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FireCloud, a scalable cloud-based platform for collaborative genome analysis: Strategies for reducing and controlling costs

By Chet Birger, Megan Hanna, Edward Salinas, Jason Neff, Gordon Saksena, Dimitri Livitz, Daniel Rosebrock, Chip Stewart, Ignaty Leshchiner, Alexander Baumann, Douglas Voet, Kristian Cibulskis, Eric Banks, Anthony Philippakis, Gad Getz

Posted 03 Nov 2017
bioRxiv DOI: 10.1101/209494

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.

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