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1
Characterizing Deep-Learning I/O Workloads in TensorFlow:
, In:
2018 IEEE/ACM 3rd International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS)
,
Chien, Steven W. D.
;
Markidis, Stefano
;
Sishtla, Chaitanya Prasad
... - p. 54-63 , 2018
Link:
https://doi.org/10.1109/PDSW-DISCS.2018.00011
RT T1 <cTitle>2018 IEEE/ACM 3rd International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS)</cTitle>: T1 <Title>Characterizing Deep-Learning I/O Workloads in TensorFlow</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-8638422&Exemplar=1&LAN=DE A1 Chien, Steven W. D. A1 Markidis, Stefano A1 Sishtla, Chaitanya Prasad A1 Santos, Luis A1 Herman, Pawel A1 Narasimhamurthy, Sai A1 Laure, Erwin YR 2018 K1 Training K1 Pipelines K1 Checkpointing K1 Prefetching K1 Benchmark testing K1 Google K1 parallel-I/O K1 Input-pipeline K1 Deep-Learning K1 Tensorflow SP 54 OP 63 LK http://dx.doi.org/https://doi.org/10.1109/PDSW-DISCS.2018.00011 DO https://doi.org/10.1109/PDSW-DISCS.2018.00011 SF ELIB - SuUB Bremen
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