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020 ▼a 9780438126725
035 ▼a (MiAaPQ)AAI10903066
035 ▼a (MiAaPQ)umichrackham:001239
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 004
1001 ▼a Hill, Parker.
24510 ▼a Bridging the Scalability Gap by Exploiting Error Tolerance for Emerging Applications.
260 ▼a [S.l.] : ▼b University of Michigan., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 149 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Advisers: Jason Mars
5021 ▼a Thesis (Ph.D.)--University of Michigan, 2018.
520 ▼a In recent years, there has been a surge in demand for intelligent applications. These emerging applications are powered by algorithms from domains such as computer vision, image processing, pattern recognition, and machine learning. Across these
520 ▼a Despite the staggering computational requirements and resilience of intelligent applications, current infrastructure uses conventional software and hardware methodologies. These systems needlessly consume resources for every bit of precision and
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 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000562 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자