Cost optimization through unifying multi-cloud resources

Authors: Benjamin C. Nickerson , Synella Gonzales , Elsa M. Luthi , Tian Guo

The major qualifying project (MQP'18)

paper

Abstract:

The goal of this project is to create a multi-cloud web interface that provides users with the cheapest resource provisioning options from Amazon Web Services and Google Cloud Platform. The user can choose between predefined allocations based on workloads or specify a custom amount of resources needed. In addition, our application handles deployments to respective cloud providers. By handling the end-to-end functionality of finding cloud resources and managing deployments, the user is able to optimize costs from multiple providers.

BibTeX

@article{DBLP:journals/corr/Li19arxiv,
  author    = {Shijian Li, Robert J. Walls, Lijie Xu, Tian Guo},
  title     = {Speeding up Deep Learning with Transient Servers},
  journal   = {CoRR},
  volume    = {abs/1903.00045},
  year      = {2019},
  url       = {https://arxiv.org/abs/1903.00045},
  archivePrefix = {arXiv},
  eprint    = {1903.00045},
}