An Grid Service Module for Natural Resource Managers
|
|
- Brendan Watson
- 8 years ago
- Views:
Transcription
1 An Grid Service Module for Natural Resource Managers Dali Wang 1, Eric Carr 1, Mark Palmer 1, Michael W. Berry 2 and Louis J. Gross 1 1 The Institute for Environmental Modeling 569 Dabney Hall, University of Tennessee, Knoxville, TN [wang, carr, palmer, gross]@tiem.utk.edu 2 Department of Computer Science 203 Claxton Complex, University of Tennessee, Knoxville, TN berry@cs.utk.edu Abstract: This article presents the motivations for developing a grid service module for natural resource managers. Built on grid middleware, the grid service module allows natural resource managers to transparently use a high performance ecosystem modeling package (Across Trophic Level System Simulation) without requiring knowledge of the underlying computational issues. From a software development perspective, this novel grid service module can be deployed by researchers across multiple disciplines to allow decision makers or the public to exploit fully functional scientific computation on grids. Key words and phrases: grid service module, grid computing, distributed computation, software architecture, ecosystem modeling. 1. Introduction During the past two decades, a variety of ecological models were developed as useful tools natural resource management. Ecological models can summarize information on the natural resource, determine where gaps exist, extrapolate across the gaps, and simulate various scenarios to evaluate outcomes of natural resource management decisions [1]. However, ecological models are not effectively used in natural resource management due to the lack of training and education, integration of existing models, and development of new models [2]. We argue that for new applications of modeling to be effective, new computational methodologies must be developed to enable users to readily carry out complex simulations without extensive additional training. In reality, natural resource managers typically have very little experience with high performance computing. Therefore, as ecological models become more complex, the computational demands make it prudent to have tools available to carry out the simulations and associated visualization without requiring that the managers have extensive background in computational science. Fortunately, developments in high-performance networks, computers, and information services make it feasible to incorporate remote computing and information resources into local computational environments. Recently, grid computing [3] emerged as one of the most important new developments in building the infrastructure for computational science. In this article, we describe a grid service module developed to deliver high performance ecosystem modeling capabilities (Across Trophic Level System Simulation (ATLSS) [4]) to natural resource managers with only limited knowledge on computational science. 1
2 The Across Trophic Level System Simulation (ATLSS) is an ecosystem modeling package designed to assess the effects on key biota of alternative water management plans for the regulation of water flow across the Everglades landscape. The immediate objective of ATLSS is to provide quantitative, predictive modeling software for guiding the South and Central Florida restoration effort. The long-term goals are to aid in understanding how the biotic communities of South Florida are linked to the hydrologic regime and other abiotic factors, and to provide a predictive tool for both scientific research and ecosystem management. 2. Computational Platform and Grid Middleware The computational platform used is the Scalable Intracampus Research Grid (SInRG) [5], supported by the National Science Foundation. The SInRG project deploys a research infrastructure on the University of Tennessee, Knoxville campus that mirrors the underlying technologies and the interdisciplinary research collaborations that are characteristic of the emerging national technology grid. SInRG's primary purpose is to provide a technological and organizational microcosm in which key research challenges underlying grid-based computing can be addressed with better communication and control than wide-area environments usually permit. A variety of grid middleware were installed on SInRG, among which NetSolve [6] and Internet Backplane Protocol (IBP) [7] were deployed to create a grid service module designed to deliver high performance ecosystem modeling capability to natural resource managers at several federal and state agencies in Florida. NetSolve is a remote procedure call (RPC) based middleware system, which allows users to access additional hardware and/or software resources remotely. There are three main components in a NetSolve system: agent, server and remote users. NetSolve tracks which machines have computational servers running and with which computational service (software) they are provisioned. It also tracks the workload of each NetSolve server to yield the best choice of server for a given job request. In other words, NetSolve takes care of the details of finding a machine on which to execute the computational task. NetSolve also provides extensible service creation via Problem Definition Files (PDFs), to generate wrappers for the user s code. After compilation, the codes defined by PDFs become NetSolve services which can be enabled by server instances. IBP is middleware for managing and using remote storage. It uses small ASCII based files (called exnodes) to support global scheduling and optimization of data movement and storage in distributed systems and applications. In an IBP system, a large data file can be separated into multiple parts and stored on different IBP servers, (an exnode is created for each data storage location). In addition, multiple copies of data can be stored in the IBP system, therefore, the data integrity and reliability of data transmissions can be enhanced by a multi-threaded submission and retrieval process. 3. Design and Implementation Figure 1 presents a simplified view of the grid service module for natural resource managers based on NetSolve and IBP. It contains four major components: a dedicated web interface, a job scheduler, a simulation moderator, and a result repository. 2
