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Grid Computing Overview and Research Issues. Peter Kelly Adelaide University, Australia [email protected] Supervisors:. Paul Coddington Andrew Wendelborn. What is grid computing?. Grid computing is many things to many people At its core, it’s about

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Grid computing overview and research issues l.jpg

Grid ComputingOverview and Research Issues

Peter Kelly

Adelaide University, Australia

[email protected]


Paul Coddington

Andrew Wendelborn

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What is grid computing?

Grid computing is many things to many people

At its core, it’s about

  • Sharing computing resources between organisations

  • Enabling more complex and demanding applications by providing widespread access to powerful computers and storage

  • Integrating existing systems together

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What is grid computing?

In some respects it’s similar to cluster computing, however each computer may

  • Be located in a different country

  • Use a different CPU architecture

  • Run a different operating system

  • Be owned by a different organisation

  • Have a different amount of memory, disk space, and computing power, and network bandwidth

  • Not be available all of the time

    Thus grids are much more complex than clusters!

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Why is it useful?

  • Demand for computing power is growing rapidly

    • In industry, science, government, engineering, entertainment, defence… everywhere

  • Need ways to harness the large amount of computing power available around the world

  • Organisations often want to collaborate on projects and share resources with each other

  • Grids provide the infrastructure to integrate different applications that need to collaborate with each other to get useful work done

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Types of grid computing

  • Service Oriented Architecture (SOA)

  • Job submission (supercomputer access)

  • Cycle stealing

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Service Oriented Architecture (SOA)

  • Applications are exposed as services, which provide a well-defined interface and are accessed through standard protocols

  • Clients use remote procedure calls to access these services





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Benefits of SOA

  • SOA is platform agnostic

    • Client doesn’t need to know how service is implemented

    • Service doesn’t need to know how client is implemented

  • SOA is vendor independent

    • Based on open standards – no “lock in”

    • All SOA vendors support the same standards to enable interoperability

  • SOA is widely supported

    • Many companies are getting behind it

    • Being adopted widely in commercial and scientific organisations

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Job submission

  • Many organisations have large supercomputers (SMP or clusters) that they want users to be able to submit jobs to

  • This can be achieved by installing middleware on each supercomputer which interfaces to the local job queue

    • e.g. Globus GRAM - allows users to submit to job queues such as PBS, LSF, etc.

  • Users submit jobs to a superscheduler which manages a “higher level” queue and dispatches jobs to resources

  • The grid middleware handles tasks such as copying files to and from the execution node, monitoring job progress, and abstracts the details of these away from clients

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Job submission


SMP machine






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Benefits of Job Submission Grids

  • Users do not have to worry about differences between job submission systems running on different resources

  • Superschedulers make it possible to automatically find resources that will execute the job quicker

  • A user submits a job to a grid, it runs, and they get the results back later

  • Job submission can be implemented on top of SOA by providing a service with methods for submitting and monitoring jobs, as well as notifying clients of failures or completion

    • e.g. Globus MMJFS – provides a web service interface to allow users to submit jobs

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Cycle stealing

  • The use of large numbers of desktop PCs to run “embarrassingly parallel” applications

  • A master node coordinates execution and hands out tasks to workers

  • The worker process on each machine polls the master for work to do, and then executes the tasks as they become ready

  • Worker detects when the machine is being used by a user and suspends/aborts the active task

  • This model is inherently fault tolerant; if a machine dies or a task is aborted it can just be sent to another worker

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Cycle stealing






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Benefits of cycle stealing

  • Organisations can use their existing infrastructure to run computationally demanding applications

    • No need to invest in large SMP systems or clusters

  • Large-scale internet projects can get free computing power

    • …provided they can convince users to donate CPU time

    • e.g. [email protected]

  • Cheap supercomputing

  • Generally easy to deploy

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So what really is grid computing?

  • Not really one specific technology or concept

  • More of an umbrella term, like “networking” or “operating system”

  • Any (concrete) discussion of grid computing requires all parties involved to agree on a definition of what features they are focusing on

  • Very much dependent upon what you want to do – different types of organisations have different requirements

  • Sometimes the lines are blurred and numerous systems support multiple “types” of grid computing

  • Lots of hype – can be very confusing at first!

