider specialization based on dynamic information like user input, architectural characteristics such as the memory hierarchy organization, and the execution prole of the application as obtained from the execution platform's performance monitoring units. One of the challenges of future execution platforms is to allow the seamless integration of these various kinds of information with information obtained from static analysis (either during ahead-of-time or just-in-time) compilation. We extend the notion of information-driven adaptation and outline the architecture of an infrastructure designed to enable information ow and adaptation throughout the life-cycle of an application.
Original languageEnglish
Title of host publicationEXADAPT '11 Proceedings of the 1st International Workshop on Adaptive Self-Tuning Computing Systems for the Exaflop Era
PublisherUniversity of Strathclyde
Publication date2011
ISBN (print)978-1-4503-0708-6
DOIs
StatePublished

Conference

ConferenceInternational Workshop on Adaptive Self-Tuning Computing Systems for the Exaflop Era
Number1
CitySan Jose, California
Period01/01/11 → …

Bibliographical note

© ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in EXADAPT '11, http://doi.acm.org/10.1145/2000417.2000422

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