3 Figure 1: Architecture of the Grid Service Module The web interface provides a common gateway for users to specify simulation inputs and launch multiple tasks potentially by different users at the same time. It also checks user identifications and performs process authorization. The job scheduler, containing an IBP client and a NetSolve intelligent agent, accepts computation requests from users via the web interface and allocates appropriate ATLSS models and necessary data storage for the job (remote) executions. The simulation moderator is built on IBP and NetSolve servers where the ATLSS models have been configured as NetSolve services and model input/output are managed by IBP servers. The result repository is a database to store simulation results, which can be reviewed and reused by authorized users in future analysis. 3.1 Web Interface Various stakeholders/agencies have expressed strong interest in a single web interface for accessing, running, and retrieving data from a variety of ecological models. The only requirements for natural resource managers to use the grid service module are an Internet access and a web browser. In addition, the detailed information and model parameterizations associated with the complex ecological models necessitated that only limited functionality should be provided through the web interface. Users are given, within limits, the choice of particular models and can parameterize them as appropriate based upon their experience and the requirements of their agency. This provides different users an intuitive process to apply ecological models for particular species, conditions or spatial domains. Figure 2 illustrates the password protected web interface to access different ATLSS models. Each model allows users to vary simple simulation control parameters such as simulation time and input conditions such as hydrological scenarios. Through this web interface, users can launch parallel jobs on SInRG resources. After a simulation (which may take hours of CPU time on a high-performance computer [8,9]) is complete, the web interface issues an notification to the user. In addition, the web interface acts as the gateway for users to access a database (result repository) in which results from 3
4 Figure 2: Screenshot of the ATLSS web interface. previous simulations have been stored. Users also have access to a separate visualization and analysis tool [10] built in a geographic information system framework (ESRI ArcView). 3.2 Computational Resource Allocation and Remote Execution Technically speaking, two main functionalities are implemented in the grid service module: one is networked computational resource allocation and remote execution; the other is network storage. This section focuses on the computational resource allocation and remote execution based on NetSolve (networked storage issues are addressed in the following section). In the grid service module, the job scheduler contains a NetSolve agent. The simulation moderator incorporates the functions of NetSolve servers. The ecological models in ATLSS are preconfigured as NetSolve services at compile time (through Problem Definition Files), shown in Figure 3. When NetSolve servers register themselves and their services with the NetSolve agent, the job scheduler obtains all necessary information on the ATLSS simulation capability. An ecological model can be installed on multiple NetSolve servers, taking account of different architectural features. Also, depending on the code, the ecological model can be compiled on Windows PC, MAC and Unix based systems and report to the NetSolve agent within the job scheduler. From this standpoint, the grid service module provides the ability to harness diverse machine architectures to work together on a single computational task (heterogeneous computing). Once the job scheduler takes a job request from a user through the web interface, it will use its NetSolve agent to find a best NetSolve server within the simulation moderator based on service availability and machine workload. Next, the job request is shipped to the NetSolve server for processing. The simulation moderator contains a set of problem definition scripts to initialize the computational environment, prepare the model input and then launch the model on the computer where the NetSolve service exists. For example, if a NetSolve service must handle a message-passing interface (MPI) [11] 4
5 based model, a problem definition script will be used to initialize the MPI environment and determine the number of processes for parallel execution. There are several advantages to using this framework: 1) Computational workload balancing is achieved across the entire NetSolve organization, since all jobs are scheduled through the centralized, intelligent job scheduler; 2) Security of the system is enhanced since the users are insulated from actual software, data as well as not given the direct access to the high performance computational facilities; 3) Users can take advantage of the high performance computation facilities without extensive knowledge of computational science. Figure 3: ATLSS Installation in the NetSolve Organization 3.3 Network-Based Storage and Data Transmission A difficulty in using NetSolve for ecological modeling is the limited capability NetSolve supports for transporting large amounts of data over the network. For this reason, IBP was adopted to provide efficient data transport capability. In the grid service module, IBP exnodes are used as transfer keys through the NetSolve system to establish a novel way to send/receive large files to/from remote computational facilities, without requiring direct user access to those machines. Thus, IBP allows the simulation moderator to allocate and schedule storage resources as part of its resource brokering, which in turn leads to much improved performance, and enables fault-tolerance when resources fail or are revoked. As an example, we use a spatially explicit species index model (SESI) [12] to show the typical data flow in the grid service module (see Figure 4). The SESI model input includes a landscape map of South Florida at a 500-m scale of resolution, two hydrological scenarios over several decades, as well as a set of control parameters that specify model assumptions regarding the spatial pattern of wading birds foraging rules over the landscape of South Florida. 5
6 Figure 4: Data Flow of an Ecological Model in the Grid Service Module. (Solid black arrows represent model data flow and dashed gray arrows represent flow of exnodes) Figure 5: Sample Model Output of ATLSS SESI model for Long-legged Wading Birds Figure 4 shows the typical data flow in the grid service module. Once a user (natural resource manager) inputs control parameters (such as scenario name, simulation time, etc.) and submits a job request, these parameters are sent to the job scheduler. The job scheduler then executes four tasks: 6
