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020 ▼a 9780438125766
035 ▼a (MiAaPQ)AAI10902970
035 ▼a (MiAaPQ)umichrackham:001129
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 004
1001 ▼a Aga, Shaizeen.
24510 ▼a Near Data Processing for Efficient and Trusted Systems.
260 ▼a [S.l.] : ▼b University of Michigan., ▼c 2017
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2017
300 ▼a 174 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Satish Narayanasamy.
5021 ▼a Thesis (Ph.D.)--University of Michigan, 2017.
520 ▼a 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
520 ▼a 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
520 ▼a 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
520 ▼a 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
520 ▼a 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
590 ▼a School code: 0127.
650 4 ▼a Computer science.
690 ▼a 0984
71020 ▼a University of Michigan. ▼b Computer Science & Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0127
791 ▼a Ph.D.
792 ▼a 2017
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000478 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자