Grid Computing for Real World Applications Suresh Marru Indiana University 5th October 2005 OSCER OU.

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Presentation transcript:

Grid Computing for Real World Applications Suresh Marru Indiana University 5th October 2005 OSCER OU

Motivation: Scientific Challenges On-Demand Storm predictions Streaming Observations Forecast Model Data Mining Storms Forming The current and future generations of scientific problems are:  Data Oriented  Increasingly stream based.  Often need petabyte archives.  In need of on-demand computing resources  Conducted by geographically distributed teams of specialists  Users do not want to expend too much time learning new technologies.

Solution Grid Technology bridges the gap between the applications and the infrastructure. Fine, but what the heck is grid computing? follow along to find out … Adapt Grid Computing and solve every computing problem in this world. Is this true? I wish it is, but not really..then what..

Introduction to Grid Grid Computing enables sharing, selection and aggregation of a wide variety of geographically distributed resources including supercomputers, storage systems, data sources and specialized devices owned by different organizations for solving large-scale resource intensive problems in science, engineering, and commerce.

Power Grid Analogy SupercomputersNetworksStorage Devices Resources Grid Portal MyProxy Globus Server API Globus Client Cog Kit API Gateway Services Instrumentation Infrastructure Interface Users

Key Features of Grid Computing Provides a secure infrastructure for computing on a distributed computing environment Provides single sign-on feature by which a user can authenticate once and perform multiple computations over extended period of time Facilitates inter-domain access mechanisms Better portability (code can run on many kinds of computers) and exportability (move files from one computer to another)

Grid Security Grid Certificates: Needed for using the Grid Used to provide a set of privileges of one resource to another Provide the features of dynamic delegation, dynamic entities and repeated authentication Standard PKI infrastructure is used for validation

Challenges of using Grid computing The concept of grid is promising but users have to cope up with..  Emerging technology  Evolving standards  Frequent new versions of middleware with little or no backwards compatibility  Users have to learn the technology to use it. Alternatively, use grid-enabled science portals

Science Portals The goals of a Science Portal are –To give a community of researchers easy access to the tools, data and computational power needed to solve today’s scientific and engineering problems. –To do this in a discipline specific language that is common to the target community. –To hide any underlying Grid technology.

Portal Science Capabilities Data Access is the most important –Allow the user community access to important shared data resources Visualize it, publish it, download it, curate it. –Data Discovery Searchable metadata directories. Web access to important tools –Web-form interfaces to allow users to run important community codes –Webstart access to common java-based tools –Limited shell access - perhaps to a VM Workflow tools –Allow users to combine community codes into workflows managed by the portal back-end resources.

The Architecture of Gateway Services The Users Desktop. Gateway Services Grid Portal Server Grid Portal Server Physical Resource Layer Core Grid Services Proxy Certificate Server / vault Proxy Certificate Server / vault Application Events Resource Broker User Metadata Catalog User Metadata Catalog Replica Mgmt Application Workflow Application Workflow App. Resource catalogs App. Resource catalogs Application Deployment Application Deployment Execution Management Execution Management Information Services Information Services Self Management Self Management Data Services Data Services Resource Management Resource Management Security Services Security Services OGSA-like Layer

Service Architecture The Foundation of the gateway science portal software is based on the concept of “services” and “service oriented architectures.”

What’s a service anyway? A “web server” that runs an application for you. –You send it requests (XML documents) and it processes the information and send replies (notifications) when it is done. Application Service 1. Service Request Compute Machine 2. Run Application 3. Publish notifications

The Portal - Service interaction Browser Portal Server 1. App service registry App Service Instance Each application is deployed as a service which can be invoked by the portal or another service. –1. User looks up & selects application services from portal. –2. Portal locates service instance. –3. Service is contacted and replies with a interface description –4. Server displays the interface and user fills it out. –5. Server create ws request and sends it to the app service.

