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1 Ergebnisse
1
DeftNN : addressing bottlenecks for DNN execution on GPU..:
, In:
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture
,
Hill, Parker
;
Jain, Animesh
;
Hill, Mason
... - p. 786-799 , 2017
Link:
https://dl.acm.org/doi/10.1145/3123939.3123970
RT T1
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture
: T1
DeftNN : addressing bottlenecks for DNN execution on GPUs via synapse vector elimination and near-compute data fission
UL https://suche.suub.uni-bremen.de/peid=acm-3123970&Exemplar=1&LAN=DE A1 Hill, Parker A1 Jain, Animesh A1 Hill, Mason A1 Zamirai, Babak A1 Hsu, Chang-Hong A1 Laurenzano, Michael A. A1 Mahlke, Scott A1 Tang, Lingjia A1 Mars, Jason PB ACM YR 2017 K1 GPU architecture K1 deep neural networks K1 memory bandwidth K1 performance optimization K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks K1 General and reference K1 Cross-computing tools and techniques K1 Performance K1 Computer systems organization K1 Architectures K1 Parallel architectures K1 Single instruction, multiple data SP 786 OP 799 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3123939.3123970 DO https://dl.acm.org/doi/10.1145/3123939.3123970 SF ELIB - SuUB Bremen
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