1. An Overview Grid Computing and Applications
Subject Code:
WW Grid
Rajkumar Buyya
Grid Computing and Distributed Systems (GRIDS) Lab. The University of Melbourne Melbourne, Australia

2. Overview Computing platforms and how the Grid is different ?
Towards global (Grid) computing.
Grid resource management and scheduling.
Application development challenges.
Approaches to Grid computing.
Grid applications
Grid Projects in GRIDS Melbourne
Summary and conclusions

3. Major Networking and Computing Technologies Introduction
* HTC
* P2P
* PDAs
COMPUTING
* Mainframes
* Minicomputers
* PCs
* Workstations
* Grids
* PC Clusters
* Crays
* MPPs
* XEROX PARC worm
* WS Clusters
Technologies Introduced
* IETF
* W3C
NETWORKING
* TCP/IP
* Ethernet
* HTML
* Mosaic
* Web Services *
* Internet Era
* WWW Era
* XML
* ARPANET
1960
1970
1975
1980
1985
1990
1995
2000

4. Internet: Past, Present, Future
140
120
100
The 'Network Effect’ kicks in, and the web goes critical'
Number of hosts
(millions) 80 60 40 20
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
TCP/IP
HTML
Mosaic
XML
PHASE
1. Packet Switching Networks
2. The Internet is
Born
3. The World Wide Web 4.
with
XML
5. The Grid
1969: 4 US Universities linked to form ARPANET
TCP/IP becomes core protocol
HTML hypertext system created
1972: First program created
Domain Name System created IETF created (1986)
CERN launch World Wide Web
1976: Robert Metcalfe develops Ethernet
NCSA launch Mosaic interface

5. Internet and WWW Growth
10,000,000
1,000,000
Internet Hosts
100,000
10,000
1,000
WWW Servers
100 10 4 1
1969
1970
1975
1980
1985
1990
1995
2000

6. Installed base and Growth rate for telephone lines, mobile phones, & Internet hosts - 1995
Installed, Growth Rates (%)
Income Group/ Phone Mobile Internet Phone Mobile Internet
Region Lines Phones Hosts Lines Phones Hosts
Lower Income
Lower- Middle
Upper - Middle
High
Africa
Americas
Asia
Europe
Oceans
World
Source: ACM, Nov, 97 (phones, international telecommunication union, hosts, network Wizards

7. Internet as a delivery Vehicle

8. Scalable HPC: Breaking Administrative Barriers
2100 ?
PERFORMANCE
2100
Administrative Barriers
Individual
Group
Department
Campus
State
National
Globe
Inter Planet
Universe
Desktop
SMPs or SuperComputers
Local
Cluster
Enterprise
Cluster/Grid
Global
Cluster/Grid
Inter Planet
Cluster/Grid ??

9. Why Grids ? Large Scale Exploration needs them—Killer Applications.
Solving grand challenge applications using computer modeling, simulation and analysis
Aerospace
Internet &
Ecommerce
Life Sciences
Digital Biology
CAD/CAM
Military Applications
Military Applications
Military Applications

11. Cluster of Clusters - Hyperclusters
Scheduler
Master
Daemon
Execution
Submit
Graphical
Control
Clients
Cluster 2
Cluster 3
Cluster 1
LAN/WAN

12. Grid: Towards Internet Computing for (Coordinated) Resource Sharing
Grid enables:
Resource Sharing
Selection
Aggreation
- Unification of geographically distributed resources

13. What is Grid ?
A paradigm/infrastructure that enabling the sharing, selection, & aggregation of geographically distributed resources:
Computers – PCs, workstations, clusters, supercomputers, laptops, notebooks, mobile devices, PDA, etc;
Software – e.g., ASPs renting expensive special purpose applications on demand;
Catalogued data and databases – e.g. transparent access to human genome database;
Special devices/instruments – e.g., radio telescope – searching for life in galaxy.
People/collaborators.
[depending on their availability, capability, cost, and user QoS requirements]
for solving large-scale problems/applications.
Wide area

14. P2P/Grid Applications-Drivers
Distributed HPC (Supercomputing):
Computational science.
High-Capacity/Throughput Computing:
Large scale simulation/chip design & parameter studies.
Content Sharing (free or paid)
Sharing digital contents among peers (e.g., Napster)
Remote software access/renting services:
Application service provides (ASPs) & Web services.
Data-intensive computing:
Drug Design, Particle Physics, Stock Prediction...
On-demand, realtime computing:
Medical instrumentation & Mission Critical.
Collaborative Computing:
Collaborative design, Data exploration, education.
Service Oriented Computing (SOC):
Computing as Competitive Utility: New paradigm, new industries, and new business.