7 1. assembles all model input data (including landscape map, and water depth distribution for 35 years, etc.); 2. determines the locations of data storage (represented by two exnodes, one for model input, one for model output) and computational facilities (represented by NetSolve server); 3. launches an IBP_upload operation to move the model input into an IBP file server monitored by the simulation moderator; and 4. passes the exnode information to the simulation moderator via the connection between its NetSolve agent and the remote NetSolve server. After receiving the job request from the job scheduler, the simulation moderator uses a Problem Definition Script to download the model input from the IBP File Server, initialize the computational environment, launch the computation and upload the model result back to the IBP File Sever. Eventually, the job scheduler is notified of job completion and issues an IBP_download operation to deliver the model output to the result repository and send a notification to the user via . The total size of input files in this case is around 0.5 GB. An example output of the SESI model is shown in Figure 5, including a visual representation of the landscape with colorcoded values assigned to each cell and a time series of the mean overall index attained each year under each hydrologic scenario. The index value (ranging from 0 to 1) reflects the relative potential for appropriate foraging conditions. 4. Summary The grid service module presented in this article, utilizing the grid middleware NetSolve and IBP, is the first time (based on our knowledge and experiences) a computational grid has been applied to a natural resource management problem. Natural resource agencies typically have very limited access to computational facilities and the associated expertise necessary to carry out high performance computing. Projects such as the one described here offer resource managers the ability to apply the most scientificallydefensible models, even when these involve intensive computation. Spatially-explicit and temporally-varying models, though realistic in that they account for what we know of environmental variation and its impacts on natural systems, present numerous computational challenges. We expect that grid service modules will provide feasible methods to address these problems as well as provide input to decision support tools that are needed in natural resource management. From a broader perspective, we argue that grid service modules have a potential positive impact on applied and scientific computation problems for two different audiences: i) for model developers, they provide a practical, explicit approach to easily utilize remote high performance infrastructure and existing simulation packages (without code modification) to explore new frontiers in science and engineering; and ii) for decision makers and stakeholders, they create an intuitive method to launch and analyze model results without concern for the underlying implementations, utilizing highly integrated simulations and modeling approaches. 7
8 Acknowledgement This research has been supported by the National Science Foundation under grant No. DEB This research used the resources of the Scalable Intracampus Research Grid (SInRG) Project at the University of Tennessee, supported by the National Science Foundation CISE Research Infrastructure Award EIA References 1. Dale, V.H., Opportunities for Using Ecological Models for Resource Management, 2003, in Dale, V.H. (ed.), Ecological Modeling for Resource Management, Springer-Verlag New York, Inc. 2. Ginzburg, L., Akcakaya, H.R., Science and Management Investments Needed to Enhance the Use of Ecological Modeling in Decision Making, 2003, in Dale, V.H. (ed.), Ecological Modeling for Resource Management, Springer-Verlag New York, Inc. 3. Grid Computing Info Centre (GRID infoware), 4. ATLSS: Across Trophic Level System Simulation, 5. SInRG: Scalable Intracampus Research Grid, Innovative Computing Laboratory at the University of Tennessee, Knoxville, TN, 2002, 6. NetSolve, Innovative Computing Laboratory at the University of Tennessee, Knoxville, TN, 2002, 7. IBP: Internet Backplane Protocol, Logistical Computing and Internetworking Laboratory at the University of Tennessee, Knoxville, TN, 2002, 8. Wang, D., M. W. Berry, E. Carr, L. J. Gross, 2003, Parallel Landscape Fish Model for South Florida Ecosystem Simulation, Proceedings of Supercomputing 2003, Phoenix, AZ. 9. Wang D., E. A. Carr, M. W. Berry, L. J. Gross, Parallel Fish Landscape Model for Ecosystem Modeling on a Computing Grid, Parallel and Distributed Computing Practices (in review) 10. ATLSS Data Viewer System: National Wetlands Research Center, USGS MPI: Message Passing Interface Standard Curnutt, J. L., E.J. Comiskey, M. P. Nott and L. J. Gross Landscapebased spatially explicit species index models for Everglades restoration. Ecological Applications 10:
GridSolve: : A Seamless Bridge Between the Standard Programming Interfaces and Remote Resources
GridSolve: : A Seamless Bridge Between the Standard Programming Interfaces and Remote Resources Jack Dongarra University of Tennessee and Oak Ridge National Laboratory 2/25/2006 1 Overview Grid/NetSolve
More informationLarge Data Visualization using Shared Distributed Resources
Large Data Visualization using Shared Distributed Resources Huadong Liu, Micah Beck, Jian Huang, Terry Moore Department of Computer Science University of Tennessee Knoxville, TN Background To use large-scale
More informationRemote sensing information cloud service: research and practice
Remote sensing information cloud service: research and practice Yang Banghui Dr., Ren Fuhu Prof. and Wang jinnian Prof. yangbh@radi.ac.cn +8613810963452 Content 1 Background 2 Studying and Designing 3
More informationCluster, Grid, Cloud Concepts
Cluster, Grid, Cloud Concepts Kalaiselvan.K Contents Section 1: Cluster Section 2: Grid Section 3: Cloud Cluster An Overview Need for a Cluster Cluster categorizations A computer cluster is a group of
More informationSensing, monitoring and actuating on the UNderwater world through a federated Research InfraStructure Extending the Future Internet SUNRISE
Sensing, monitoring and actuating on the UNderwater world through a federated Research InfraStructure Extending the Future Internet SUNRISE Grant Agreement number 611449 Announcement of the Second Competitive
More informationImproved metrics collection and correlation for the CERN cloud storage test framework
Improved metrics collection and correlation for the CERN cloud storage test framework September 2013 Author: Carolina Lindqvist Supervisors: Maitane Zotes Seppo Heikkila CERN openlab Summer Student Report
More informationvisperf: Monitoring Tool for Grid Computing
visperf: Monitoring Tool for Grid Computing DongWoo Lee 1, Jack J. Dongarra and R.S. Ramakrishna Department of Information and Communication, Kwangju Institute of Science and Technology, South Korea leepro,rsr
More informationScalability and Performance Report - Analyzer 2007
- Analyzer 2007 Executive Summary Strategy Companion s Analyzer 2007 is enterprise Business Intelligence (BI) software that is designed and engineered to scale to the requirements of large global deployments.
More informationDynamism and Data Management in Distributed, Collaborative Working Environments
Dynamism and Data Management in Distributed, Collaborative Working Environments Alexander Kipp 1, Lutz Schubert 1, Matthias Assel 1 and Terrence Fernando 2, 1 High Performance Computing Center Stuttgart,
More informationThe Data Grid: Towards an Architecture for Distributed Management and Analysis of Large Scientific Datasets
The Data Grid: Towards an Architecture for Distributed Management and Analysis of Large Scientific Datasets!! Large data collections appear in many scientific domains like climate studies.!! Users and
More informationHEP Data-Intensive Distributed Cloud Computing System Requirements Specification Document
HEP Data-Intensive Distributed Cloud Computing System Requirements Specification Document CANARIE NEP-101 Project University of Victoria HEP Computing Group December 18, 2013 Version 1.0 1 Revision History
More informationWhite Paper. ThinRDP Load Balancing
White Paper ThinRDP Load Balancing Introduction Load balancing and Fault-tolerance are methodologies to distribute workload across multiple services to achieve optimal resource utilization, avoid overload
More informationGrid Computing Making the Global Infrastructure a Reality Teena Vyas March 11, 2004
Chapter 32 - Grid Resource Allocation and Control using computational economies Grid Computing Making the Global Infrastructure a Reality Teena Vyas March 11, 2004 Introduction Basic strategies used for
More informationFUTURE VIEWS OF FIELD DATA COLLECTION IN STATISTICAL SURVEYS
FUTURE VIEWS OF FIELD DATA COLLECTION IN STATISTICAL SURVEYS Sarah Nusser Department of Statistics & Statistical Laboratory Iowa State University nusser@iastate.edu Leslie Miller Department of Computer
More informationIT service for life science
anterio performs research in the field of molecular modelling including computer-aided drug design. With our experience in these fields we help customers to implement an IT infrastructure to aid these
More informationGeoCloud Project Report USGS/EROS Spatial Data Warehouse Project
GeoCloud Project Report USGS/EROS Spatial Data Warehouse Project Description of Application The Spatial Data Warehouse project at the USGS/EROS distributes services and data in support of The National
More informationlocuz.com HPC App Portal V2.0 DATASHEET
locuz.com HPC App Portal V2.0 DATASHEET Ganana HPC App Portal makes it easier for users to run HPC applications without programming and for administrators to better manage their clusters. The web-based
More informationWyoming Geographic Information Science Center University Planning 3 Unit Plan, 2009-2014 #
I. Mission and Aspirations Wyoming Geographic Information Science Center University Planning 3 Unit Plan, 2009-2014 # The mission of the Wyoming Geographic Information Science Center (WyGISC) is to advance
More informationApplying Business Architecture to the Cloud
Applying Business Architecture to the Cloud Mike Rosen, Chief Scientist Mike.Rosen@ WiltonConsultingGroup.com Michael Rosen Agenda n What do we mean by the cloud? n Sample architecture and cloud support
More informationANSYS EKM Overview. What is EKM?
ANSYS EKM Overview What is EKM? ANSYS EKM is a simulation process and data management (SPDM) software system that allows engineers at all levels of an organization to effectively manage the data and processes
More informationIntegrated Municipal Asset Management tool (IMAM)
Integrated Municipal Asset Management tool (IMAM) Integrated Municipal Asset Management tool that makes it easy for decision makers to use and implement the developed Models. This tool is developed using
More informationCollaborative & Integrated Network & Systems Management: Management Using Grid Technologies
2011 International Conference on Computer Communication and Management Proc.of CSIT vol.5 (2011) (2011) IACSIT Press, Singapore Collaborative & Integrated Network & Systems Management: Management Using
More informationa new generation software test automation framework - CIVIM
a new generation software test automation framework - CIVIM Software Testing is the last phase in software development lifecycle which has high impact on the quality of the final product delivered to the
More informationServer Consolidation with SQL Server 2008
Server Consolidation with SQL Server 2008 White Paper Published: August 2007 Updated: July 2008 Summary: Microsoft SQL Server 2008 supports multiple options for server consolidation, providing organizations
More informationSoftline VIP Payroll System Requirements v2.9a January 2010
i Softline VIP Payroll System Requirements v2.9a January 2010 Table of Contents Introduction... 1 Assumptions... 1 Standalone Requirements... 2 Note:Peer-to-peer Network Installations... 2 Peer-to-peer
More informationTranslating Science Into Practice
Translating Science Into Practice Climate Change Carbon Cycle Translating Science Into Practice Tools and interfaces that aid in turning the data into useable and accessible information 1 Translating Science
More informationUnderstand the strategic arrangement of IS/IT in modern organisations. Week 3 IT Architecture and Infrastructure. Lecture objectives
IMS9043 IT in Organisations Lecture objectives Week 3 IT Architecture and Infrastructure Understand the strategic arrangement of IS/IT in modern organisations 1 2 Information Systems & People Information
More informationUsing the Grid for the interactive workflow management in biomedicine. Andrea Schenone BIOLAB DIST University of Genova
Using the Grid for the interactive workflow management in biomedicine Andrea Schenone BIOLAB DIST University of Genova overview background requirements solution case study results background A multilevel
More informationScientific and Technical Applications as a Service in the Cloud
Scientific and Technical Applications as a Service in the Cloud University of Bern, 28.11.2011 adapted version Wibke Sudholt CloudBroker GmbH Technoparkstrasse 1, CH-8005 Zurich, Switzerland Phone: +41
More informationHigh Performance Cluster Support for NLB on Window
High Performance Cluster Support for NLB on Window [1]Arvind Rathi, [2] Kirti, [3] Neelam [1]M.Tech Student, Department of CSE, GITM, Gurgaon Haryana (India) arvindrathi88@gmail.com [2]Asst. Professor,
More informationORACLE DATABASE 10G ENTERPRISE EDITION
ORACLE DATABASE 10G ENTERPRISE EDITION OVERVIEW Oracle Database 10g Enterprise Edition is ideal for enterprises that ENTERPRISE EDITION For enterprises of any size For databases up to 8 Exabytes in size.
More informationISA CERTIFIED AUTOMATION PROFESSIONAL (CAP ) CLASSIFICATION SYSTEM
ISA CERTIFIED AUTOMATION PROFESSIONAL (CAP ) CLASSIFICATION SYSTEM Domain I: Feasibility Study - identify, scope and justify the automation project Task 1: Define the preliminary scope through currently
More informationIntroduction to grid technologies, parallel and cloud computing. Alaa Osama Allam Saida Saad Mohamed Mohamed Ibrahim Gaber
Introduction to grid technologies, parallel and cloud computing Alaa Osama Allam Saida Saad Mohamed Mohamed Ibrahim Gaber OUTLINES Grid Computing Parallel programming technologies (MPI- Open MP-Cuda )
More informationUptime Infrastructure Monitor. Installation Guide
Uptime Infrastructure Monitor Installation Guide This guide will walk through each step of installation for Uptime Infrastructure Monitor software on a Windows server. Uptime Infrastructure Monitor is
More informationStock Trader System. Architecture Description
Stock Trader System Architecture Description Michael Stevens mike@mestevens.com http://www.mestevens.com Table of Contents 1. Purpose of Document 2 2. System Synopsis 2 3. Current Situation and Environment
More informationProduct Brief. DC-Protect. Content based backup and recovery solution. By DATACENTERTECHNOLOGIES
Product Brief DC-Protect Content based backup and recovery solution By DATACENTERTECHNOLOGIES 2002 DATACENTERTECHNOLOGIES N.V. All rights reserved. This document contains information proprietary and confidential
More informationRPC and TI-RPC Test Suite Test Plan Document
RPC and TI-RPC Test Suite Test Plan Document Cyril LACABANNE Bull S.A.S. Version 1.3 12 July 2007 Revision history Version Description 1.0 First release 1.1 Several correction on 1, 5, 8, 14 1.2 Add first
More informationAn approach to grid scheduling by using Condor-G Matchmaking mechanism
An approach to grid scheduling by using Condor-G Matchmaking mechanism E. Imamagic, B. Radic, D. Dobrenic University Computing Centre, University of Zagreb, Croatia {emir.imamagic, branimir.radic, dobrisa.dobrenic}@srce.hr
More informationG-Monitor: Gridbus web portal for monitoring and steering application execution on global grids
G-Monitor: Gridbus web portal for monitoring and steering application execution on global grids Martin Placek and Rajkumar Buyya Grid Computing and Distributed Systems (GRIDS) Lab Department of Computer
More informationBringing Value to the Organization with Performance Testing
Bringing Value to the Organization with Performance Testing Michael Lawler NueVista Group 1 Today s Agenda Explore the benefits of a properly performed performance test Understand the basic elements of
More informationDeveloping Microsoft Azure Solutions 20532B; 5 Days, Instructor-led
Developing Microsoft Azure Solutions 20532B; 5 Days, Instructor-led Course Description This course is intended for students who have experience building vertically scaled applications. Students should
More informationCisco Application Networking for IBM WebSphere
Cisco Application Networking for IBM WebSphere Faster Downloads and Site Navigation, Less Bandwidth and Server Processing, and Greater Availability for Global Deployments What You Will Learn To address
More informationTableau Server 7.0 scalability
Tableau Server 7.0 scalability February 2012 p2 Executive summary In January 2012, we performed scalability tests on Tableau Server to help our customers plan for large deployments. We tested three different
More informationTEST AUTOMATION FRAMEWORK
TEST AUTOMATION FRAMEWORK Twister Topics Quick introduction Use cases High Level Description Benefits Next steps Twister How to get Twister is an open source test automation framework. The code, user guide
More informationCapacity Plan. Template. Version X.x October 11, 2012
Template Version X.x October 11, 2012 This is an integral part of infrastructure and deployment planning. It supports the goal of optimum provisioning of resources and services by aligning them to business
More informationIBM Global Technology Services September 2007. NAS systems scale out to meet growing storage demand.
IBM Global Technology Services September 2007 NAS systems scale out to meet Page 2 Contents 2 Introduction 2 Understanding the traditional NAS role 3 Gaining NAS benefits 4 NAS shortcomings in enterprise
More informationPERFORMANCE COMPARISON OF COMMON OBJECT REQUEST BROKER ARCHITECTURE(CORBA) VS JAVA MESSAGING SERVICE(JMS) BY TEAM SCALABLE
PERFORMANCE COMPARISON OF COMMON OBJECT REQUEST BROKER ARCHITECTURE(CORBA) VS JAVA MESSAGING SERVICE(JMS) BY TEAM SCALABLE TIGRAN HAKOBYAN SUJAL PATEL VANDANA MURALI INTRODUCTION Common Object Request
More informationCisco Application Networking for BEA WebLogic
Cisco Application Networking for BEA WebLogic Faster Downloads and Site Navigation, Less Bandwidth and Server Processing, and Greater Availability for Global Deployments What You Will Learn To address
More informationProject Title: Project PI(s) (who is doing the work; contact Project Coordinator (contact information): information):
Project Title: Great Northern Landscape Conservation Cooperative Geospatial Data Portal Extension: Implementing a GNLCC Spatial Toolkit and Phenology Server Project PI(s) (who is doing the work; contact
More informationPC-Duo Web Console Installation Guide
PC-Duo Web Console Installation Guide Release 12.1 August 2012 Vector Networks, Inc. 541 Tenth Street, Unit 123 Atlanta, GA 30318 (800) 330-5035 http://www.vector-networks.com Copyright 2012 Vector Networks
More informationHarmonized Use Case for Electronic Health Records (Laboratory Result Reporting) March 19, 2006
Harmonized Use Case for Electronic Health Records (Laboratory Result Reporting) March 19, 2006 Office of the National Coordinator for Health Information Technology (ONC) Table of Contents American Health
More informationMIGRATING DESKTOP AND ROAMING ACCESS. Migrating Desktop and Roaming Access Whitepaper
Migrating Desktop and Roaming Access Whitepaper Poznan Supercomputing and Networking Center Noskowskiego 12/14 61-704 Poznan, POLAND 2004, April white-paper-md-ras.doc 1/11 1 Product overview In this whitepaper
More informationLegacy System Integration Technology for Legacy Application Utilization from Distributed Object Environment
Legacy System Integration Technology for Legacy Application Utilization from Distributed Object Environment 284 Legacy System Integration Technology for Legacy Application Utilization from Distributed
More informationOnline Transaction Processing in SQL Server 2008
Online Transaction Processing in SQL Server 2008 White Paper Published: August 2007 Updated: July 2008 Summary: Microsoft SQL Server 2008 provides a database platform that is optimized for today s applications,
More informationPart I Courses Syllabus
Part I Courses Syllabus This document provides detailed information about the basic courses of the MHPC first part activities. The list of courses is the following 1.1 Scientific Programming Environment
More informationNewsletter 4/2013 Oktober 2013. www.soug.ch
SWISS ORACLE US ER GRO UP www.soug.ch Newsletter 4/2013 Oktober 2013 Oracle 12c Consolidation Planer Data Redaction & Transparent Sensitive Data Protection Oracle Forms Migration Oracle 12c IDENTITY table
More informationLEVERAGE VBLOCK SYSTEMS FOR Esri s ArcGIS SYSTEM
Leverage Vblock Systems for Esri's ArcGIS System Table of Contents www.vce.com LEVERAGE VBLOCK SYSTEMS FOR Esri s ArcGIS SYSTEM August 2012 1 Contents Executive summary...3 The challenge...3 The solution...3
More informationSAP IT Infrastructure Management. Dirk Smit ALM Engagement Manager SAP Africa dirk.smit@sap.com
SAP IT Infrastructure Management Dirk Smit ALM Engagement Manager SAP Africa dirk.smit@sap.com Challenges in managing heterogeneous IT environments Determine the value that IT contributes to the business
More informationCloud application for water resources modeling. Faculty of Computer Science, University Goce Delcev Shtip, Republic of Macedonia
Cloud application for water resources modeling Assist. Prof. Dr. Blagoj Delipetrev 1, Assist. Prof. Dr. Marjan Delipetrev 2 1 Faculty of Computer Science, University Goce Delcev Shtip, Republic of Macedonia
More informationAPPLICATIONS AND RESEARCH ON GIS FOR THE REAL ESTATE
APPLICATIONS AND RESEARCH ON GIS FOR THE REAL ESTATE Chengda Lin, Lingkui Meng, Heping Pan School of Remote Sensing Information Engineering Wuhan University, 129 Luoyu Road, Wuhan 430079, China Tel: (86-27)-8740-4336
More informationCloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers
Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers Ntinos Krampis Asst. Professor J. Craig Venter Institute kkrampis@jcvi.org http://www.jcvi.org/cms/about/bios/kkrampis/
More informationTimePictra Release 10.0
DATA SHEET Release 100 Next Generation Synchronization System Key Features Web-based multi-tier software architecture Comprehensive FCAPS management functions Software options for advanced FCAPS features
More informationCOURSE NUMBER: CTS 2371
Form 2A, Page 1 FLORIDA STATE COLLEGE AT JACKSONVILLE COLLEGE CREDIT COURSE OUTLINE COURSE NUMBER: CTS 2371 COURSE TITLE: Virtual Infrastructure: Deployment, Security, and Analysis PREREQUISITE(S): CTS
More informationSTATEMENT OF WORK. NETL Cooperative Agreement DE-FC26-02NT41476
STATEMENT OF WORK NETL Cooperative Agreement DE-FC26-02NT41476 Database and Analytical Tool for the Management of Data Derived from U. S. DOE (NETL) Funded Fine Particulate (PM 2.5 ) Research PROJECT SCOPE
More informationManjrasoft Market Oriented Cloud Computing Platform
Manjrasoft Market Oriented Cloud Computing Platform Innovative Solutions for 3D Rendering Aneka is a market oriented Cloud development and management platform with rapid application development and workload
More informationUniversity of Messina, Italy
University of Messina, Italy IEEE MoCS 2011 Kerkyra - Greece June 28, 2011 Dr. Massimo Villari mvillari@unime.it Cross Cloud Federation Federated Cloud Scenario Cloud Middleware Model: the Stack The CLEVER
More informationCONNECTING TO DEPARTMENT OF COMPUTER SCIENCE SERVERS BOTH FROM ON AND OFF CAMPUS USING TUNNELING, PuTTY, AND VNC Client Utilities
CONNECTING TO DEPARTMENT OF COMPUTER SCIENCE SERVERS BOTH FROM ON AND OFF CAMPUS USING TUNNELING, PuTTY, AND VNC Client Utilities DNS name: turing.cs.montclair.edu -This server is the Departmental Server
More informationSimplifying Administration and Management Processes in the Polish National Cluster
Simplifying Administration and Management Processes in the Polish National Cluster Mirosław Kupczyk, Norbert Meyer, Paweł Wolniewicz e-mail: {miron, meyer, pawelw}@man.poznan.pl Poznań Supercomputing and
More informationDistributed Systems and Recent Innovations: Challenges and Benefits
Distributed Systems and Recent Innovations: Challenges and Benefits 1. Introduction Krishna Nadiminti, Marcos Dias de Assunção, and Rajkumar Buyya Grid Computing and Distributed Systems Laboratory Department
More informationTransitioning from a Physical to Virtual Production Environment. Ryan Miller Middle Tennessee Electric Membership Corp
Transitioning from a Physical to Virtual Production Environment Ryan Miller Middle Tennessee Electric Membership Corp Introduction MTEMC Distribute electricity to ~200,000 residential & business members
More informationENOVIA V6 Architecture Performance Capability Scalability
ENOVIA V6 Technical Advantages Whitepaper ENOVIA V6 Architecture Performance Capability Scalability a Product Lifecycle Management Whitepaper Prepared by ENOVIA, a Dassault Systèmes Brand Executive Summary
More information- An Essential Building Block for Stable and Reliable Compute Clusters
Ferdinand Geier ParTec Cluster Competence Center GmbH, V. 1.4, March 2005 Cluster Middleware - An Essential Building Block for Stable and Reliable Compute Clusters Contents: Compute Clusters a Real Alternative
More informationAutomated deployment of virtualization-based research models of distributed computer systems
Automated deployment of virtualization-based research models of distributed computer systems Andrey Zenzinov Mechanics and mathematics department, Moscow State University Institute of mechanics, Moscow
More informationPRIMERGY server-based High Performance Computing solutions
PRIMERGY server-based High Performance Computing solutions PreSales - May 2010 - HPC Revenue OS & Processor Type Increasing standardization with shift in HPC to x86 with 70% in 2008.. HPC revenue by operating
More informationParallel Visualization for GIS Applications
Parallel Visualization for GIS Applications Alexandre Sorokine, Jamison Daniel, Cheng Liu Oak Ridge National Laboratory, Geographic Information Science & Technology, PO Box 2008 MS 6017, Oak Ridge National
More informationFOUNDATIONS OF A CROSS- DISCIPLINARY PEDAGOGY FOR BIG DATA
FOUNDATIONS OF A CROSSDISCIPLINARY PEDAGOGY FOR BIG DATA Joshua Eckroth Stetson University DeLand, Florida 3867402519 jeckroth@stetson.edu ABSTRACT The increasing awareness of big data is transforming
More informationImplementing a Microsoft SQL Server 2005 Database
This class combines two courses into one 5-day class. 2779 (3-day) & 2780 (2-day) Implementing a Microsoft SQL Server 2005 Database Course 2779: Three days; Instructor-Led Introduction This three-day instructor-led
More informationSolving Healthcare's BIG Data Problem... Imaging and Cloud Infrastructure
Solving Healthcare's BIG Data Problem... Imaging and Cloud Infrastructure Michael J. Gray Gray Consulting 1 Objectives Background & Landscape Summary of Problems & Issues Role of Vendor Neutral Archive
More informationTowards a New Model for the Infrastructure Grid
INTERNATIONAL ADVANCED RESEARCH WORKSHOP ON HIGH PERFORMANCE COMPUTING AND GRIDS Cetraro (Italy), June 30 - July 4, 2008 Panel: From Grids to Cloud Services Towards a New Model for the Infrastructure Grid
More informationStream Processing on GPUs Using Distributed Multimedia Middleware
Stream Processing on GPUs Using Distributed Multimedia Middleware Michael Repplinger 1,2, and Philipp Slusallek 1,2 1 Computer Graphics Lab, Saarland University, Saarbrücken, Germany 2 German Research
More informationHow To Test For Performance And Scalability On A Server With A Multi-Core Computer (For A Large Server)
Scalability Results Select the right hardware configuration for your organization to optimize performance Table of Contents Introduction... 1 Scalability... 2 Definition... 2 CPU and Memory Usage... 2
More informationGFI Product Manual. Deployment Guide
GFI Product Manual Deployment Guide http://www.gfi.com info@gfi.com The information and content in this document is provided for informational purposes only and is provided "as is" with no warranty of
More informationTroubleshooting BlackBerry Enterprise Service 10 version 10.1.1 726-08745-123. Instructor Manual
Troubleshooting BlackBerry Enterprise Service 10 version 10.1.1 726-08745-123 Instructor Manual Published: 2013-07-02 SWD-20130702091645092 Contents Advance preparation...7 Required materials...7 Topics
More informationFLORIDA STATE COLLEGE AT JACKSONVILLE COLLEGE CREDIT COURSE OUTLINE. CTS 2655 and CNT 2102 with grade of C or higher in both courses
Form 2A, Page 1 FLORIDA STATE COLLEGE AT JACKSONVILLE COLLEGE CREDIT COURSE OUTLINE COURSE NUMBER: CTS 2662 COURSE TITLE: PREREQUISITE(S): COREQUISITE(S): Voice Over IP CTS 2655 and CNT 2102 with grade
More informationInternet accessible facilities management
Internet accessible facilities management A technology overview This overview is an outline of the major components and features of TotalControl, deployment possibilities and a list of terms that describe
More informationINFORMATION SCIENCE. INFSCI 0010 INTRODUCTION TO INFORMATION SCIENCE 3 cr. INFSCI 0015 DATA STRUCTURES AND PROGRAMMING TECHNIQUES 3 cr.
