Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Matthew Tomei"'
Autor:
Das Shomit N, Philip Bedoukian, Mohammad Seyedzadeh, Darien Wood, Bradford M. Beckmann, Rakesh Kumar, Matthew Tomei
Publikováno v:
ACM Transactions on Architecture and Code Optimization. 18:1-27
Cache-block compression is a highly effective technique for both reducing accesses to lower levels in the memory hierarchy (cache compression) and minimizing data transfers (link compression). While many effective cache-block compression algorithms h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf04ec5d9aafbb458cd57267492e4ac0
https://doi.org/10.1145/3462209
https://doi.org/10.1145/3462209
Autor:
Xinan Chen, Yifan Zhang, Kartik K. Kansal, Ian George, Yibo Zhang, Bochao Li, Kelly A. Levick, Yibo Zhao, John B. Harvill, Sourya Basu, Tanya Veeravalli, Alton S. Barbehenn, S. Yagiz Olmez, Lav R. Varshney, Yuncong Geng, Yashaswini Murthy, Adarsh Muthuveeru-Subramaniam, Taha Ameen ur Rahman, Sung Woo Jeon, Fan Wu, Heling Zhang, Ziyue Li, Hassan Dbouk, Shen Yan, Matthew Tomei, Xuechao Wang, Kiwook Lee, James A. Douglas, Peng Xu, Eric A. Wayman
Publikováno v:
DCC
Many information sources are not just sequences of distinguishable symbols but rather have invariances governed by alternative counting paradigms such as permutations, combinations, and partitions. We consider an entire classification of these invari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e06f15cceafa02ad92b2b534588ea69
https://doi.org/10.1109/dcc50243.2021.00061
https://doi.org/10.1109/dcc50243.2021.00061
Autor:
Dennis D. Weller, Jasmin Aghassi-Hagmann, Muhammad Husnain Mubarik, Mehdi B. Tahoori, Rakesh Kumar, Nathaniel Bleier, Matthew Tomei
Publikováno v:
MICRO
A large number of application domains have requirements on cost, conformity, and non-toxicity that silicon-based computing systems cannot meet, but that may be met by printed electronics. For several of these domains, a typical computational task to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8fe9e432fbe399f0ba4fe2722cf8118b
https://doi.org/10.1109/micro50266.2020.00019
https://doi.org/10.1109/micro50266.2020.00019
Publikováno v:
DAC
Graph neural networks (GNNs) have been shown to extend the power of machine learning to problems with graph-structured inputs. Recent research has shown that these algorithms can exceed state-of-the-art performance on applications ranging from molecu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8ddf0c0aba6ea6ffd61d873336a8c63
https://doi.org/10.1109/dac18072.2020.9218751
https://doi.org/10.1109/dac18072.2020.9218751
Publikováno v:
HotEdgeVideo@MOBICOM
Ensuring safety and reliability of autonomous vehicles requires good learning models which, in turn, require a large amount of real-world training data. Data produced by in-vehicle sensors (e.g., cameras, LIDARs, IMUs, etc.) can be used for training;
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe93d0439ad68b7e5f0940d8caf95fac
https://doi.org/10.1145/3349614.3356028
https://doi.org/10.1145/3349614.3356028
Publikováno v:
ISLPED
Many emerging sensor applications are powered by energy harvesters that impose strict power constraints. These applications often do not require high performance or energy efficiency. We explore a technique for minimizing power of a microprocessor fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbeb99ee49ad1813c8f923d631d8fc20
https://doi.org/10.1145/2934583.2934597
https://doi.org/10.1145/2934583.2934597