RT Journal Article
SR Electronic
T1 Aether: Leveraging Linear Programming for Optimal Cloud Computing In Genomics
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 162883
DO 10.1101/162883
A1 Jacob M. Luber
A1 Braden T. Tierney
A1 Evan M. Cofer
A1 Chirag J. Patel
A1 Aleksandar D. Kostic
YR 2017
UL http://biorxiv.org/content/early/2017/07/13/162883.abstract
AB Across biology we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective, and scalable framework that uses linear programming (LP) to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis while maximizing its efficiency and speed. As a test, we used Aether to de novo assemble 1572 metagenomic samples, a task it completed in merely 13 hours with cost savings of approximately 80% relative to comparable methods.