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Training for multi-resolution inference using reusable quan..:
, In:
Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
,
Zhang, Sai Qian
;
McDanel, Bradley
;
Kung, H. T.
. - p. 845-860 , 2021
Link:
https://dl.acm.org/doi/10.1145/3445814.3446741
RT T1 <cTitle>Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems</cTitle>: T1 <Title>Training for multi-resolution inference using reusable quantization terms</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3446741&Exemplar=1&LAN=DE A1 Zhang, Sai Qian A1 McDanel, Bradley A1 Kung, H. T. A1 Dong, Xin PB ACM YR 2021 K1 Multi-resolution inference K1 co-design K1 deep neural networks K1 joint-optimization training K1 quantization K1 systolic arrays K1 Computer systems organization K1 Architectures K1 Other architectures K1 Neural networks K1 Reconfigurable computing K1 Computing methodologies K1 Artificial intelligence K1 Parallel architectures K1 Systolic arrays K1 Data flow architectures SP 845 OP 860 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3445814.3446741 DO https://dl.acm.org/doi/10.1145/3445814.3446741 SF ELIB - SuUB Bremen
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