자료유형 | 학위논문 |
---|---|
서명/저자사항 | Near Data Processing for Efficient and Trusted Systems. |
개인저자 | Aga, Shaizeen. |
단체저자명 | University of Michigan. Computer Science & Engineering. |
발행사항 | [S.l.]: University of Michigan., 2017. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2017. |
형태사항 | 174 p. |
기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
ISBN | 9780438125766 |
학위논문주기 | Thesis (Ph.D.)--University of Michigan, 2017. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Satish Narayanasamy. |
요약 | We live in a world which constantly produces data at a rate which only increases with time. Conventional processor architectures fail to process this abundant data in an efficient manner as they expend significant energy in instruction processin |
요약 | An exciting technique in our repertoire to deal with these challenges is near-data processing. Near-data processing (NDP) is a data-centric paradigm which moves computation to where data resides. This dissertation exploits NDP to both process th |
요약 | To this end, we first propose Compute Caches, a novel NDP technique. Simple augmentations to underlying SRAM design enable caches to perform commonly used operations. In-place computation in caches not only avoids excessive data movement over me |
요약 | Second, this dissertation identifies security advantages of NDP. While memory bus side channel has received much attention, a low-overhead hardware design which defends against it remains elusive. We observe that smart memory, memory with comput |
요약 | This dissertation also addresses a related vulnerability of page fault side channel in which the Operating System (OS) induces page faults to learn application's address trace and deduces application secrets from it. To tackle it, we propose San |
일반주제명 | Computer science. |
언어 | 영어 |
바로가기 | ![]() |