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A Memory Hierarchy- and Network Topology-Aware Framework for Runtime Data Sharing at Scale

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서명/저자사항A Memory Hierarchy- and Network Topology-Aware Framework for Runtime Data Sharing at Scale.
개인저자Zhang, Wenzhao.
단체저자명North Carolina State University.
발행사항[S.l.]: North Carolina State University., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항102 p.
기본자료 저록Dissertation Abstracts International 79-12B(E).
Dissertation Abstract International
ISBN9780438284661
학위논문주기Thesis (Ph.D.)--North Carolina State University, 2018.
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Nagiza F. Samatova.
요약Data analytics is often performed in a post-processing manner, as the data generated by an application is first written to the file system, for example parallel file system (PFS), and then read out to dynamic-random-access-memory (DRAM) for anal
요약In this dissertation, we illustrate the value of the proposed framework using large scale scientific datasets generated and shared over modern supercomputers. Specifically, we demonstrate that our framework enables the runtime sharing of the Ada
요약In this dissertation, we propose a framework to facilitate runtime AMR data sharing for scientific applications, with the goals of realizing effective AMR data access and further optimizing data access performance over the staging space by explo
요약Then, we present a set of methods to further extend the framework. The upgraded framework is able to utilize Solid State Drives (SSDs) on modern supercomputers as an over ow space for when the DRAM fills. It can detect common spatially constrain
요약Finally, we present a collection of methods to address some key performance issues plaguing SSDs, such as read contention and files fragmentation. To address read contention issues involved with SSDs, we present a general purpose online read alg
일반주제명Computer science.
언어영어
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