Job merging for machine and deep learning hyperparameter tuning

Job merging for machine and deep learning hyperparameter tuning

Embodiments for efficient machine and deep learning hyperparameter tuning in a distributed computing system. Runtime metrics of each training iteration are collected to identify candidate jobs to merge during an execution phase. The candidate jobs are grouped into job groups, and the job groups cont...

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Hauptverfasser: Feng, Kuan, Su, Zhichao, Zhao, Yi, Liu, Junfeng
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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creator Feng, Kuan
Su, Zhichao
Zhao, Yi
Liu, Junfeng
description Embodiments for efficient machine and deep learning hyperparameter tuning in a distributed computing system. Runtime metrics of each training iteration are collected to identify candidate jobs to merge during an execution phase. The candidate jobs are grouped into job groups, and the job groups containing the candidate jobs are merged together subsequent to each iteration boundary for execution during the execution phase.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
title Job merging for machine and deep learning hyperparameter tuning
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