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Semantics-Guided Systems Foundations for Disaggregated Datacenters
Semantics-Guided Systems Foundations for Disaggregated Datacenters
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151939
- ISBN
- 9798382772073
- DDC
- 004
- 저자명
- Ma, Haoran.
- 서명/저자
- Semantics-Guided Systems Foundations for Disaggregated Datacenters
- 발행사항
- [Sl] : University of California, Los Angeles, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 154 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
- 주기사항
- Advisor: Xu, Harry Guoqing;Kim, Miryung.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Los Angeles, 2024.
- 초록/해제
- 요약Resource disaggregation has emerged as a promising solution to enhance both resource utilization and management efficiency in datacenters. Existing disaggregation solutions have largely centered on generic, low-level system optimizations such as minimizing remote access latency at the operating system and hardware levels. However, these solutions often yield suboptimal performance due to the lack of alignment between application semantics and the underlying system layers.This dissertation presents a novel approach that enhances the performance of disaggregated systems by incorporating application semantics, including memory access patterns, data object ownership, and computational intensity, into the system design. Our methodology is demonstrated through three techniques-Mako, MemLiner, and DRust. Each technique applies program semantics at different levels of the system stack, ranging from programming languages and compilers to runtime environments and operating systems. Specifically, Mako and MemLiner utilize program semantics to develop a new runtime that is optimized for disaggregated memory architectures. Meanwhile, DRust employs data object ownership semantics in applications to build a programming framework tailored for compute disaggregation.Collectively, these proposed techniques aim to enhance the performance, efficiency, and consistency of disaggregated systems, making them more viable for practical implementation in today's datacenters. This body of work lays a foundational framework for the co-design and co-optimization of techniques across system layers, aimed at advancing future disaggregated datacenters.
- 일반주제명
- Computer science
- 일반주제명
- Computer engineering
- 키워드
- Semantics
- 기타저자
- University of California, Los Angeles Computer Science 0201
- 기본자료저록
- Dissertations Abstracts International. 85-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798382772073
■035 ▼a(MiAaPQ)AAI31301914
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a004
■1001 ▼aMa, Haoran.
■24510▼aSemantics-Guided Systems Foundations for Disaggregated Datacenters
■260 ▼a[Sl]▼bUniversity of California, Los Angeles▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a154 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-12, Section: B.
■500 ▼aAdvisor: Xu, Harry Guoqing;Kim, Miryung.
■5021 ▼aThesis (Ph.D.)--University of California, Los Angeles, 2024.
■520 ▼aResource disaggregation has emerged as a promising solution to enhance both resource utilization and management efficiency in datacenters. Existing disaggregation solutions have largely centered on generic, low-level system optimizations such as minimizing remote access latency at the operating system and hardware levels. However, these solutions often yield suboptimal performance due to the lack of alignment between application semantics and the underlying system layers.This dissertation presents a novel approach that enhances the performance of disaggregated systems by incorporating application semantics, including memory access patterns, data object ownership, and computational intensity, into the system design. Our methodology is demonstrated through three techniques-Mako, MemLiner, and DRust. Each technique applies program semantics at different levels of the system stack, ranging from programming languages and compilers to runtime environments and operating systems. Specifically, Mako and MemLiner utilize program semantics to develop a new runtime that is optimized for disaggregated memory architectures. Meanwhile, DRust employs data object ownership semantics in applications to build a programming framework tailored for compute disaggregation.Collectively, these proposed techniques aim to enhance the performance, efficiency, and consistency of disaggregated systems, making them more viable for practical implementation in today's datacenters. This body of work lays a foundational framework for the co-design and co-optimization of techniques across system layers, aimed at advancing future disaggregated datacenters.
■590 ▼aSchool code: 0031.
■650 4▼aComputer science
■650 4▼aComputer engineering
■653 ▼aResource disaggregation
■653 ▼aComputational intensity
■653 ▼aData object ownership
■653 ▼aSemantics
■690 ▼a0984
■690 ▼a0464
■71020▼aUniversity of California, Los Angeles▼bComputer Science 0201.
■7730 ▼tDissertations Abstracts International▼g85-12B.
■790 ▼a0031
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17162154▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