What do we do with Applications? Service-oriented applications –Wrap applications as services –Compose applications into workflows –Execute applications on remote resources on behalf of user in a secured manner

What a User Gains By Using Grid and Portals As a direct user – Can easily Execute jobs at one or more remote sites Move data between sites All with single sign-on security As a user of a grid enabled application Will not see the grid Will see an application whose development was eased with grid functions or grid-based web services Ease of development should result in more applications or faster availability of applications

What Application Developers Gain by Using Grids and Portals Application web services can be built by re-using capabilities provided by existing grid-enabled Web services. Applications can also be built by using grid functions Grid functions/services handle distributed management of tasks and data – Developer can focus on logic of application and not logic of distributed interaction

Example Gateway LEAD – Linked Environments for Atmospheric Discovery (Mesoscale Meteorology) NSF LEAD project - making the tools that are needed to make accurate predictions of tornados and hurricanes. - Data exploration and Grid workflow

Example Gateway - LEAD (Mesoscale Meteorology)

LEAD utilizes grid tools adopting a strategy to deal with middleware issues Stick with pre-ws globus version (Globus 2.4) and slowly transition to GT 4 Develop software on self-controlled test grid constituting of machines distributed at various partner institutions port the tested version on to teragrid – production grid resources by working closely with the resource providers

Web Services Components Non-WS Components Data Management Security Common Runtime Execution Management Information Services Pre-WS Authentication Authorization GridFTP Grid Resource Allocation Mgmt (Pre-WS GRAM) Monitoring & Discovery System (MDS2) C Common Libraries GT2GT2 WS Authentication Authorization Reliable File Transfer OGSA-DAI [Tech Preview] Grid Resource Allocation Mgmt (WS GRAM) Monitoring & Discovery System (MDS4) Java WS Core Community Authorization Service GT3GT3 Replica Location Service XIO GT3GT3 Credential Management GT4GT4 Python WS Core [contribution] C WS Core Community Scheduler Framework [contribution] Delegation Service GT4GT4 Pre-WS Globus components are still supported

Java Services in Apache Axis Plus GT Libraries and Handlers Your Java Service Your Python Service Your Java Service RFT GRAM Delegation Index Trigger Archiver pyGlobus WS Core Your C Service C WS Core RLS Pre-WS MDS CAS Pre-WS GRAM SimpleCAMyProxy OGSA-DAI GTCP GridFTP C Services using GT Libraries and Handlers SERVER CLIENT Interoperable WS-I-compliant SOAP messaging Your Java Client Your C Client Your Python Client Your Java Client Your C Client Your Python Client Your Java Client Your C Client Your Python Client Your Java Client Your C Client Your Python Client X.509 credentials = common authentication Python hosting, GT Libraries GT4 Components

LEAD Test-bed Grid

DEMO LEAD Portal demo

The top level view The current weather. Click on a location for more data The current testbed status Top Level tabs to public Tools and information. To get to your stuff, log in here Or create a new account

GEO Reference GUI Prototype Use mouse to drag a region of interest. Fill in the data requirements The tool, when finished will gather the data for you.

Educational Resources

Log in and see your MyLEAD Space x

Searching MyLEAD Shots of the search tool.

The Experiment Builder To review your previous experiments and create new ones Experiments are organized into projects –You can select an old one to look at, –Or create a new project or experiment. –Let’s do a new experiment! (click “new”)

Creating a workflow for Data Mining Use ADaM services from UAH 3DMesocyclone Detection ESML_Converter MinMaxNormalizer VisualizationBayesClassifying Feature Extraction Service Nexrad II Radar Data ESML Descriptor Data Transformation Service Data Normalization Service Classification Service

Provide a name and description Next select an application from the dropdown list or create a new workflow. Once we have selected the app, we push “next” to add data.

Composing the Workflow Graphical Composer –Standard drop-and-drag composer model (like Kepler and others) –Compiles Python or PBEL code

Final Workflow Save it back to my lead Next we must bind the inputs to the workflow

Wizard understand the workflow requirements

Select an output location

Submitting the workflow

Monitor results in real time

Check it out in MyLEAD

Click on the output file to see visualization

Large workflows can be composed

Output from the Weather Workflow

Acknowledgements Slide Courtesy: Dr. Dennis Gannon Globus Website (

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