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pro vyhledávání: '"Chang, Andre Xian Ming"'
Autor:
Chang, Andre Xian Ming, Khopkar, Parth, Romanous, Bashar, Chaurasia, Abhishek, Estep, Patrick, Windh, Skyler, Vanesko, Doug, Mohideen, Sheik Dawood Beer, Culurciello, Eugenio
The Streaming Engine (SE) is a Coarse-Grained Reconfigurable Array which provides programming flexibility and high-performance with energy efficiency. An application program to be executed on the SE is represented as a combination of Synchronous Data
Externí odkaz:
http://arxiv.org/abs/2205.13675
Deep convolutional neural networks (CNNs) are the deep learning model of choice for performing object detection, classification, semantic segmentation and natural language processing tasks. CNNs require billions of operations to process a frame. This
Externí odkaz:
http://arxiv.org/abs/1708.02579
Convolutional neural networks (CNNs) are the core of most state-of-the-art deep learning algorithms specialized for object detection and classification. CNNs are both computationally complex and embarrassingly parallel. Two properties that leave room
Externí odkaz:
http://arxiv.org/abs/1708.00117
Recurrent Neural Networks (RNNs) have the ability to retain memory and learn data sequences. Due to the recurrent nature of RNNs, it is sometimes hard to parallelize all its computations on conventional hardware. CPUs do not currently offer large par
Externí odkaz:
http://arxiv.org/abs/1511.05552
Autor:
Chang, Andre Xian Ming
Deep Neural Networks (DNNs) are the algorithm of choice for various applications that require modeling large datasets, such as image classification, object detection and natural language processing. DNNs present highly parallel workloadsthat lead to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be1f630700968094603728db9eba8e11
Akademický článek
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Publikováno v:
ACM / SIGPLAN Notices; Jun2018, Vol. 53 Issue 6, p89-93, 5p