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Efficient Implement...
Efficient Implementation of 2-D Convolution on DRRA and DiMArch Architectures
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- Dhilleswararao, Pudi (författare)
- Indian Institute of Technology, Bhubaneswar
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- Ryansh, Rajeev (författare)
- Indian Institute of Technology, Bhubaneswar
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- Boppu, Srinivas (författare)
- Indian Institute of Technology, Bhubaneswar
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- Yang, Yu (författare)
- KTH,Elektronik och inbyggda system
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- Hemani, Ahmed, 1961- (författare)
- KTH,Elektronik och inbyggda system
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(creator_code:org_t)
- Association for Computing Machinery (ACM), 2023
- 2023
- Engelska.
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Ingår i: Proceedings of the 13th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, HEART 2023. - : Association for Computing Machinery (ACM). ; , s. 86-92
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Convolution has been widely employed in image processing and computer vision applications such as picture augmentation, smoothing, and structure extraction. In addition, convolution operations are the most prevalent computing patterns in machine learning domains. Convolutions, for example, are used in a substantial chunk of state-of-the-art convolutional neural network operations. Therefore, effectively mapping convolution operations onto hardware architectures is crucial for achieving superior performance while accelerating convolutional neural networks. In this paper, we proposed various algorithms to efficiently map the 2-D convolution operation onto a dynamically reconfigurable resource array and distributed memory architecture. Furthermore, we have discussed the mapping of 2-D convolution on the target architecture for an input matrix of arbitrary size, as well as the generalization of the proposed approaches for multi-column DRRA architectures.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Inbäddad systemteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Embedded Systems (hsv//eng)
Nyckelord
- Coarse Grain Reconfigurable Architectures
- Convolution
- Convolutional Neural Networks
- Distributed Memory Architecture
- Dynamically Reconfigurable Resource Array
- FPGA
- Machine Learning
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)