A Performance Evaluation of Sequence Alignment Software in Virtualized Environments

Abstract

The prospect of simpler infrastructure management and affordability has garnered interest in cloud computing from bioinformaticians. However, the performance cost of adopting such an infrastructure model for bioinformatics is not fully known. In an effort to help quantify this performance cost, we ran synthetic benchmarks and measured the runtimes of two short-read alignment applications on cloud-like virtualization environments. The environments were implemented utilizing the KVM hypervisor, the Xen hypervisor, and Linux Containers. We compare the runtime in each environment against a physical server and offer discussion and insights. Though the applications perform similar operations, we observe that their performance characteristics differ, as do their performance in the different virtualized environments. We attribute the differences to the way that these programs utilize system resources. We find that the more CPU-bound Novo align is much less sensitive to virtualization environments than BWA is, and has near-physical server performance even when virtualized. Additionally, we find that static CPU pinning can improve performance, and we demonstrate that Linux Containers offer performance comparable to that of a physical server.