15. Building and Using Grids requires...
Services that make our systems Grid Ready!
Security mechanisms that permit resources to be accessed only by authorized users.
(New) programming tools that make our applications Grid Ready!.
Tools that can translate the requirements of an application into requirements for computers, networks, and storage.
Tools that perform resource discovery, trading, composition, scheduling and distribution of jobs and collects results.

16. A Typical Grid Computing Environment
Grid Information Service
Grid Resource Broker
database
Application R2 R3 R4 R5 RN
Grid Resource Broker R6 R1
Resource Broker
Grid Information Service

18. Issues in Grid Technology Development

19. Sources of Complexity in Resource Management for World Wide Computing
Size (large number of nodes, providers, consumers)
Heterogeneity of resources (PCs, Workstatations, clusters, and supercomputers)
Heterogeneity of fabric management systems (single system image OS, queuing systems, etc.)
Heterogeneity of fabric management polices
Heterogeneity of applications (scientific, engineering, and commerce)
Heterogeneity of application requirements (CPU, I/O, memory, and/or network intensive)
Heterogeneity in demand patters
Geographic distribution and different time zones
Differing goals (producers and consumers have different objectives and strategies)
Unsecure and Unreliable environment

20. Traditional approaches to resource management are NOT useful for Grid ?
They use centralised policy that need
complete state-information and
common fabric management policy or decentralised consensus-based policy.
Due to too many heterogenous parameters in the Grid it is impossible to define:
system-wide performance matrix and
common fabric management policy that is acceptable to all.
So, we propose the usage of “economics” paradigm for managing resources
proved successful in managing decentralization and heterogeneity that is present in human economies!
We can easy leverage proven Economic principles and techniques
Easy to regulate demand and supply
User-centric, scalable, adaptable, value-driven costing, etc.
Offers incentive (money?) for being part of the grid!

21. Grid Resource Management systems need to ensure/provide:
Site autonomy.
Heterogeneous resources and substrate:
Each resource can be different – SMPs, Clusters, Linux, UNIX, Windows, Intel, etc.
Resource owners have their own policies or scheduling mechanisms (Codine/Condor).
Extend policies, through resource brokers.
Resource allocation/co-allocation
Online control - can apps (Graphics) tolerate non-availability of a resource and adapt themselves?

22. Grid RMS to support Authentication (once).
Specify (code, resources, etc.).
Discover resources.
Negotiate authorization, acceptable use, Cost, etc.
Acquire resources.
Schedule Jobs.
Initiate computation.
Steer computation.
Access remote data-sets.
Collaborate with results.
Account for usage.
Discover resources.
Negotiate authorisation,
acceptable use, Cost, etc.
Acquire resources.
Schedule jobs.
Initiate computation.
Steer computation.
Domain 1
Domain 2
Ack: Globus..

23. Resource Management Architecture
Resource Brokers
(RSL Specialization)
RSL
Information
Service - MDS
Application
Resource Co-allocators
Local Resource Mgr
Local Resource Mgr
Local Resource Mgr

24. Major Grid Projects and Initiatives

25. Grid Computing Approaches
mix-and-match
Object-oriented
Internet/partial-P2P
Grid Computing
Approaches
Network enabled Solvers
NetSolve
Economy/Service-Oriented Grid Computing
Gridbus

