RT Journal Article
SR Electronic
T1 FireCloud, a scalable cloud-based platform for collaborative genome analysis: Strategies for reducing and controlling costs
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 209494
DO 10.1101/209494
A1 Birger, Chet
A1 Hanna, Megan
A1 Salinas, Edward
A1 Neff, Jason
A1 Saksena, Gordon
A1 Livitz, Dimitri
A1 Rosebrock, Daniel
A1 Stewart, Chip
A1 Leshchiner, Ignaty
A1 Baumann, Alexander
A1 Voet, Douglas
A1 Cibulskis, Kristian
A1 Banks, Eric
A1 Philippakis, Anthony
A1 Getz, Gad
YR 2017
UL http://biorxiv.org/content/early/2017/11/03/209494.abstract
AB FireCloud, one of three NCI Cloud Pilots, is a collaborative genome analysis platform built on a cloud computing infrastructure. FireCloud aims to solve the many challenges presented by the increasingly large data sets and computing requirements employed in cancer research. However, cost uncertainty associated with cloud computing’s pay-as-you-go model is proving to be a barrier to adoption of cloud computing. In this paper we present guidelines for optimizing workflows to minimize cost and reduce latency. Our guidelines include: (i) dynamic disk sizing to efficiently utilize virtual disks; (ii) tuned provisioning of virtual machines (VMs) using a performance monitoring tool; (iii) taking advantage of steep price discounts of preemptible VMs; and (iv) utilizing the optimal parallelization of a task’s workload.