nguyen tuan anh page 1 grid computing – master course 2008 grid computing dr. nguyen tuan anh...
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Nguyen Tuan AnhPage 1Grid Computing – Master Course 2008
Grid Computing
Dr. Nguyen Tuan Anh
Contacts: Email: [email protected] Tel: (84-8) 8647256, ext. 5840
Faculty of Computer Science and EngineeringHo Chi Minh city University of Technology
Nguyen Tuan AnhPage 2Grid Computing – Master Course 2008
Course objectives
Understand “Grid” concepts
Roles of “Grid” in our modern society
Grid architectures
Understand Grid related technologies Security Web services Grid services and standards
Ways to efficiently exploit the Grid power Programming models
“Know-how” Programming the Grid
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Evaluation
Self study and self research Active Efficient
Practical exercises and seminars: 50% Exercises Seminar: each group will study a Grid-related topics and present this in the
class
Final exam: 50%
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References
Lecture notes http://www.cse.hcmut.edu.vn/~tuananh/courses/Grid
Books I. Foster and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure.
Morgab Kaufmann Publishers, 1999. Maozhen Li, Mark Baker, The Grid Core Technologies, Wiley, 2005. Fran Berman, Anthony J. G. Hey and Geoffrey C. Fox, Grid computing: Making the
Global Infrastructure a Reality. John Wiley & Sons Ltd, 2003.
Luis Ferrelra et al. Grid Services Programming and Application Enablement. IBM Redbooks, 2004.
Mark Endrei et al. Patterns: Service Oriented Architecture and Web Services. IBM Redbooks, 2004.
Web links: Globus project: http://www.globus.org/alliance/ Global Grid Forum: http://www.ggf.org
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Grid introduction
Nguyen Tuan AnhPage 6Grid Computing – Master Course 2008
CERN
CERN (founded 1954) = “Conseil Européen pour la
Recherche Nucléaire”
“European Organisation for Nuclear Reseach”
27 km circumference tunnel
Large
Hadron
Collider
Concorde(15 Km)
Balloon(30 Km)
CD stack with1 year LHC data!(~ 20 Km)
Mt. Blanc(4.8 Km)
50 CD-ROM
= 35 GB
6 cm
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Un little bit of history …
I.Foster and C.Kesselman come from the parallel computing field Parallelism
1970-80 : The pioneers– Vectorial computers (Cray 1, Cray 2,..)
1980-90 : The exuberance Massively Parallel Computers (CrayT3D/T3E, Connection Machine,…)
1990-2000 : The profit Cluster (Beowulf, ASCII Red,..)
2000 ->? The Globalization GRID Global Computing
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Overview
Grid concepts
Challenges and issues
Grid middleware
Grid applications
Grid projects
Future directions
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Part I: concepts
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What is “Grid”?
1001 definitions HPC researchers
Connect supercomputing sites Distributed supercomputing
Web engineers Stateful web services for accessing resources Next generation of the Internet and Web
Companies Services accessible by other users Portal to access local resources
Users Like electrical grid
…
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Grid environment
11
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« Grid » domains
Originally To link together supercomputing sites
Today Collaborative engineering Data exploration High-throughput computing Distributed high performance computing
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A little bit of vocabulary
Usually one distinguishes three types of GRID
Knowledge GRID To share knowledge Idea: Virtual distributed laboratory
Data GRID To share the data Idea: Large scale data storage
Computing GRID To share computing power Idea: Alternative to supercomputers
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The GRID today -1
Knowledge GRID Virtual distributed Institutes/Laboratories allowing remote people to collaborate as
they would be at the same location
Purpose: to share knowledge, to collaborate for researches or specific activities
Few specific tries Remote surgery ….