26. Many Grid Projects & Initiatives
Australia
Nimrod-G
GridSim
Virtual Lab
Gridbus
DISCWorld
..new coming up
Europe
UNICORE
MOL
UK eScience
Poland MC Broker
EU Data Grid
EuroGrid
MetaMPI
Dutch DAS
XW, JaWS
Japan
Ninf
DataFarm
Korea...
N*Grid
USA
Globus
Legion
OGSA
Javelin
AppLeS
NASA IPG
Condor-G
Jxta
NetSolve
AccessGrid
and many more...
Cycle Stealing & .com Initiatives
Distributed.net ….
Entropia, UD, Parabon,….
Public Forums
Global Grid Forum
P2P Working Group
IEEE TFCC
Grid & CCGrid conferences

27. Table 4: Major European Grid Computing Efforts
Initiative
Focus and Technologies Developed
UNICORE
The UNiform Interface to Computer Resources aims to deliver software that allows users to submit jobs to remote high performance computing resources –
MOL
Metacomputer OnLine is a toolbox for the coordinated use of WAN/LAN connected systems. MOL aims at utilizing multiple WAN-connected high performance systems for solving large-scale problems that are intractable on a single supercomputer –
METODIS
Metacomputing Tools for Distributed Systems –
Globe
Globe is a research project aiming to study and implement a powerful unifying paradigm for the construction of large-scale wide area distributed systems: distributed shared objects –
Pozan
Poznan Centre works on development of tools and methods for metacomputing -
Date Grid
This project aims to develop middleware and tools necessary for the data-intensive applications of high-energy physics – grid.web.cern.ch/grid
MetaMPI
MetaMPI supports the coupling of heterogeneous MPI systems, thus allowing parallel applications developed using MPI to be run on Grids without alteration –
DAS
This is a wide-area distributed cluster, used for research on parallel and distributed computing by five Dutch universities –
JaWs
JaWS is an economy-based computing model where both resource owners and programs using these resources place bids to a central marketplace that generates leases of use – roadrunner.ics.forth.gr
Table 4: Major European Grid Computing Efforts

28. Focus and Technologies Developed
Initiative
Focus and Technologies Developed
Globus
This project is developing basic software infrastructure for computations that integrate geographically distributed computational and information resources –
Legion
Legion is an object-based metasystem. Legion supports transparent scheduling, data management, fault tolerance, site autonomy, and a wide range of security options –
Javelin
Javelin: Internet-based parallel computing using Java –
AppLes
This is an application-specific approach to scheduling individual parallel applications on production heterogeneous systems –
NASA IPG
The Information Power Grid is a testbed that provides access to a Grid – a widely distributed network of high performance computers, stored data, instruments, and collaboration environments –
Condor
This project aims is to develop, deploy, and evaluate mechanisms and policies that support high throughput computing (HTC) on large collections of distributed computing resources –
Harness
Harness builds on the concept of the virtual machine and explores dynamic capabilities beyond what PVM can supply. It focused on developing three key capabilities: Parallel plug-ins, Peer-to-peer distributed control, and multiple virtual machines –
NetSolve
NetSolve is a project that aims to bring together disparate computational resources connected by computer networks. It is a RPC based client/agent/server system that allows one to remotely access both hardware and software components –
Grid Port
SDSCs Grid Port Toolkit generalises the HotPage infrastructure to develop a reusable portal toolkit –gridport.npaci.edu/
HotPage
NPACI’s HotPage is a user portal that is designed to be a single point-of-access to computer resources – hotpage.npaci.edu/
Gateway
Gateway offers a programming paradigm implemented over a virtual Web of accessible resources -

29. Initiative
Focus and Technologies Developed
Ninf
Ninf allows users to access computational resources including hardware, software and scientific data distributed across a wide area network with an easy-to-use interface – ninf.etl.go.jp
Bricks
Bricks is a performance evaluation system that allows analysis and comparison of various scheduling schemes on a typical high-performance global computing setting – matsu-

30. Initiative
Focus and Technologies Developed
DISCWorld
An infrastructure for service-based metacomputing across LAN and WAN clusters. It allows remote users to login to this environment over the Web and request access to data, and also to invoke services or operations on the available data – dhpc.adelaide.edu.au/Projects/DISCWorld/
Nimrod/G & GRACE
A global scheduler (resource broker) for parametric computing over clusters or computational grids –

31. Many Testbeds ? & who pays ?
$grid
GUSTO
EcoGrid
Legion Testbed
NASA IPG

32. Some GRID APPLICATIONS

33. Types of Grid Applications
Sequential – dusty deck codes.
Data Parallel:
Synchronous – tightly coupled;
Loosely synchronous.
Asynchronous:
Irregular in time and space;
Difficult to parallelise to exploit the massive parallelism.
Embarrassingly Parallel.

