자료유형 | 학위논문 |
---|---|
서명/저자사항 | A Memory Hierarchy- and Network Topology-Aware Framework for Runtime Data Sharing at Scale. |
개인저자 | Zhang, Wenzhao. |
단체저자명 | North Carolina State University. |
발행사항 | [S.l.]: North Carolina State University., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 102 p. |
기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
ISBN | 9780438284661 |
학위논문주기 | Thesis (Ph.D.)--North Carolina State University, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Nagiza F. Samatova. |
요약 | Data 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 |
요약 | In 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 |
요약 | In 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 |
요약 | Then, 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 |
요약 | Finally, 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 |
일반주제명 | Computer science. |
언어 | 영어 |
바로가기 |
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |