Cloud Computing Environment for Engineering and Business Education

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<ul><li><p>Cloud computing environment for engineering </p><p>and business education </p><p>Gabriel Raicu1, a, Alexandra Raicu2, b 1Constanta Maritime University, Romania, Department of Economic Engineering in Transports, </p><p>Mircea cel Batran Street, No. 104, Constanta, 900663, Romania </p><p>2Constanta Maritime University, Romania, Department of General Engineering Sciences, Mircea </p><p>cel Batran Street, No. 104, Constanta, 900663, Romania </p><p>agabriel.raicu@cmu-edu.eu, </p><p>balexandra.raicu@cmu-edu.eu </p><p>Keywords: Cloud computing, simulation environments, engineering, capacity planning, KVM, OpenMX. </p><p>Abstract. The authors present the development of a scientific cloud computing environment </p><p>(SCCE) for engineering and business simulations that offers high performance computation </p><p>capability. The software platform consists of a scalable pool of virtual machines running a UNIX-</p><p>like (Linux) or UNIX-derivative (FreeBSD) operating systems using specialised software based on </p><p>modelling engineering processes and focused on business training and predictive analytics using </p><p>simulations. The use of advanced engineering simulation technology allows engineers to understand </p><p>and predict the future performance of complex structures and systems designs which can be </p><p>optimized to reduce risk, improve performance or enhance survivability. A key component of cloud </p><p>computing in Universities as well as in other research centers: they can share computing resources </p><p>beyond their technical capabilities. With cloud computing, this allows them all to have access to </p><p>large scales processing power based on KVM (Kernel based Virtual Machine). Our solution </p><p>provides a more productive approach: a full scale virtualised computer with scalable storage space </p><p>and instantly upgradable processing capability. It has more flexibility than other network computing </p><p>systems and saves precious research time and money. Unlike the existing systems, the scientific </p><p>community can receive support from a large number of specialists who may contribute by in a </p><p>collaborative way. </p><p>Introduction </p><p>A recent survey carried out by Peer 1 Network Enterprises found that of the 88% of key decision-</p><p>makers that do not use cloud computing, 39% said it was because they don't know enough about it. </p><p>So, for those who are still in the dark, what is cloud computing anyway? </p><p>Cloud computing enables users to work on very powerful virtual comput-ers/store files and </p><p>software remotely, rather than on a hard drive or server at their office. The fact is many people may </p><p>already be using cloud compu-ting without realizing it, whether through work or personal use [1]. </p><p>Some examples of cloud computing applications include software as a ser-vice (SaaS), Customer </p><p>Relationship Management, File storage, File synchronization and file back-up. It's now possible for </p><p>businesses to have their own private cloud, which incorporates specific services and is only </p><p>accessible to specific people. </p><p>Business simulations allows decision makers to establish a common understanding for the </p><p>strategic values, change key factors and study how strategies and decisions are made. As an </p><p>additional value, on the cloud you can test decisions and strategies before they are implemented and </p><p>to see problems before they actually occur. The hybrid parallelization is also supported which is </p><p>suitable for virtual cluster consisting of multicore virtual machines placed on several distributed </p><p>hardware nodes. Each of the cluster nodes can be accessed by remote operators to modify the </p><p>simulation job or to schedule another scientific experiment. </p><p>Advanced Materials Research Vol. 837 (2014) pp 651-656Online available since 2013/Nov/08 at www.scientific.net (2014) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMR.837.651</p><p>All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP,www.ttp.net. (ID: 142.103.160.110, University of British Columbia, Kelowna, Canada-21/11/14,14:14:47)</p><p>http://www.scientific.nethttp://www.ttp.net</p></li><li><p>With cloud computing [2], this allows them all to have access to large scales processing power </p><p>based on KVM (Kernel based Virtual Machine) [3]. Several of the authors papers address the </p><p>concept of Virtual Learning Computing Center and distributed applications. Some of the authors </p><p>projects are related to on-line educational developing activity and simulation for educational </p><p>purposes. Other authors rely on Amazon Elastic Compute Cloud (EC2) [4] which is a web service </p><p>that provides resizable compute capacity in the cloud. </p><p>Our solution provides a more productive approach: a full scale virtualised computer with scalable </p><p>storage space and instantly upgradable processing capability. It has more flexibility than other </p><p>network computing systems and saves precious research time and money. The platform was </p><p>optimised to run simulations software [5]. Not only conventional diagonalization schemes are </p><p>provided for clusters, but also linear scaling and a low-order scaling methods are supported as value </p><p>solver. The cluster is also adaptable to other related scientific tasks. Unlike the existing systems, the </p><p>scientific community can receive support from a large number of specialists who may contribute by </p><p>in a collaborative way. </p><p>The benefits of cloud computing </p><p>As long as they can get on the Internet, staff can access information from home, on the road, </p><p>from clients offices or even from a smartphone such as a BlackBerry or iPhone. Staff can also work </p><p>collaboratively on files and documents, even when they are not physically together. Documents can </p><p>simultaneously be viewed and edited from multiple locations. </p><p>Cloud computing can be very quick and easy to get up and running. There is no need to buy and </p><p>install expensive software because it is all ready installed online remotely and you run it from there, </p><p>not to mention the fact that many cloud computing applications are offered free of charge. The need </p><p>to pay for extensive disk space is also removed. With cloud computing, you subscribe to the </p><p>software, rather than buy-ing it outright. This means that you only need to pay for it when you need </p><p>it, and it also offers flexibility, in that it can be quickly and easily scaled up and down according to </p><p>demand. </p><p>A major advantage of using cloud computing (figure 1) for many companies is that because it is </p><p>online, it offers virtually unlimited storage compared to your servers and hard drive limits. Needing </p><p>more storage space does not cause issues with your computer upgrades and equipment, usually all </p><p>you need to do is increase your monthly fee slightly for more data storage. </p><p>Fig. 1 Cloud Technology </p><p>Services of cloud computing </p><p>When we refer about Services of the cloud computing we can talk about Infrastructure, Platform </p><p>and Software. </p><p>652 Modern Technologies in Industrial Engineering</p></li><li><p>IaaS (Infrastructure as a Service): Offers infrastructure on demand. The infrastructure can be </p><p>anything from storage servers to applications to operating systems. Buying infrastructure or renting </p><p>it out in traditional models can be very expensive. When you opt for IaaS, you save a lot on </p><p>expenses, space, and personnel required to set up and maintain the infrastructure. The cloud service </p><p>provider takes care of setting up and maintaining the infrastructure. </p><p>PaaS (Platform as a Service): Offers a platform to clients for different purposes. For example, a </p><p>platform developers to build, test, and host applications that can be accessed by the end users. The </p><p>end users may or may not know that the application is hosted on the cloud. As mentioned earlier, </p><p>the storage space for user data may be increased or decreased per the requirement of the </p><p>applications. As with the SaaS, you do not need to build the platform. </p><p>SaaS (Software as a Service): This is the most popular form of cloud services. The service </p><p>provider offers a software to support the service on offer. The software is built by the service </p><p>provider while the end users can configure it to suit their needs. The clients (end users) however, </p><p>cannot change or modify the software. It is basically a backup service that offers software to help </p><p>people back up their data. Thus, you can use the service without actually having to code or buy the </p><p>software [6]. </p><p>Cloud Computing at Constanta Maritime University </p><p>In the last eight years CMUConstanta Maritime Universityhas invested significant funds in </p><p>developing a cloud/grid computing for research in fundamental scientific fields and the </p><p>development of new techniques in naval operations. </p><p>Cloud features at Constanta Maritime University are (figure 2): </p><p> Hundreds of TB Core Storage ZFS with dual or triple parity check; </p><p> Hundreds of GB RAM for Virtual Machines; </p><p> Dozens of Xeon QCE5430/Xeon 8CX7560 computing cores; </p><p> Gluster/Lustre/HA redundant data storages; </p><p> Multiple Distributed nodes, ready for KVM Virtual Machines or OpenVZ Containers; </p><p> Ability to run every type of Linux/BSD/Windows OS in 32/64 bit envi-ronment; </p><p> Ability to emulate other CPU architectures. </p><p>Fig. 2 Cloud at CMU </p><p>Addressing the needs of extended computing at CMU: </p><p> Reduced Cost: Cloud technology is paid incrementally, saving organizations money; </p><p> Increased Storage: Organizations can store more data than on private computer systems; </p><p> Highly Automated: No longer do IT personnel need to worry about keeping software up to </p><p>date; </p><p> Flexibility: Cloud computing offers much more flexibility than past computing methods; </p><p>Advanced Materials Research Vol. 837 653</p></li><li><p> More Mobility: Employees can access information wherever they are, rather than having to </p><p>remain at their desks; </p><p> Allows IT to Shift Focus: No longer having to worry about constant server updates and other </p><p>computing issues, government organizations will be free to concentrate on innovation; </p><p> Green Computing: As cloud computing can always be used to reprovisioning of resources, </p><p>when you need to expand, you need not buy the infrastructure to increase the carbon emissions by </p><p>way of using more electricity to cool off the computer resources; </p><p> Security concerns: Though people doubt cloud computing, clouds tend to be more secure </p><p>than the traditional business models. Clouds offer realtime backup which results in less data loss. In </p><p>case of outage, your customers can use the backup servers that sync with the main ones as soon as </p><p>they are up. Your business gets maximum uptime without any loss of data during the transitions. </p><p>Other than this, clouds are less prone to hacks and DDoS attacks as people dont know the </p><p>whereabouts of your data; </p><p> The Cloud Gives New Value to Old Hardware and Software: You can perform outstanding </p><p>CPU intensive activity on remote hardware even from ordinary, old desktop or laptop; </p><p> Faster Deployment: Lower Costs, faster implementation. </p><p>In the figure 3 we present a CMU cloud desktop interface. </p><p>Fig. 3 CMU cloud desktop interface </p><p>Remote session sample on working account: Virtualization type is KVM, Virtual Machine </p><p>Account for student educational &amp; research activity with the 6 Xeon QCE5430 CPU/6GB RAM. </p><p>For example, OpenMX (Open source package for Material eXplorer) is a software package for </p><p>nano-scale material simulations based on density functional theories (DFT), norm-conserving </p><p>pseudopotentials, and pseudo-atomic localized basis functions. The code is designed for the </p><p>realization of large-scale ab initio calculations on parallel computers, and thereby we expect that </p><p>OpenMX can be a useful and powerful tool for nano-scale material sciences in a wide variety of </p><p>systems such as bio-materials, carbon nanotubes, magnetic materials, and nanoscale conductors [7]. </p><p>Considerable functionalities are available for calculations of physical properties such as </p><p>magnetic, dielectric, electric transport properties as listed above. Not only conventional </p><p>diagonalization schemes are provided for clusters, molecules, slab, and solids, but also linear </p><p>scaling and a low-order scaling methods are supported as eigenvalue solver. The execution </p><p>environment is unix and linux, figure 4. </p><p>All work arrays in the program codes are dynamically allocated with the minimum memory size </p><p>required by an input file. For large-scale calculations parallel execution by MPI or OpenMX is </p><p>654 Modern Technologies in Industrial Engineering</p></li><li><p>supported for parallel machines. The hybrid parallelization by OpenMP/MPI is also supported </p><p>which is suitable for PC cluster consisting of multicore processors. For the execution of OpenMX, </p><p>you are required to possess pseudo-atomic basis orbitals and pseudopotentials. </p><p> Fig. 4 CMU cloud desktop applications </p><p>Conclusion </p><p>The cloud computing environment can be accessed globally using mobile devices or standard </p><p>desktops. Researchers can operate the cloud simultaneously as scientific virtual teams and can </p><p>collaborate in scenario development. The scalable infrastructure allows also simultaneously </p><p>observation during experiments, figure 5. </p><p>Unlike the existing systems, the scientific community can receive support from a large number of </p><p>specialists who may contribute by in a collaborative way. </p><p> Fig. 5 OpenMX cluster results </p><p>Advanced Materials Research Vol. 837 655</p></li><li><p>Using the platform in conjunction with OpenMX we can provide a large string of features and </p><p>capabilities as such: total energy and forces by cluster, band, O(N), and low-order scaling methods, </p><p>local density approximation (LDA, LSDA) and generalized gradient approximation (GGA) to the </p><p>exchange-correlation potential, norm-conserving pseudopotentials, variationally optimized pseudo-</p><p>atomic basis functions, fully and scalar relativistic treatment within pseudopotential scheme, non-</p><p>collinear DFT, constraint DFT for non-collinear spin and orbital orientation, collinear LDA+U and </p><p>non-collinear LDA+U methods, macroscopic polarization by Berry's phase, Divide-conquer (DC) </p><p>method, generalized DC method, and Krylov subspace method for O() eigenvalue solver, simple, </p><p>RMM-DIIS, GR-Pulay, Kerker, and RMM-DIIS with Kerker's metric charge mixing schemes, </p><p>exchange coupling parameter, effective screeing medium method, scanning tunneling microscope </p><p>(STM) simulation, nudged elastic band (NEB) method, full and constrained geometry optimization, </p><p>electric transport calculation by a non-equilibrium Green's function (NEGF) method, construction of </p><p>maximally localized wannier functions, NVE ensemble molecular dynamics, NVT ensemble </p><p>molecular dynamics by a velocity scaling and the Nose-Hoover methods, Mulliken, Voronoi, and </p><p>ESP fitting analysis of charge and spin densities, analysis of wave functions and electron (spin) </p><p>densities, dispersion analysis by the band calculation, density of states (DOS) and projected DOS, </p><p>etc. </p><p>Scientific cloud computing environment (SCCE) may evolve to future developments on virtual </p><p>computing platforms. </p><p>References </p><p>[1] K. Jorissen, F. D. Vila, J. J. Rehr, A high performance scientific cloud computing environment </p><p>for materia...</p></li></ul>

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