| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000331784 |
| 005 | | 20241120142409 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438126725 |
| 035 | |
▼a (MiAaPQ)AAI10903066 |
| 035 | |
▼a (MiAaPQ)umichrackham:001239 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a Hill, Parker. |
| 245 | 10 |
▼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 |
| 502 | 1 |
▼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 |
| 710 | 20 |
▼a University of Michigan.
▼b Computer Science & Engineering. |
| 773 | 0 |
▼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 |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000562
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |