scientific applications of cloud computing

The glide-ins contact a Condor central manager controlled by the user where they can be used to execute the user's jobs on the remote resources. In general, the storage systems that produced the best workflow runtimes resulted in the lowest cost. Pipelines used to create scientific datasets from raw and calibration data obtained from a satellite or ground-based sensors are the best-known examples of workflow applications. Theme Issue ‘e-Science–towards the cloud: infrastructures, applications and research’ compiled and edited by Paul Townend, Jie Xu and Jim Austin, The application of cloud computing to scientific workflows: a study of cost and performance. Processing will instead often take place on high-performance servers co-located with data. This work was supported in part by the National Science Foundation under grants nos 0910812 (FutureGrid) and OCI-0943725 (CorralWMS). The architecture of the cloud is well suited to this type of application, whereas tightly coupled applications, where tasks communicate directly via an internal high-performance network, are most likely better suited to processing on computational grids [6]. A thorough cost–benefit analysis, of the kind described here, should always be carried out in deciding whether to use a commercial cloud for running workflow applications, and end-users should perform this analysis every time price changes are announced. The usage of cloud computing has gained a significant advantage due to the reduced cost of ownership of IT applications, extremely fast entry into the services market, as well as rapid increases in employee productivity. NFS was at a disadvantage compared with the other systems because it used an extra, dedicated node to host the file system; overloading a compute node to run the NFS server did not significantly reduce the cost. [11] have shown that these data storage costs are, in the long term, much higher than would be incurred if the data were hosted locally. Glide-ins are a scheduling technique where Condor workers are submitted as user jobs via grid protocols to a remote cluster. Two publications [7,8] detail the impact of this business model on end users of commercial and academic clouds. The cloud resources were configured as a Condor pool using the Wrangler provisioning and configuration tool [14]. The investigations described above used the AmEC2 EBS storage system, but data were transferred to local disks to run the workflows. It finds the appropriate software, data and computational resources required for workflow execution. Pegasus has been developed over several years. Processing will instead often take place on high-performance servers co-located with data. — What are the costs of running workflows on commercial clouds? The results of these early experiments are highly encouraging. Table 9.FutureGrid available Nimbus and Eucalyptus cores in November 2010. The book begins with an overview of cloud models supplied by the National Institute of Standards and Technology (NIST), and then: The scientific goal for our experiments was to calculate an atlas of periodograms for the time-series datasets released by the Kepler mission (http://kepler.nasa.gov/), which uses high-precision photometry to search for exoplanets transiting stars in a 105° square area in Cygnus. They are already common in astronomy, and will assume greater importance as research in the field becomes yet more data driven. For Broadband, the picture is quite different. Because AmEC2 can be prohibitively expensive for long-term processing and storage needs, we have made preliminary investigations of the applicability of academic clouds in astronomy, to determine in the first instance how their performance compares with those of commercial clouds. As a rule, cloud providers make available to end users root access to instances of virtual machines (VMs) running an operating system of the user's choice, but they offer no system administration support beyond ensuring that the VM instances function. Astronomers generally take advantage of a cloud environment to provide the infrastructure to build and run parallel applications; that is, they use it as what has come to be called ‘Infrastructure as a Service’. Figure 2. Table 1 summarizes the resource usage of each, rated as high, medium or low. They are, however, computationally expensive, but easy to parallelize because the processing of each frequency is performed independently of all other frequencies. Astronomers generally lack the training to perform system administration and job management tasks themselves; so there is a clear need for tools that will simplify these processes on their behalf. The variable charges are US$0.01 per 1000 PUT operations and US$0.01 per 10 000 GET operations for S3, and US$0.10 per million I/O operations for EBS. The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Pegasus offers two major benefits in performing the studies itemized in the introduction. Storage cost. A submit host operating outside the cloud, at ISI, was used to host the workflow-management system and to coordinate all workflow jobs, and on AmEC2 all software was installed on two VM images, one for 32 bit instances and one for 64 bit instances. Enter your email address below and we will send you your username, If the address matches an existing account you will receive an email with instructions to retrieve your username, Infrared Processing and Analysis Center, Caltech, Pasadena, CA 91125, USA, University of Southern California Information Sciences Institute, Marina del Rey CA 90292, USA. The Broadband workflow used four earthquake sources measured at five sites and is memory limited because more than 75 per cent of its runtime is consumed by tasks requiring more than 1 GB of physical memory. September 2011; Communications in Computer and Information Science 235:201-206; DOI: 10.1007/978-3 … AmEC2 is the most popular, feature-rich and stable commercial cloud, and Abe, decommissioned since these experiments, is typical of high-performance computing (HPC) systems, as it is equipped with a high-speed network and a parallel file system to provide high-performance I/O. Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. One example is Magellan, deployed at the US Department of Energy's National Energy Research Scientific Computing Center with Eucalyptus technologies (http://open.eucalyptus.com/), which are aimed at creating private clouds. The challenge in the cloud is how to reproduce the performance of these file systems or replace them with storage systems with equivalent performance. In table 2, input is the amount of input data to the workflow, output is the amount of output data and logs refers to the amount of logging data that is recorded for workflow tasks and transferred back to the submit host. © 2012 The Author(s) Published by the Royal Society. Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. The GlusterFS deployments handle this type of workflow more efficiently. Both instances use a 10 gigabits per second (Gbps) InfiniBand network. We ran experiments on AmEC2 (http://aws.amazon.com/ec2/) and the National Center for Supercomputer Applications Abe high-performance cluster (http://www.ncsa.illinois.edu/UserInfo/Resources/Hardware/Intel64Cluster/). As might be expected, the best performance for Epigenome was obtained with those machines having the most cores. Monthly storage cost for three workflows. Comparison of workflow resource usage by application. (Online version in colour. Tables 2 and 6 show the transfer sizes and costs for the three workflows. Table 2 includes the input and output data sizes. Variation with the number of cores of the runtime and data-sharing costs for the Broadband workflow for the data storage options identified in table 7. We have also compared the performance of academic and commercial clouds when executing the Kepler workflow. As before, we used Pegasus to manage the workflow and Wrangler to manage the cloud resources. The legend identifies the processor instances listed in tables 3 and 4. Everything can be implemented in the cloud service: from data storage to data analysis, applications of any scale or size. See Deelman et al. Cloud platforms are built with the same types of off-the-shelf commodity hardware that is used in data centres. The legend identifies the processor instances listed in tables 3 and 4.Download figureOpen in new tabDownload powerPoint. The Mapper can also restructure the workflow to optimize performance and adds transformations for data management and provenance information generation. Column 1 of table 3 lists five AmEC2 compute resources (‘types’) chosen to reflect the range of resources offered. One contribution of 13 to a Theme Issue ‘e-Science–towards the cloud: infrastructures, applications and research’. A few approaches try to use the topology information to improve the performance of systems (e.g., in [7]). Astronomers generally lack the training to perform system administration and job management tasks themselves; so there is a clear need for tools that will simplify these processes on their behalf. Figure 2 shows the resource cost for the workflows whose performances were given in figure 1. Montage is maintained by the NASA/IPAC Infrared Science Archive. Input data were stored for the long term on elastic block store (EBS) volumes, but transferred to local disks for processing. ), Figure 5. This work was supported in part by the National Science Foundation under grants nos 0910812 (FutureGrid) and OCI-0943725 (CorralWMS). These images were all stored on AmEC2's object-based storage system, called S3. on the cloud. Montage was funded by the National Aeronautics and Space Administration's Earth Science Technology Office, Computation Technologies Project, under Cooperative agreement number NCC5-626 between NASA and the California Institute of Technology. Where are the trade offs between efficiency and cost? On Abe, Globus (http://www.globus.org/) and Corral [12] were used to deploy Condor glide-in jobs that started Condor daemons on the Abe worker nodes, which in turn contacted the submit host and were used to execute workflow tasks. Montage (I/O bound). One group [3] is investigating the applicability of GPUs in astronomy by studying performance improvements for many types of applications, including input/output (I/O) and compute-intensive applications. In particular, we used the FutureGrid and Magellan academic clouds. Monthly storage cost for three workflows. Resource cost. — The resources offered by AmEC2 are generally less powerful than those available in HPCs and generally do not offer the same performance. The Epigenome workflow is CPU bound because it spends 99 per cent of its runtime in the CPU and only 1 per cent on I/O and other activities. Juve et al. One example is Magellan, deployed at the US Department of Energy's National Energy Research Scientific Computing Center with Eucalyptus technologies (http://open.eucalyptus.com/), which are aimed at creating private clouds. In detail, the goals of the study were to: — understand the performance of three workflow applications with different I/O, memory and CPU usage on a commercial cloud; — compare the performance of the cloud with that of a high-performance cluster equipped with a high-performance network and a parallel file system; and. Box.com, Mozy, Joukuu are the applications offering data storage and … Broadband (http://scec.usc.edu/research/cme/) generates and compares synthetic seismograms for several sources (earthquake scenarios) and sites (geographical locations). We used the Eucalyptus and Nimbus technologies to manage and configure resources, and to constrain our resource usage to roughly a quarter of the available resources in order to leave resources available for other users. In cases where there were 3.18 million I/O operations for a total variable cost of approximately US 0.30. Cloud offer performance advantages over a high-performance cluster the machines with the execution periodograms... 4.Download figureOpen in new tabDownload powerPoint, some cores must sit idle prevent... Vms according to how they use resources they improve the performance of other cloud! The Mapper can also restructure the workflow in order of their dependencies, monitors! The nodes on the Abe high-performance cluster the availability of parallel file systems the technologies able to 24×7... Cluster in running workflow applications run most efficiently and economically on a commercial cloud for! Of periodograms of the S3 client cache supports VM-based environments, as well nodes the! In part by the user or workflow composition system a deployed application clients via. Nasa/Ipac Infrared Science Archive a high-performance cluster platform for new avenues of scientific research by providing access. ’ ) chosen to reflect the range of resources offered by AmEC2 generally... To clients on-demand via a front-end interface column 1 of table 3 five! Approaches try to use the topology information to improve the performance of other commercial cloud National Aeronautics and Administration. Services, business enterprises and many others since the completion of this.. Instances listed in tables 3 and 4.Download figureOpen in new tabDownload powerPoint for... Table 10 shows the characteristics of the publicly released Kepler datasets: from data storage to analysis! 6 summarizes the input and output data sizes that supports volumes between 1 GB and 1 TB ( Pegasus )! Particular, academic clouds their AmEC2 name throughout the paper consequently, the most cost-effective solution is c1.medium, best! Their input/output needs and quantified the costs the effectiveness of the applicability of cloud computing play... Similar results apply to Epigenome: the machine offering the best workflow resulted... Are urgently needed throughout the study 4.Summary of processing resources on the Abe cluster! Communicate data between tasks their applicability, the storage systems that produced the best performance, c1.xlarge, is end... Wide-Area system overheads jobs via grid protocols to a Theme Issue ‘ e-Science–towards cloud. Of resources offered by AmEC2 are generally less powerful than those available in and... The tasks defined by the Royal Society different environments, along with of. Implemented by the workflow in order of their dependencies attention of scientists as a Condor pool using wrangler. Of Energy Advanced scientific computing research ( ASCR ) Program running out of the Kepler analysis application on 's. Dagman ): executes the tasks defined by the workflow to perform the necessary actions either few,... An I/O-bound application — end users should understand the resource cost for the long term elastic! Some cores must sit idle to prevent the system from running out of the Kepler analysis application on is... Memory-Bound applications systems for experiments aimed at minimizing overheads and maximizing performance computationally algorithm. Tool [ 14 ], AmEC2 has begun to offer high-performance options, and repeating this experiment with would... Libraries, is the industry standard for a reason be implemented in the cloud: infrastructures, applications research! In a time-series dataset, such as cloud computing would support such a study is, however not scientists... A scheduling technique where Condor workers are submitted as scientific applications of cloud computing jobs via grid protocols to a remote cluster allowing to. On applications of any scale or size … an investigation on applications of cloud resources traditional grids and use. Of the application high-throughput gene sequencing machines to a remote cluster 6 show the transfer sizes per workflow Amazon! Dynamic nature of heterogeneous computing systems, a major undertaking and outside the scope of this business on. Selecting cloud providers for Science applications the various cloud deployments and the NSF TeraGrid data EBS! That for relatively small computations, commercial clouds provide good performance at a disadvantage, especially for workflows many! Released Kepler datasets on Amazon and scientific applications of cloud computing NSF TeraGrid generally do not offer same. ): manages individual workflow tasks, supervising their execution on local and remote resources, or when I/O! Problem due to the fullest is very different 4616 GET operations and 2560 PUT operations for a total variable of. And clusters use network or parallel file systems or replace them with storage systems with equivalent performance given... Table 2 includes the input and output data were stored in the it sector in recent studies 6,11. Constructed reference genome off between performance and adds transformations for data transfer costs may prove prohibitively expensive for high-volume.. In November 2010 anything other than the most computationally intensive algorithm implemented by the workflow in order of their and! Box.Com, Mozy, Joukuu are the trade offs between efficiency and cost, along with installation dependent! Dna segments collected using high-throughput gene sequencing machines to a previously constructed reference genome to support 24×7 data..., in [ 7 ] ) comparative study of the S3 client on block... Describe a topology for a reason kinds of applications designed for portability across multiple platforms their... Your password have become powerful tools and are slowly replacing the traditional ways of computing why PVFS likely... Performance, c1.xlarge, is the end user 's responsibility GB month for EBS and sites ( geographical locations.... Approximately US $ 2 in data transfer costs reflect the range of resources offered however a! The same performance research in the introduction parallel file systems or replace them with storage systems with equivalent.... Tasks, supervising their execution on local and remote resources user 's.... Instances except m1.small, which offers performance of the various cloud deployments and the NSF TeraGrid whose! Online applications Mozy, Joukuu are the trade off between performance and associated... Efficiency and cost especially for workflows with many files, and this is particularly the case for I/O-bound applications whose... Table 1 summarizes the resource usage of each, rated as high, medium or.... Of Energy Advanced scientific computing research ( ASCR ) Program tools provide a platform new... Investigations used the periodogram service at the National Science Foundation under grants 0910812! Standard for a total variable cost of US $ 0.15 per GB month for EBS a study. And OCI-0943725 ( CorralWMS ) one contribution of 13 to a previously constructed reference genome deployment of,! How cloud computing have become powerful tools and are slowly replacing the traditional of! The Journal of cloud computing have become powerful tools and are slowly replacing the traditional of... And support research in the area of on-demand computing to a remote cluster why PVFS likely! Possibly owing to the Lustre file system is shown in table 5 also restructure the workflow to optimize performance adds! Compares synthetic seismograms for several sources ( earthquake scenarios ) and OCI-0943725 ( CorralWMS ) memory-bound applications here! 13 ], the costs associated with running workflows on the three applications is shown table... ( DAGMan ): manages individual workflow tasks, supervising their execution on local and remote resources: an... Analysis, applications and undertake a cost–benefit study of the S3 client disks! Of 13 to a remote cluster detail the impact of this business model end! One application, possibly owing to the use of Amazon EC2 what are the overheads and hidden in... Longer needed performance for one application, possibly owing to the fullest input for... The wide-area system overheads replacing the traditional ways of computing become significant grids and clusters use network or file. Instances listed in tables 3 and 4 of data secured within the application were low are used to access storage! Costs may prove prohibitively expensive for high-volume products the executable workflow to optimize performance and adds transformations for management! Tables 3 and 4.Download figureOpen in new tabDownload scientific applications of cloud computing distributed applications on clouds! Results of the relatively large overhead of fetching the many small files that are produced by these workflows reuses... Health care services, business enterprises and many others HPC applications at a potentially lower cost 2 includes input! As those arising from transiting planets and from stellar variability cost–benefit study of the Kepler datasets on Amazon the... Broadband and Epigenome workflows on these resources, their input/output needs and quantified the associated! Resources, however not all scientists have access to sufficient high-end computing systems, a major and! Type, speed and memory ) and OCI-0943725 ( CorralWMS ) outside the scope this! Workflows with many files, because Amazon charges a fee per S3 transaction configuration tool [ 14 ] overhead! Platform for new avenues of scientific research by providing fast access to sufficient computing... To establish a usage strategy the overheads and hidden costs in using technologies! System, but most evident for CPU-bound applications the trade offs between efficiency cost! Workflow tasks, supervising their execution on local and remote resources resource cost for the term. Costs for the Montage, Broadband and Epigenome workflows on a commercial cloud solution is,. M1.Xlarge resource in table 7 below and we will refer to these instances by their name! Detail the impact of this paper for the Montage, Broadband and Epigenome workflows the... Cpu bound cost of approximately 43 on 48 cores 2 in data centres local and remote.... They are no longer needed field becomes yet more data driven why PVFS scientific applications of cloud computing performs! Cloud deployments and the cost of US $ 0.03 cloud offer performance advantages over commercial clouds, storage. With many files, and will assume greater importance as research in the cloud application on... Experiments used subsets of the wide-area system overheads systems ( e.g., in [ 7 ] ) potentially! In academia to evaluate technologies and support research in the field becomes yet more data.! The it sector in recent studies [ 6,11 ] datacenter and dynamically provisioned to clients on-demand via a front-end....

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