34. Grid Applications-Drivers
Distributed HPC (Supercomputing):
Computational science.
High-throughput computing:
Large scale simulation/chip design & parameter studies.
Content Sharing
Sharing digital contents among peers (e.g., Napster)
Remote software access/renting services:
Application service provides (ASPs).
Data-intensive computing:
Data mining, particle physics (CERN), Drug Design.
On-demand computing:
Medical instrumentation & network-enabled solvers.
Collaborative:
Collaborative design, data exploration, education.

35. Distributed Supercomputing (SF-Express/MPICH-G, Caltech)
NCSA
Origin
Caltech
Exemplar
CEWES SP
Maui
SF-Express distributed interactive simulation.
100K vehicles (2002 goal) using 13 computers, 1386 nodes, 9 sites.
Globus mechanisms for
Resource allocation;
Distributed startup;
I/O and configuration;
Security.
P. Messina et al., Caltech

36. SF-Express Architecture
Local
Simulation
Router
Interest
Mgmt. IP
MPI
Create synthetic, representations of interactive environments.
Scalability via interest management.
Starting point:
MPI and socket communication;
Hand startup.

37. High Throughput Computing (parameter sweep applications)
A study involving exploration of possible scenarios - i.e., execution of the same program for various design alternatives (data).
It consists of large number of tasks (1000s).
Generally, no inter-task communication (task farming).
Large size data (MBytes+) files and I/O constraints
A large class of application areas:
Parameter explorations and simulations (Monte Carlo);
A large number of science, engineering, and commercial applications: Astrophysics, Drug Design, NeroScience, Network simulation, structural engineering, automobiles crash simulation, aerospace modeling, financial risk analysis
Condor, Nimrod/G, Distributed.net.

38. Ad Hoc Mobile Network Simulation
Ad Hoc Mobile Network Simulation: Network performance under different microware frequencies and different weather conditions – uses Nimrod.

39. Drug Design: Data Intensive Computing on Grid
Protein
Molecules
Chemical Databases
(legacy, in .MOL2 format)
It involves screening millions of chemical compounds (molecules) in the Chemical DataBase (CDB) to identify those having potential to serve as drug candidates.

40. DesignDrug@Home Architecture A Virtual Lab for “Molecular Modeling for Drug Design” on P2P Grid
Data Replica Catalogue
Grid Market
Directory
Grid Info.
Service
“Give me list PDBs sources
Of type aldrich_300?”
“service cost?”
“service providers?”
GTS
Resource
Broker
“Screen 2K molecules in 30min. for $10”
“mol.5 please?”
GTS
(RB maps suitable Grid nodes and Protein DataBank)
“get mol.10 from pdb1 & screen it.”
PDB2
GTS
“mol.10 please?”
GTS
GTS
(GTS - Grid
Trade Server)
PDB1

41. [Collaboration with Osaka University, Japan]
MEG(MagnetoEncephaloGraphy) Data Analysis on the Grid: Brain Activity Analysis
64 sensors MEG
Analysis All pairs (64x64) of MEG data by shifting the temporal region of MEG data over time: 0 to 29750: 64x64x29750 jobs 2
Data Generation 3 1
Data Analysis 5
Results
Nimrod-G 4
[deadline, budget, optimization preference]
Life-electronics laboratory,
AIST
World-Wide Grid
Provision of expertise in
the analysis of brain function
Provision of MEG analysis
[Collaboration with Osaka University, Japan]

