vScale: Automatic and Efficient Processor Scaling for SMP Virtual Machines

SMP virtual machines (VMs) have been deployed extensively in clouds to host multithreaded applications. A widely known problem is that when CPUs are oversubscribed, the scheduling delays due to VM preemption give rise to many performance problems because of the impact of these delays on thread synchronization and I/O efficiency. Dynamically changing the number of virtual CPUs (vCPUs) by considering the available physical CPU (pCPU) cycles has been shown to be a promising approach. Unfortunately, there are currently no efficient mechanisms to support such vCPU-level elasticity. We present vScale, a cross-layer design to enable SMP-VMs to adaptively scale their vCPUs, at the cost of only microseconds. vScale consists of two extremely light-weight mechanisms: i) a generic algorithm in the hypervisor scheduler to compute VMs' CPU extendability, based on their proportional shares and CPU consumptions, and ii) an efficient method in the guest OS to quickly reconfigure the vCPUs. vScale can be tightly integrated with existing OS/hypervisor primitives and has very little management complexity. With our prototype in Xen/Linux, we evaluate vScale's performance with several representative multithreaded applications, including NPB suite, PARSEC suite and Apache web server. The results show that vScale can significantly reduce the VM's waiting time, and thus can accelerate many applications, especially synchronization-intensive ones and I/O-intensive ones.