FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support-Reference-Cited by-同舟云学术

FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support

Author:

Noh Seock-Hwan¹,Koo Jahyun¹,Lee Seunghyun¹,Park Jongse²^ORCID,Kung Jaeha³^ORCID

Affiliation:

1. Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea

2. Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejon, South Korea

3. School of Electrical Engineering, Korea University, Seoul, South Korea

Funder

Samsung Research Funding Incubation Center of Samsung Electronics

IC Design Education Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Link

Reference47 articles.

2. CIFAR-10 and CIFAR-100 dataset;krizhevsky,2010

4. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard,2017

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