Understanding the Performance and Potential of Cloud Computing for Scientific Applications

Abstract

Commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems. Cloud computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work provides a comprehensive evaluation of EC2 cloud in different aspects. We first analyze the potentials of the cloud by evaluating the raw performance of different services of AWS such as compute, memory, network and I/O. Based on the findings on the raw performance, we then evaluate the performance of the scientific applications running in the cloud. Finally, we compare the performance of AWS with a private cloud, in order to find the root cause of its limitations while running scientific applications. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud in terms of both raw performance and scientific applications performance. Furthermore, we evaluate other services including S3, EBS and DynamoDB among many AWS services in order to assess the abilities of those to be used by scientific applications and frameworks. We also evaluate a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.

Automating NEURON Simulation Deployment in Cloud Resources

“…Typically, there is no waiting queue for cloud servers and no layer between the user and the cloud server, though the so–called ‘bare–metal’ versions, which allow the user exclusive access to hardware, may require reservations. 4 Public clouds and private clouds both provide cloud services, but private clouds tend to have better performance characteristics (Sadooghi et al 2015). …”

“…Many scientific communities have embraced or investigated the use of cloud resources for their research, including particle physics (Sadooghi et al 2015), astrophysics (Smith 2011), high-energy physics (Segal et al 2010; Taylor et al 2015), computational chemistry (Thackston and Fortenberry 2015b), chemical modeling for high–throughput drug discovery (Moghadam et al 2015), bioinformatics (Hanson et al 2014), medical imaging (Kagadis et al 2013), geophysics (Mudge et al 2011), social sciences (Wittek and Rubio-Campillo 2012), geochemistry (Huang et al 2014), genomic analysis (Ban et al 2015), and various projects at the Department of Energy (Yelick et al 2011). …”

“…In this document we refer to Amazon Web Services as “AWS” and the Amazon EC2 cloud as “Amazon EC2” or “EC2” in accordance with current practice (Belgacem and Chopard 2015; Kaminski and Szufel 2015; Sadooghi et al 2015; Yoginath and Perumalla 2015). …”

Job placement advisor based on turnaround predictions for HPC hybrid clouds

“…In addition, the aim has been to evaluate the performance gap between cloud and on-premise resources [9][10][11][12]. Even though cloud typically has slower internal network speeds than onpremise resources, bursting jobs to the cloud can still provide better overall performance in overloaded environments.…”

Build and Evaluate a Free Virtual Cluster on Amazon Elastic Compute Cloud for Scientific Computing

“…Scientific computing has been dependent on High Performance Computing (HPC) and parallel processing, since running large simulation requires a huge amount of computing resources. However, not all scientific researchers have an access to sufficient high-end computing systems [2]. Moreover, some scientific researchers in developing country even do not have any cluster at all.…”