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Found 4 papers, 2 papers with code
DL2: A Deep Learning-driven Scheduler for Deep Learning Clusters
DL2 is a DL-driven scheduler for DL clusters, targeting global training job expedition by dynamically resizing resources allocated to jobs.
Qiniu Submission to ActivityNet Challenge 2018
We also propose new non-local-based models for further improvement on the recognition accuracy.
Online Job Scheduling in Distributed Machine Learning Clusters
In a shared cluster handling multiple training jobs, a fundamental issue is how to efficiently schedule jobs and set the number of concurrent workers to run for each job, such that server resources are maximally utilized and model training can be completed in time.
Distributed, Parallel, and Cluster Computing
Online Influence Maximization in Non-Stationary Social Networks
Nevertheless, the existing studies mostly investigate the problem on a one-off basis, assuming fixed known influence probabilities among users, or the knowledge of the exact social network topology.
