Tps: An Efficient Vm Scheduling Algorithm For Hpc Applications In Cloud

Cloud computing platforms are becoming viable alternative for running high performance parallel applications. However, when running these applications in cloud platforms, VMs (virtual machines) are easily affected by the synchronization latency problem which leads to serious performance degradation. There are two main reasons. The first is that a host is unaware of the synchronization requirements of the guest OS. The second is that the synchronization requests of VMs on a physical host are unknown to VMs on the other physical host. It is a great challenge to mitigate the negative influence of virtualization on synchronization and accelerate the synchronization response of HPC applications. In this paper, we propose a two -phase synchronization-aware (TPS) scheduling algorithm to solve the problem above. The TPS algorithm takes both intra-VMs' and inter-VMs' synchronization demands into consideration. Spin-locks and network packets are used as the metrics to detect the synchronization demands of VMs and VMs are scheduled based on spinlock-aware and communication-aware strategies. The algorithm is implemented on the base of KVM and experiments are conducted in a cluster environment. The experimental results show that our TPS algorithm obtains a better performance for HPC applications and reduces negative impacts on non-HPC applications simultaneously. Therefore, our approach is an effective solution to the HPC synchronization issues in cloud platforms.