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The GRID today - 2
Data GRID Also referenced as « peer-to-peer » technology
Versus to the « Client/Server » technology who dominated the market of distributed systems during last decades, with this approach every participant is both client and server
Nobody knows exactly where the data are The system figures to find the nearest requested data out
The requested data could be distributed on several location and same data could be located at several places (data coherence problem)
The pursuit of the data is transparent to the user Some examples:
Napster, Gnutella, pirate software, Project DATAGRID (CERN),…
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The GRID today - 3
Computing GRID A supercomputer on you the table of your kitchen …
Some facts Supercomputers are very expensive and age very rapidly Except for some very specific persons, we do not need a supercomputer every day…
… but when we need one it is very frustrating not to have one ! The total time personal and other computer waste time not doing anything is huge I am (almost) permanently connected to a lot of computers. Potentially I am permanently connected to a supercomputer
First try to exploit this fact: Projet seti@home
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GRID computing : different views
Virtual Supercomputing An association of several supercomputers geographically distributed (10-
1000) Each node is a parallel machine managed through a scheduling system
(batch) To provide a virtual supercomputer
Internet computing A combination of a large number of PCs
(10000 - 1000000) To exploit unused computing
Metacomputing An association of several servers providing a set of applications
Thierry Priol
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“Grid” vs. cluster computing
“Partial view” vs. “Global view” of the environment
Large scale, geographically distributed
Non-structured
Heterogeneous
Dynamic, unstable
Multiple administrative domains
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Supercomputer
PC
Supercomputer
My laptopMy laptop
Workstation
SMPCluster
Computing Grid: our goal
?
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The dream
To make computers user friendly: To switch from a program centric view…
« Execute this program on this (these) machine(s)»
to a service centric view… « Provide me this service with this QoS level »
Today the WEB provides access to a large amount of documents and data BUT…. Access is not transparent…. URL To find the correct information is a tedious work… search engines
The GRID will change our way to use computer as many drastically
that WEB did more than 10 years ago
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New characteristics
Large-scale Need for dynamic selection Partial view of the environment
Heterogeneity Hardware, OS, network, software environments (languages, libraries, tools...)
Complex unpredictable structure
Dynamic unpredictable behavior
Multiple administrative domain no centralized control
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Challenges
Efficient exploitation of Grid performance New programming models Service-centric vision
Resource connectivity Middleware services Applications
Interoperability vs. performance Good interoperability -> (very) slow Fast -> not so interoperable
Grid scalability Resource management mechanisms/models
Large number of heterogeneous resources
Grid infrastructure and Grid application evaluations How to benchmark Grid systems and applications
Trust and security How to trust the environment How to protect sensitive data
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Part II: Grid Middleware & components
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What is Grid middleware
System software between applications and OS Provide services to applications
Discovery Execution Storage Data movements Information Service integration ... Failure detection and recovery Resource monitoring ...
Hide all complexities of the Grid environment
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Grid layered architecture: principle
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Grid architecture
Fabric layer Physical resources
Computers/ computing platforms Data storages Sensors Network
Layered on top of local OS
Resource & connectivity protocols layer Provide access to resources and services in the fabric layer Security management
Authentication Authorization Secure communication
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Grid architecture
Collective service layers Facilitate the use of resources/services Provide meta-services
Resource discovery Resource brokers Failure detection ...
User application layers Grid applications
Parallel applications Service-oriented applications ...
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Community Grid Architecture Model
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Service-centric view: Grid environment
Physical Environment
Security• Authentication• Authorization• Policy implementation
Resources• Virtualization• Management• Optimization
Execution Management
• Execution Planning• Workflow• Work managers
Provisioning• Configuration• Deployment• Optimization
Data• Storage Mgmt.• Transport• Replica Mgmt.
Virtual Domains
• Service Groups• Virtual Organizations
Physical Environment
• Hardware• Network• Sensors• Equipment
I nfrastructure Profile
• Required interfaces supported by all services
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Virtual organization (VO)
Grid environment can be organized as VOs VO: groups of services/resources
Similar characteristics Location/site Functions
A VO can a part of a bigger VO
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Grid evolution
1996
GT1.0
Proof of concept
1999
GUSTO testbed
2002
GT3.0OGSA
2005
GT4.xWSRF
GGF
Standardization
-Basic services?-Security issues
- Grid architecture- Grid interoperability
Globus Toolkit !!!!http://www.globus.org
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Globus layered architecture
Applications
Core ServicesMetacomputing
Directory Service
GRAMGlobus
Security Interface
Heartbeat Monitor
Nexus
Gloperf
Local Services
LSF
Condor MPI
NQEEasy
TCP
SolarisIrixAIX
UDP
High-level Services and Tools
POP-C++ globusrunMPI Nimrod/GProActive CC++
GlobusView Testbed Status
GASS
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Globus Toolkit 4x
Sustainable changes on the services interoperability and infrastructure Open Grid Services Architecture (OGSA)
Stateful Web Services Enable the integration of user specific Grid
services Define standard interfaces
How to access Grid services Disadvantage
Slow
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GT: Core service architecture
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Globus Toolkit
Grid Service Specification How to write, publish and use a Grid service
GT components: GT core
Meta-services used to implement other services and service behaviors (e.g. service creation, destruction)
GT base services Use the GT core to implement Grid capacities: resource
management, information services, data transfer, etc. Other Grid services
Implemented by user to enable some enhancement capacities
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GT: from other perspectives
GT containerGT security
Local-level services WS GRAM
Fork PBS LSF
GridFTP RFTP
…
VO-level services Information service…???
create
create
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What GT DOES NOT address
GT focus on accessing local resources
Things still missing Coordination services
Resource/service discovery Information collection Resource connectivity Programming models/tools
Things to be improved Performance!
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Part III: Grid security
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Grid security: a scenario
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Symmetric key
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Asymmetric cryptography
UniqueMathematical relation
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How to guarantee the information integrity?
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Digital Signatures
A message signed by the private-key
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How to identify users?
(User authentication)
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Authentication models
Direct-trusted model Third-party trusted model
Sender Receiver
1: Register sender’s public key
2: store trusted public key
3: message M
4: sign(M) with sender’s private key
Key repository5: public key existed?
Sender Receiver
Trusted authority
Digital certificate
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Digital certificate
Based on asymmetric cryptography
Consist of Public key User identity information (user name, organization, address, …) One or more digital signature signed by some well known Certificate
Authority (CA)
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Certificate authority
Responsible for Positively identify entities requesting certificates Issuing, removing, and archiving certificates Protecting the Certificate Authority server Maintaining a namespace of unique names for certificate owners Serve signed certificates to those needing to authenticate entities Logging activity
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Access the Grid
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Grid authentication
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Grid Delegation
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Delegation
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Grid authentication and delegation
Source: Ian Foster et al: A security architecture for computational Grids
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Part IV: Grid applications
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Computing GRID: the issue ….
Supercomputer, cluster,… How to extract the 99,999999% of the computing power of my limited powered expensive
environment
GRID environment How to extract the very power I need from the theoretically infinite powered cheap
environment
Consequence Speedup/efficiency curves are not any more relevant information..
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Grid vs. Cluster computing from application view
Cluster Have applications, build a cluster for those applications High efficiency but expensive
Grid infrastructure Have existing platforms, find applications that can efficiently run on those
platforms Cheap but not well tailored to every application
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Types of Grid applications
Type 1: Traditional HPC applications running within a site (VO)
Using traditional models (MPI, PVM,…) Ready-to-run, no need to modify/re-compile Role of the Grid middleware
– Resource discovery – Deploy and run the application remotely, securely on the discovered resource
Nguyen Tuan AnhPage 57Grid Computing – Master Course 2008
Types of Grid applications
Type 1: Traditional HPC applications running within a site (VO)
Using traditional models (MPI, PVM,…) Ready-to-run, no need to modify/re-compile Role of the Grid middleware
– Resource discovery – Deploy and run the application remotely, securely on the discovered
resource
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Types of Grid applications
Type 2: New HPC applications running across multiple sites (VOs)
Require new programming models/tools– Multiple level parallelism– Embracing parallelism
Example: bio-informatics, parameter sweeping Huge speedup can be achieved
Very few applications Role of the Grid middleware
Resource discovery Resource allocation and co-allocation Application supporting services Dynamic deployments and executions of application components
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Issues
Missing high-level services QoS of resources
Heterogeneity
Code portability Binary/Byte code or source code?
Resource connectivity Firewall/NAT/ Virtual IP
Fault tolerance Resource volatility
Data protection Protect sensitive data from stealing
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Part V: Grid in the world
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United Kingdom
E-Science, 215M€ over 5 years e-Science will refer to the large scale science that will increasingly be carried out through distributed
global collaborations enabled by the Internet.
1 - National Network of Grid Centers
2 - Development of Generic Grid Middleware
3 - Support for e-Science Projects.
e-Science support centre
Grid Network Team
Grid Engineering Task Force
Newcastle
Edinburgh
Oxford
Glasgow
Manchester
Cardiff
Southampton
London
Belfast
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Germany
D-GRID, 100M€ over 5 years (2005-2009) More than 100 academia and industry partners
Phase 1 -> 2008: Construction of a GRIDinfrastructure, development of themiddleware and a pilot to runGRID applications
Phase 2: the GRID infrastructure will beused to run e-science(enhanced science) projects
In close collaboration with IBM
Stuttgart
Leipzig
Berlin
Frankfurt
Karlsruhe Garching
Kiel
Braunschweig
Dresden
Aachen
RegensburgKaiserslau
tern Augsburg
Bielefeld
Hannover
Erlangen
Heidelberg
IlmenauWürzb
urg
Magdeburg
Marburg
Göttingen
Oldenburg
Essen
St. Augusti
n
Rostock
Global UpstreamHamb
urg
10 Gbit/s2,4 Gbit/s622 Mbit/s
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Nederland
Virtual Laboratory for e-science (VL-e), 55 M€ over 5 years 21 partners in 19 institutions
The mission of the VL-E project is: To boost e-Science by the creation of an e-Science environment and doing research on methodologies.
The strategy will be: To carry out concerted research along the complete e-Science technology chain, ranging from applications to
networking, focused on new methodologies and reusable components.
The essential components of the total e-Science technology chain are: e-Science development areas, a Virtual Laboratory development area, a Large Scale Distributed computing development area, consisting of high performance networking and grid parts.
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France
ACI-GRID, ~8 M€ 2001-2004 Based on « call for proposals » Use RENATER network
GRID 5000 Building a nation wide experimental platform for Grid researches (like a particle accelerator for the
computer scientists) 10/11 geographically distributed sites, every site hosts a cluster (from 256 CPUs to 1K CPUs) All sites are connected by RENATER (French Academ. Network) RENATER hosts probes to trace network condition load Design and develop a system/middleware environment for safely test and repeat experiments Only experimental platform (no production)
R eimsC aen
Rouen
Ren nes N ancy
S tras bourg
Po it ie rs
Bo rd eaux
L yon
G renob le
Tou lou se .
Mon tpellie r
Marseille
N antes
B esan çon
C lerm ont -F errand
Lim oges
P aris
D ijon
L il le
S oph ia
C om piè gne
O rlé ans
C orte
2 .4 Gbi t/s
622 Mbi t/s
155 Mbi t/s
34 M bi t/s
8 M bit/s
N R D
N IO
N O C
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Europe - CERN
DATAGRID 10M€, ended beginning 2004 21 partners Feasibility project, final test bed
1000 computers, 15 Terabytes on 25 sites
Followed by…
EGEE, 4 years, 40 M€ for the first two years 70 partners in 27 countries To provide the necessary storage and computing infrastructure to LHC (and others..)
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…and at HCMUT….
Nguyen Tuan AnhPage 67Grid Computing – Master Course 2008
VN-Grid: toward a national-scale computing Grid
Main focus: infrastructure High-level services
Resource discovery and reservation Scheduling VO and policy management
OGSA and WSRF compliance Programming support
MPI POP-C++
We do not develop from scratch! Using GT for providing base services
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A VN-Grid scenario
Site
Resource Discovery
ResourceAllocation/Reservation
Scheduling
Learn
in
g
Data warehouse
Monitoring
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Our first prototype-to-be-built
Keep in mind the heterogeneity the dynamics “Virtual site” concept (VSite) Combine the flexibility of P2P technologies (partial view assumption) with the efficiency of
centralized management on each VSite Flexible to involve more resources Flexible security management
Multiple level authentication and authorization (VO, user,…)
Programming supports Parallel object model (POP-C++) MPI
Applications Oil exploitation (geo-physic data computation of oil fields) Supraconductor study Aviation Chip Design
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VN-Grid testbed
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Other projects
Factors that could lead to the success of VN-Grid SuperNode
POP-C++
EDAGrid
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Supernode project
Building HPC system with programming supports
Supernode 1 (1998-2000) Supernode 2 (2004-2006)
• 4 Nodes• Configurable network topology• MPI interface
• 64 Nodes (dual Xeon)• Fast network (32 links, 1Gb/s each)• 330 GFlops effective performance• MPI interface
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User Management and Billing
User
Proxy
Resource Management Job Execution
Job ManagementMonitoringScheduling
Supernode II Architechture
Remote Terminal
Request/Result
Proxy
Supernode II
Transparency!
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Supernode II: tools
Nguyen Tuan AnhPage 75Grid Computing – Master Course 2008
Object oriented application
POP-C++: Parallel Object Programming
Grid environment
ObjectObj
Object
ObjectObject
Object
• Heterogeneous• Large scale• Unstructured• Dynamic and unknown topology
• Distributed objects• Heterogeneous
execute
http://www.eif.ch/gridgroup/popc
Object
ObjectObject
Obj
Object
Object
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Parallel object by extending C++
Computational environment
POP-C++ essential service abstractions
Globus Toolkit XtremWebStandalone POP-C++
GridWeb
computing
Testing Distributed
environment
Other toolkits
Other distributed
environments
POP-C++ programming
POP-C++ services for
Globus
POP-C++ services for XtremWeb
POP-C++ services for
testing
Other customizable
services
parclass Foo {
Foo() @{ od.power(100);};
async conc void MyMethod();
};
parclass Foo {
Foo() @{ od.power(100);};
async conc void MyMethod();
};
class Foo {
Foo();
void MyMethod();
};
class Foo {
Foo();
void MyMethod();
};
Foo::Foo() { ... }
void Foo::MyMethod(){...}
Foo::Foo() { ... }
void Foo::MyMethod(){...}
POP-C++C++
Shared implementation
Grid ProgrammingGrid Programming
Grid infrastructure
• Transparent, requirement driven object allocation• Various method invocation semantics
Archi
tectu
re
Archi
tectu
re
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EDAGRID
Computing Grid for microchip design Synthesis and optimization
Smaller Faster More power efficient Self verification
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Behavioral Specification
RTL Description
Translation
Logic Optimization
Technology Mapping
Optimized Logic Description
Unoptimized Logic Description
Microchip design processProduct Requirement
Physical Design(back-end)
Library
Constraints
GRID
MIDDLEWARE
Supercomputer, PC-Cluster
Data-storage, Sensors, Experiments
Internet, networks
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Future directions
OGSA/WSRF based services
Target Grid environment Data Grid or service Grid or computing Grid?
Global services Grid topology Resource discovery Distributed information system Resource connectivity Fault tolerance
Local services Acquire resource information Security management
Grid enabled Applications Programming models Supporting tools
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Nguyen Tuan AnhPage 83Grid Computing – Master Course 2008
GT: Core service architecture
Nguyen Tuan AnhPage 84Grid Computing – Master Course 2008
Globus Toolkit
Grid Service Specification How to write, publish and use a Grid service
GT components: GT core
Meta-services used to implement other services and service behaviors (e.g. service creation, destruction)
GT base services Use the GT core to implement Grid capacities: resource management, information services, data
transfer, etc. Other Grid services
Implemented by user to enable some enhancement capacities
Nguyen Tuan AnhPage 85Grid Computing – Master Course 2008
What GT DOES NOT address
GT focus on accessing local resources
Things still missing Coordination services
Resource/service discovery Information collection Resource connectivity Programming models/tools
Things to be improved Performance!