HYBRID AND HIERARCHICAL MULTI-TRIAL AND ONESHOT NEURAL ARCHITECTURE SEARCH ON DATACENTER MACHINE LEARNING ACCELERATORS

HYBRID AND HIERARCHICAL MULTI-TRIAL AND ONESHOT NEURAL ARCHITECTURE SEARCH ON DATACENTER MACHINE LEARNING ACCELERATORS

According to various implementations, generally disclosed herein is a hybrid and hierarchical neural architecture search (NAS) approach. The approach includes performing a search space partitioning scheme to divide the search space into sub-search spaces. The approach further includes performing a f...

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Bibliographische Detailangaben
Hauptverfasser: LU, Yifeng, NI, Yun, WANG, Kun, LE, Quoc, V, CHENG, Liqun, LI, Yang, WICKE, Martin, RANGANATHAN, Parthasarathy, LI, Sheng, ANDERSEN, Garrett, Axel, JOUPPI, Norman, Paul, GRADY, Julian, Paul
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Beschreibung
Zusammenfassung:According to various implementations, generally disclosed herein is a hybrid and hierarchical neural architecture search (NAS) approach. The approach includes performing a search space partitioning scheme to divide the search space into sub-search spaces. The approach further includes performing a first type of NAS, such as a Multi-trial NAS, to cover a search across the sub-search spaces. The approach also includes performing a second type of NAS, such as a One-Shot NAS, to cover each sub-search space. The approach further includes automatically stopping the second type of NAS based on one or more early stopping criteria.