PT  - JOURNAL ARTICLE
AU  - Birger, Chet
AU  - Hanna, Megan
AU  - Salinas, Edward
AU  - Neff, Jason
AU  - Saksena, Gordon
AU  - Livitz, Dimitri
AU  - Rosebrock, Daniel
AU  - Stewart, Chip
AU  - Leshchiner, Ignaty
AU  - Baumann, Alexander
AU  - Voet, Douglas
AU  - Cibulskis, Kristian
AU  - Banks, Eric
AU  - Philippakis, Anthony
AU  - Getz, Gad
TI  - FireCloud, a scalable cloud-based platform for collaborative genome analysis: Strategies for reducing and controlling costs
AID  - 10.1101/209494
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 209494
4099  - http://biorxiv.org/content/early/2017/11/03/209494.short
4100  - http://biorxiv.org/content/early/2017/11/03/209494.full
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.