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Grid Computing and Middleware. Shawn Malhotra Monday, February 5 th , 2007. Overview. Background and definition Importance of middleware Globus Toolkit Sample Applications. What is Grid Computing?. Computing model that leverages the power of many networked resources Not just CPUs

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grid computing and middleware

Grid Computing and Middleware

Shawn Malhotra

Monday, February 5th, 2007

overview
Overview
  • Background and definition
  • Importance of middleware
  • Globus Toolkit
  • Sample Applications
what is grid computing
What is Grid Computing?
  • Computing model that leverages the power of many networked resources
  • Not just CPUs
    • Storage devices, special equipment (i.e. telescope)
  • Share resources across administrative domains
    • Requires security features
    • Different than traditional cluster computing
  • Programmer sees a single ‘virtual computer’
  • Web ↔ Information as Grid ↔ Computing Power
why is grid computing important
Why is Grid Computing Important?
  • Helps solve computationally expensive problems
    • Flexible enough to handle many small problems
  • Share costly resources amongst institutions
    • Federally funded research labs / academic institutions
  • Make resources available to anybody
    • Cost barrier is lowered
    • ‘Pay as you go’ type service
    • Increases overall bandwidth
motivation for middleware
Motivation for Middleware
  • Need robust, efficient ways to pool resources
  • Previous ‘ad-hoc’ methods not sufficient
  • Need for standardization!
  • Distributed Computing System (DCS)
    • Developed at the University of California at Irvine
    • Early 1970s
    • Focus on CPU management
  • Poor security solution
  • Abandoned in the 1980s
globus toolkit
Globus Toolkit
  • Broader scope, more complete solution
    • CPU Management
    • Storage Management
    • Monitoring Services
    • More details to come …
  • Most popular grid computing framework
  • Implements several standards
    • OGSA, WSRF, SOAP, WSDL
globus toolkit overview
Globus Toolkit - Overview
  • Facilitates grid application development
    • Open, extensible, flexible, high abstraction
job submission
Job Submission
  • GRAM interface
    • Grid Resource Allocation and Management
  • Specify resource requirements and flow
  • Uniform way to submit remote jobs
    • Translate request for local resources
  • Offers a variety of features
    • Retrieve job status
    • Send job signals (kill, start, restart)
  • Uses Web services interface
job scheduling
Job Scheduling
  • What happens after the job is submitted?
  • Submitted to a scheduler
  • Queues jobs decides where/when to run
    • Requirement matching, priority systems, etc.
  • Abstracts resources from user
    • Pool heterogeneous resources together
  • Can have multiple layers of scheduling
    • Local schedulers vs. Metaschedulers
security
Security
  • Access to resources must be controlled
  • Grid Security Infrastructure (GSI)
  • Provides basic security constructs
    • Certificate-based PKI system
    • Supports single sign-on over the grid
    • Supports delegation
  • Access control left to individual services
    • Infrastructure provides necessary info and control
  • Uses Web services interface
other provided modules
Other Provided Modules
  • Data management
    • Facilitates file transfer, access to data stores
  • Monitoring and discovery
    • APIs to get status, subscribe to content
    • Important since ‘grid’ is never down, only components
  • Collaboration tools
    • Facilitates person-to-person collaboration
    • Build web portals for chat, e-mail, etc.
example applications
Example Applications
  • What can you build with such a toolkit?
  • Applications range from the depths of the sea to the stars above!
    • LOOKING  deep sea research
    • Condor  batch computing infrastructure
    • BIRN  medical resource pooling
    • LEAD  meteorological data
    • NVO  virtual observatory
slide13
Workload management system
    • Queuing, scheduling, prioritization, monitoring
  • Pool desktops into batch system
    • Use when idle, auto-detect when busy again
  • ClasAd mechanism
    • Novel way to match resources with requests
  • Flocking
    • Seamless combination of multiple networks

http://www.cs.wisc.edu/condor

slide14
Make tools / data related to oceanography available to all researchers
  • ‘20,000 Terabits Beneath the Sea’
    • Presented at iGrid2005
    • Real-time high definition deep sea video
    • Monitor active underwater volcanoes

http://lookingtosea.ucsd.edu/

slide15
Resource pooling
    • Tools for research and diagnoses
  • Collaboration
    • Common user interface
  • Better hypotheses testing
    • Use a distributed patient population

http://www.nbirn.net/

slide16
Sharing meteorological resources
  • Algorithm Development and Mining (ADaM)
    • Works on observational data
    • Provides analysis tools
  • ARPS Data Assimilation System (ADAS)
    • Provides visualization tools
  • Earth Science Markup Language (ESML)
    • Uniform way of expressing data
  • Data Access Systems
    • Allow uniform access to distributed data

https://portal.leadproject.org/gridsphere/gridsphere

slide17
Expose the vast amount of astronomical data for all to use
    • Telescopes will produce 7 petabytes per year by 2012
  • Standardized way of expressing data
    • VOTable
  • Creation of tools to produce required data
    • ConeSearch
  • Make accessing data like using real tools

http://www.us-vo.org/

the wisdom project
The WISDOM Project
  • Analyze potential anti-malaria drugs
  • Focus lab tests on promising compounds
  • Uses up to 5000 computers in 27 countries
  • Simulate drug interaction with malaria protein
    • Test 80,000 drugs per hour, 140 million in total
  • Shows the power of collaboration
    • Many computers borrowed from particle physics simulator in the UK – GridPP
    • Shared spare capacity

http://grid.globalwatchonline.com/epicentric_portal/site/GRID/

grid computing the future
Grid Computing – The Future
  • Currently the domain of ‘Big Science’
    • Make it more mainstream for ‘Little Science’
    • Technology is not the barrier
  • Evolution of the standards
    • Continued enhancement of the toolkit
  • Better front-end design
    • Promote peer-to-peer collaboration
  • Security is still a challenge
summary
Summary
  • Grid computing is a powerful collaborative computing model
  • Grid computing requires efficient, fully featured middleware to thrive
  • Grid computing enables research and development that is not possible in isolation
references
References
  • Globus site
    • http://www.globus.org/
  • Wikipedia
    • http://en.wikipedia.org/wiki/Grid_computing
  • Grid Café
    • http://gridcafe.web.cern.ch/gridcafe/
the need for grid solutions
The Need for Grid Solutions
  • Grids are essential to sustain Moore’s Law as physical limitations will eventually limit what individual computing stations can achieve
  • It will become less necessary as individual resources become more powerful since technology grows faster than the complexity of our research
the corporate barrier
The Corporate Barrier
  • True grid computing will never be embraced by corporations due to security issues and sensitivity of data. This will limit the scope and power of the technology
  • Much like Web 2.0 has caused a shift in corporate presence on the internet, a ‘Grid 2.0’ will eventually force corporations to embrace this technology
grid middleware
Grid Middleware
  • Middleware designed to manage a grid will eventually merge with software designed to handle multiple CPUs on one motherboard to form a common solution.
  • Grid computing is far too different from multi-CPU processing to ever offer a common solution.
expanding user base
Expanding User Base
  • Development of a good middleware solution that abstracts most details of the grid will bring grid computing to ‘Little Science’ and eventually individual users.
  • The complexity of grid computing and lack of demand will prevent grid computing from ever becoming part of the main stream.