# Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud
## 1 Introduction
EDEM software has been deployed on Rescale's cloud simulation platform for high-performance computations [12]. [PERSON] et al. [13] proposed a tool for the automatic validation of cloud-native applications, which provides insightful suggestions on how to enhance the performance and cloud-native characteristics of the validated applications. However, it is difficult to provide precise guidelines regarding the optimal cloud platform and virtualization technology for each type of research and application [1]. Deployment of scientific codes as software services for data preparation, high-performance computation, and visualization on the cloud infrastructure increases the mobility of users and achieves better exploitation because clouds feature flexible management of resources. Thus, flexible cloud infrastructures and software services are perceived as a promising avenue for future advances in the multidisciplinary area of discrete element method (DEM) applications [14]. However, the cloud SaaS might suffer from severe performance degradation due to higher latencies of networks, virtualization overheads, and other issues [15]. Cloud computing still lacks in terms of case studies and quantitative comparison of performance in the case of specific applications of granular materials and particle technology. Most evaluations of the virtualization overhead and performance of cloud services are based on standard benchmarks [1]; therefore, the impact of the virtualization and processes of the cloud infrastructure on the performance of communication- and computation-intensive MPI-based DEM computations [16] remains unclear. Moreover, performance is a critical factor in deciding whether cloud infrastructures are viable for scientific DEM software. The performance of virtual machines and lightweight containers has already received some attention in the academic literature because they are crucial components of the overall cloud performance. [PERSON] et al. [17] compared the overheads of VMWare Server, Xen,and OpenVZ. For OpenMP runs, the performance of Xen and OpenVZ was close to that obtained on native hardware, but VMware produced a large overhead. [PERSON] and [PERSON] [18] measured the performance of the VMWare virtualization platform for a variety of common scientific computations. The overhead for computation-intensive tasks was around 6%. [PERSON] et al. [19] assessed the performance of the private cloud infrastructure and virtual machines of KVM by testing the CPU, memory, hard disk drive, network, and software services for medical engineering. The measured performance of the virtual resources was close to the performance of the native hardware when measuring only the memory bandwidth and disk I/O. [PERSON] et al. [20] presented an overview of the performance evaluation of virtual machines and Docker containers in terms of CPU performance, memory throughput, disk I/O, and operation speed measurement. [PERSON] et al. [21] also looked at the performance differences of non-scientific software within virtualized and containerized environments. [PERSON] et al. [22] executed genomic workloads on the KVM hypervisor, the Xen para-virtualized hypervisor, and LXC containers. Xen and Linux containers exhibited near-zero overhead. [PERSON] et al. [23] compared the performance of Xen, KVM, and Docker in three different ways: the CPU and memory usage of the host; idleness of the CPU, memory usage, and I/O performance on migrating a large file; and the performance of the web server through JMeter. In [24] the performance of software services developed for hemodynamic computations was measured on Xen hardware virtual machines, KVM-based virtual machines, and Docker containers and compared with the performance achieved by using native hardware. [PERSON] et al. [25] used synthetic benchmarks to empirically evaluate the overheads of bare-metal-, virtual-machine- and Docker-container-based hosts of OpenStack. Docker-container-based hosts had the fastest boot time and the best overall performance, with the exception of network bandwidth.