Towards High-level Software Approaches to Reduce Virtualization Overhead for Parallel Applications

Abstract

Due to its numerous advantages, the IT industry is moving more and more towards the cloud for hosting applications. Reducing the virtualization overhead inherent to cloud computing has therefore been a topic of much research and innovation, resulting in a drastic reduction of this overhead for most workloads. For specific tasks however, challenges remain. One example is parallel, CPU-intensive workloads. Studies concerning this specific workload exist, but focus on low-level properties of the virtualization process, which are often out of reach of the application programmer in commercial cloud environments. Therefore, we aim to approach virtualization overhead from an application architecture and implementation perspective, and provide guidelines for application programmers to develop their software in such a way that they avoid virtualization overhead without the need for access to the hypervisor or specific hardware. As a first step towards this goal, this paper offers a proof of concept applied to the dedup benchmark from the PARSEC benchmark suite, which is notorious for its high virtualization overhead. We provide an alternative implementation of this benchmark, which suffers negligible virtualization overhead compared to the original, thus increasing performance by up to 45%.