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Supplementary to the Workflow scheduling submission

Novel Scheduling Algorithms

We present a novel algorithm in this work: MCDS. MCDS uses a deep surrogate model with monte carlo learning to develop a long-term QoS estimate. MCDS uses gradient based optimization to converge to near-optimal scheduling decisions.

Quick Start Guide

To run the COSCO framework, install required packages using

python3 install.py

To run the code with the required scheduler, modify line 117 of main.py to one of the several options including GOSH.

scheduler = MCDSScheduler('energy_latency_'+str(HOSTS))

To run the simulator, use the following command

python3 main.py

Wiki

Access the wiki for detailed installation instructions, implementing a custom scheduler and replication of results. All execution traces and training data is available at Zenodo under CC License.

License

BSD-3-Clause. Copyright (c) 2021, Shreshth Tuli. All rights reserved.

See License file for more details.