INFORMATION SCIENCE INFSCI 0010 INTRODUCTION TO INFORMATION SCIENCE 3 cr. Introduction to the concepts, principles, and skills of information science for students with no programming experience. Topics
More informationThe Role of the Software Architect
IBM Software Group The Role of the Software Architect Peter Eeles peter.eeles@uk.ibm.com 2004 IBM Corporation Agenda Architecture Architect Architecting Requirements Analysis and design Implementation
More informationProvisioning and Resource Management at Large Scale (Kadeploy and OAR)
Provisioning and Resource Management at Large Scale (Kadeploy and OAR) Olivier Richard Laboratoire d Informatique de Grenoble (LIG) Projet INRIA Mescal 31 octobre 2007 Olivier Richard ( Laboratoire d Informatique
More informationIBM Cognos Controller
IBM Cognos Controller Accurate, auditable close, consolidation and reporting in a solution managed by the office of finance Highlights Provides all close, consolidation and reporting capabilities Automates
More informationOcé PRISMA access BUSINESS CONTROL. Order submission and workflow management made easy
Océ PRISMA access BUSINESS CONTROL Order submission and workflow management made easy 2 ATTRACT, PRINT, DELIVER Océ PRISMAaccess workflow management software helps transform your print shop into a print
More informationIBM 000-281 EXAM QUESTIONS & ANSWERS
IBM 000-281 EXAM QUESTIONS & ANSWERS Number: 000-281 Passing Score: 800 Time Limit: 120 min File Version: 58.8 http://www.gratisexam.com/ IBM 000-281 EXAM QUESTIONS & ANSWERS Exam Name: Foundations of
More informationFundamentals of LoadRunner 9.0 (2 Days)
Fundamentals of LoadRunner 9.0 (2 Days) Quality assurance engineers New users of LoadRunner who need to load test their applications and/or executives who will be involved in any part of load testing.
More informationInformation Technology Engineers Examination. Network Specialist Examination. (Level 4) Syllabus. Details of Knowledge and Skills Required for
Information Technology Engineers Examination Network Specialist Examination (Level 4) Syllabus Details of Knowledge and Skills Required for the Information Technology Engineers Examination Version 2.0
More informationHow To Write An Nccwsc/Csc Data Management Plan
Guidance and Requirements for NCCWSC/CSC Plans (Required for NCCWSC and CSC Proposals and Funded Projects) Prepared by the CSC/NCCWSC Working Group Emily Fort, Data and IT Manager for the National Climate
More informationWhat can DDS do for You? Learn how dynamic publish-subscribe messaging can improve the flexibility and scalability of your applications.
What can DDS do for You? Learn how dynamic publish-subscribe messaging can improve the flexibility and scalability of your applications. 2 Contents: Abstract 3 What does DDS do 3 The Strengths of DDS 4
More informationKM road map. Technology Components of KM. Chapter 5- The Technology Infrastructure. Knowledge Management Systems
Knowledge Management Systems Chapter 5- The Technology Infrastructure Dr. Mohammad S. Owlia Associate Professor, Industrial Engineering Department, Yazd University E-mail :owliams@gmail.com, Website :
More informationInformation Systems Development Process (Software Development Life Cycle)
Information Systems Development Process (Software Development Life Cycle) Phase 1 Feasibility Study Concerned with analyzing the benefits and solutions for the identified problem area Includes development
More informationOptimizing Storage for Better TCO in Oracle Environments. Part 1: Management INFOSTOR. Executive Brief
Optimizing Storage for Better TCO in Oracle Environments INFOSTOR Executive Brief a QuinStreet Excutive Brief. 2012 To the casual observer, and even to business decision makers who don t work in information
More informationThe Massachusetts Open Cloud (MOC)
The Massachusetts Open Cloud (MOC) October 11, 2012 Abstract The Massachusetts open cloud is a new non-profit open public cloud that will be hosted (primarily) at the MGHPCC data center. Its mission is
More informationEXECUTIVE SUMMARY CONTENTS. 1. Summary 2. Objectives 3. Methodology and Approach 4. Results 5. Next Steps 6. Glossary 7. Appendix. 1.
CONTENTS 1. Summary 2. Objectives 3. Methodology and Approach 4. Results 5. Next Steps 6. Glossary 7. Appendix EXECUTIVE SUMMARY Tenzing Managed IT services has recently partnered with Amazon Web Services
More information