42. SETI@home: Search for Extraterrestrial Intelligence at Home

43. Content Sharing – P2P

44. Collaborative Engineering
Access GRID:
Components of an AG Node
Digital Video
Digital Audio
NETWORK
Mixer
Control Computer
NTSC Video
RGB Video
Analog Audio
Video Capture Computer
Display Computer
Audio Capture Computer
Echo Canceller
Group to group interactions.
Human collaboration across
distributed locations
Remote visualizations, virtual meeting,
seminars,etc.
Uses grid technologies for secure
communication etc.
May have interaction with scientific apps.
Rick Stevens & Team, ANL

45. Image-Rendering

46. Parallelisation of Image Rendering
Image splitting (by rows, columns, and checker)
Each segment can be concurrently processed on different nodes and render image as segments are processed.

47. Scheduling (need load balancing)
Each row rendering takes different times depending on image nature – e.g, rendering rows across the sky take less time compared to those that intersect the interesting parts of the image.
Rending apps can be implemented using MPI, PVM, or p-study tools like Nimrod and schedule.

48. Data Intensive Computing e.g., CERN Data Grid initiative

49. CERN Large Hadron Collider - circular particle accelerator to be placed in 27 km long tunnel in 2005.

50. Conclude with a comparison with the Electrical Grid………..
Where we are ????

51. Fresco by N. Cianfanelli (1841)
Alessandro Volta in Paris in 1801 inside French National Institute shows the battery while in the presence of Napoleon I
Fresco by N. Cianfanelli (1841)
(Zoological Section "La Specula" of National History Museum of Florence University)

52. What ?!?! Oh, mon Dieu ! This is a mad man… ….and in the future,
I imagine a worldwide
Power (Electrical) Grid …...
Oh, mon
Dieu !
What ?!?!
This is a mad man…

53. = 199 Years
2000
1801

54. Grid Computing: A New Wave ?
What will be the dominant Grid approach in the next future ??

55. ”The Computational Grid” is analogous to Electricity (Power) Grid and the vision is to offer a (almost) dependable, consistent, pervasive, and inexpensive access to high-end resources irrespective their location of physical existence and the location of access.

56. Trends It is very difficult to predict the future and
this is particular true in a field such as
Information Technology
“I think there is a world market for about five computers.”
Thomas J. Watson Sr., IBM Founder, 1943

57. The time is exciting but the way ahead may be hard and long….!
Trends
Grid
The time is exciting but the way ahead may be hard and long….!

58. The Grid Impact!
“The global computational grid is expected to drive the economy of the 21st century similar to the electric power grid that drove the economy of the 20th century”

59. Future Grid Scenarios
Access to any resources, for anyone, anywhere, anytime, from any platform – portal (super) computing .
Application access to resources from the wall socket!
Many applications provide solutions in real-time.
Choice of working: office vs home vs . . .
Collaboratories for distributed teams.
Monitoring and steering applications through wireless devices (PDAs etc.).

60. Final Summary
There are currently a large number of projects and diverse range of emerging Grid developmental approaches being pursued.
These range from metacomputing frameworks to application testbeds, and from collaborative environments to batch submission mechanisms.

61. Conclusions
The HPC will be dominated by Peer-to-Peer Grid of clusters.
Adaptive, scalable, and easy to use Systems and End-User applications will be prominent.
Access electricity, internet, entertainment (music, movie,…), etc. from the wall socket!
An Economics –based Service Oriented Grid Computing computing needed for eventual success of Grids!
The impact of Grid on 21st century economy will be the same as electricity on 20th century economy.

62. Further Information Books: IEEE Task Force on Cluster Computing
High Performance Cluster Computing, V1, V2, R.Buyya (Ed), Prentice Hall, 1999.
The GRID, I. Foster and C. Kesselman (Eds), Morgan-Kaufmann, 1999.
IEEE Task Force on Cluster Computing
GRID Forums
CCGRID 2001,
GRID Meeting -

63. Further Information Cluster Computing Infoware:
Grid Computing Infoware:
IEEE DS Online - Grid Computing area:
Millennium Compute Power Grid/Market Project

64. Thank You… Any ??