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pro vyhledávání: '"Hegde, Kartik"'
Autor:
Hegde, Kartik, Tsai, Po-An, Huang, Sitao, Chandra, Vikas, Parashar, Angshuman, Fletcher, Christopher W.
Modern day computing increasingly relies on specialization to satiate growing performance and efficiency requirements. A core challenge in designing such specialized hardware architectures is how to perform mapping space search, i.e., search for an o
Externí odkaz:
http://arxiv.org/abs/2103.01489
As the Moore's scaling era comes to an end, application specific hardware accelerators appear as an attractive way to improve the performance and power efficiency of our computing systems. A massively heterogeneous system with a large number of hardw
Externí odkaz:
http://arxiv.org/abs/1907.00271
The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and the design of accelerators to make CNN inference practical. In the architecture community, the lion share of effort has targeted CNN inference f
Externí odkaz:
http://arxiv.org/abs/1810.06807
Autor:
Hegde, Kartik, Yu, Jiyong, Agrawal, Rohit, Yan, Mengjia, Pellauer, Michael, Fletcher, Christopher W.
Convolutional Neural Networks (CNNs) have begun to permeate all corners of electronic society (from voice recognition to scene generation) due to their high accuracy and machine efficiency per operation. At their core, CNN computations are made up of
Externí odkaz:
http://arxiv.org/abs/1804.06508
Publikováno v:
Computer Sciences & Mathematics Forum; Jan2024, Vol. 9 Issue 1, p3, 15p
Publikováno v:
2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA); 2015, p196-201, 6p