    • it took me about a year to understand it enough to be able to figure out what I wanted to do in my project

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Web services

  • Web services are a particular type of SOA

  • Based on standards from W3C and others:

    • WSDL - language for defining service interfaces

    • SOAP - format used for exchange of messages

    • UDDI - directory mechanism for locating services

    • XML - used as standard encoding mechanism used by WS protocols

    • … and many more

  • Web services are supported by all major programming languages

    • either as part of built-in APIs or add-on libraries

  • Today web services are the most popular mechanism for integrating systems together in and between organisations

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Web service composition

  • A programming model based on composing together functionality provided by multiple web services

  • Similar to the use of shared libraries/DLL files

    • common functionality provided by shared entity (service)

    • composition program builds additional functionality by making use of one or more services

  • Service composition programs can themselves be exposed as web services

    • Can then be accessed by clients

    • Or used as part of even higher-level service compositions

  • Most popular language at present is BPEL (Business Process Execution Language)

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SOA programming vs. remote execution

  • Web services allow you to invoke programs already installed on a remote machine

  • Remote code execution allows you to execute arbitrary code on a remote machine

  • The latter is used for job submission and cycle stealing systems

  • Our research investigates a combination of these approaches

    • Provides ability to invoke and expose web services

    • Provides a distributed execution environment

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Execution Environments

  • Problem: Need a standard way of executing arbitrary code remotely

  • SOA doesn’t give you this

    • it only standardises the protocols for different applications to interact with each other

  • Job submission systems don’t give you this

    • only standardise the means of submitting and monitoring jobs – but not how they are actually executed

  • Cycle stealing requires this

    • existing cycle stealing systems these days typically specify Java or .NET, or use app-specific worker code

    • but there is no standard which allows us to do this on an internet scale

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What is an execution environment

  • Instruction set

    • e.g. x86, PPC, SPARC, Java bytecode, .NET bytecode

  • API library

    • e.g. WIN32, POSIX, Java class libraries, .NET class libraries

  • Applications are always compiled for a specific execution environment

  • Can have different implementations of that environment

    • x86 - AMD, Intel

    • Java - Sun, IBM, various open source efforts

    • .NET - Microsoft, Mono project

  • Applications compiled for a particular execution environment can run on any implementation of it

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Virtual machines

  • Common way of implementing an execution environment

  • Abstracts away from underlying hardware/OS, providing platform independence

  • In a grid containing machines of different CPU architectures and operating systems this is necessary to provide seamless access

  • To enable code to be executed anywhere, each machine on the grid must provide the same execution environment

  • Currently popular virtual machines:

    • Java Virtual Machine (JVM)

    • .NET Common Language Runtime (CLR)

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A grid execution environment?

  • Problem: No standard execution environment supported by the popular grid middleware

  • Standardisation efforts (GGF) to date have focused only service interfaces, not implementation

  • Each grid middleware system provides its own set of APIs, and is targeted at different VMs/OSs

  • Applications are not yet portable between different middleware systems

    • At least not in the same sense that bytecode-compiled code is portable

    • Compatibility exists only at the service interface level

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My belief:

  • We won’t see the full potential of grid computing until we have agreement on a standard execution environment

  • Currently only SOA aspects are standardised

    • But this goes only half way to solving the problem

      This is is very much an open research issue

  • Obvious candidates are Java and .NET

    • But are they sufficient? Should they be extended?

  • What about other alternatives?

    • Much research already done into VM technology

    • But not so much in the grid community

    • IMHO a very important issue! More research needed here

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It’s just like the web

  • Early web pages were static, as there was no support for executing code in the browser; code only ran server-side

    • In the grid world this corresponds to SOA

  • Then came early versions of JavaScript/DHTML

    • Lack of standardisation, browsers were incompatible

  • Now we have a standard, widely supported, platform independent execution environment on 300+ million computers worldwide (JavaScript/ECMAScript)

    • And look what happened… client side web apps, AJAX, Google maps, “Web 2.0” and the rest

  • I predict grid will go through the same evolution

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Our current research

  • Investigating how to combine SOA and remote code execution programming models

  • Development of a new virtual machine + language implementation targeted at grid applications


  • An implementation of the XSLT programming language

    • Supports web service composition

    • Executes programs across a grid in parallel

    • Provides a natural way to deal with XML data

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  • Ideal for manipulating XML data

  • Has a “semantic match” with many properties of web services

  • Is a functional language and can be automatically parallelised

  • W3C standard with a sizable existing user base

    • We wanted to avoid the challenges of trying to design a new language and introduce it to the world

    • Better to just develop a new implementation of an existing one which is already popular

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Support for XML data

  • XSLT is specifically designed for dealing with XML data

  • All web services exchange data in XML format

  • Java, C#, C++ etc. are less suitable for manipulating XML because they are not designed for this (and in fact pre-date XML)

    • XML data is a “second class citizen” in these languages and must be accessed through library functions or converted into objects

    • APIs like DOM, SAX, etc. are less intuitive than built-in language constructs

    • Conversion to objects carries significant overheads and risks losing information (e.g. element ordering)

  • We argue that XSLT is therefore a useful approach to developing composite web services

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Pass by value semantics

  • Another mismatch between OO languages and web services is the way in which function arguments are handled

  • OO languages use pass by reference semantics - allowing a function to modify its arguments and the caller to see those changes

  • Web services use pass by value - where a new copy of each argument is made and a function can only transfer information to its caller through the return value

  • When using an OO language for WS development, the programmer must be aware of this and it can sometimes lead to mistakes

  • As a side effect-free functional language, XSLT uses pass by value, avoiding this problem

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Parallel execution

  • XSLT is a functional language

  • Functions and loops do not have side effects - there is no global state that can be modified

  • This enables automatic parallelisation

    • All arguments to a function call can be evaluated in parallel

    • All iterations of a loop can be evaluated in parallel

  • The programmer never needs to even know that their program will be run in parallel

    • No dealing with threads, synchronisation, critical sections, message passing, race conditions etc…

    • The underlying runtime system deals with all these issues

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Implementing XSLT

  • We use a technique called graph reduction, a common way if implementing functional languages

  • A program is represented as a graph

  • Execution proceeds by performing a series of transformations on the graph

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Graph reduction: Example











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Graph reduction: Example











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Graph reduction: Example







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Graph reduction: Example







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Graph reduction: Example



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Parallel graph reduction

  • Graph reduction permits the possibility of parallel execution by allowing multiple parts of the graph to be reduced in parallel

  • Each processor in a parallel computer or cluster can manipulate a separate portion of the graph

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Parallel graph reduction

+ (nprime 2000) (nprime 2001)










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Parallel graph reduction

+ (nprime 2000) (nprime 2001)








Processor 2



Processor 1

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Parallel graph reduction

+ 17389 17393






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Parallel graph reduction



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Functional programming for grids?

It permits

  • Automatic, seamless parallelism

  • Automatic, seamless fault tolerance

  • Automatic, seamless distribution


  • Some programs are based on state, which is in conflict with the pure functional programming model

    • Although there are ways to get around this, e.g. monads

  • Different programming style to what most people are used to

    • Involves a learning curve

    • But might be worth it to get the above benefits

    • …depending on your needs

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  • Grid computing is a very diverse area

    • Many different types of systems

    • Many different requirements

    • Useful in many areas

  • Different “types” of grid computing

    • SOA, job submission, cycle stealing

    • Others as well that I haven’t discussed here

  • Lots of challenges and open research questions

    • e.g. defining a suitable execution environment for grid applications

    • This is just one of many!

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Our research project - GridXSLT

  • An attempt to combine different grid computing models

    • SOA

    • Remote code execution/cycle stealing

  • Aims to make the programmer’s job easier

    • Parallelisation handled by the compiler

    • Suited to dealing with XML data exchanged by web services and stored in XML databases

    • High-level language which hides underlying details

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Websites of interest

  • Global Grid Forum


  • Grid Café (introduction to grid computing)


  • IBM - grid computing


  • GridXSLT


  • Updates on my research


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