Grid: New Business Opportunities?

GRID: new business opportunities?

Dominique Thomas

Software Development Manager
Processing & Imaging Product Line – R&D

Compagnie Generale de Geophysique Veritas
(CGGVeritas)

October 12, 2007 - D Thomas CyberInfrastructure Summit, Banff, ab Slide 1

Evolution to the Grid

€€€€

€€€

€€
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The Grid Dream

G
Mobile R Supercomputer, PC-Cluster
Access I
D

M
I
Desktop D
D Data Storage, Sensors,
L Experiments
E
W
A
R
Visualizing E
Internet, Networks
Analogy with the electrical supply network
Geographically distant resources
Secure environment
“Coordinated resources sharing and problem solving in dynamic,
multi-institutional virtual organization” – Ian Foster 2001

Outline

HPC trends

European Projects:
BEinGRID, EGEE, GEANT2

CGGVeritas Challenges

Cluster to Grid Computing

EGEODE


HPC market trends

2005: $2.1B
2005: $2.1B
2010: $2.5B
2010: $2.5B

High-end
High-end

Volume
Volume

2005: $7.1B
2005: $7.1B
2010: $11.7B
2010: $11.7B

Sys. Size
Sys. Size 2005
2005 2010
2010 %
%

$250k~$1M $1.9B
$1.9B $3.4B
$3.4B 11.8
$250k~$1M 11.8
$2.9B
$2.9B $4.9B
$4.9B 10.7
$50k~$250k
$50k~$250k 10.7
$2.2B
$2.2B $3.4B
$3.4B
$0~$50k
$0~$50k 9.6
9.6


Exponential Growth

Optical Fibre Gilder’s Law
Performance per Dollar Spent

Doubling Time (bits per second) bandwidth
(months)
(32X in 4 yrs)
9 12 18
Data Storage
(bits per sq. inch)
Storage Law
(16X in 4yrs)

Chip capacity
(# transistors)
Moore’s Law
procesing
power
0 1 2 3 4 5
(5X in 4yrs)
Number of Years

Triumph of Light – Scientific American. George Stix

HPC Segments


PC technologies analysis


Lost in transition ?


Grid Technology Adoption Life-cycle

The Chasm
Main Street

Initial Market
BEinGRID bowling

Grid
Science
Computing
The tornado
Next Generation Grid
Enterprise Applications

Grid Enterprise
Service Oriented The Bowling Infrastructure
Utility for the Alley (on-demand)
Niche
Knowledge Marketing
Economy
Early Early Late Laggards
Innovators Adopters Majority Majority (skeptics)
(visionaries) (pragmatics) (conservatives)


BEinGRID: Business Experiment in Grid

BE1 - Computational Fluid Dynamics and Computer Aid Design
BE2 - Movie Post-Production Workflow
BE3 - Visualisation and Virtual Reality
BE4 - Financial Portfolio Management
BE5 - Retail Management
BE6 - Groundwater Modeling
BE7 - Earth Observation
BE8 - Integration of Engineering and Business Processes in Metal Forming
BE9 - Distributed Online Gaming
BE10 - Collaborative Environment in the Supply Chain Management for Pharmaceutics
BE11 - Risk Management in Finance
BE12 - Sales Management System
BE13 - Textile Grid Portal
BE14 - New Product & Process Development
BE15 - Data Recovery Service
BE16 - Ship Building
BE17 - Logistics & Distribution Optimisation
BE18 - Seismic Processing and Reservoir Simulation


BEinGRID Logistics
MultiMedia Experiments
by sectors
SP
SP Finance
Experiments Oil & Gas Automotive
by technology
Chemistry

Integrator End-
User
SP
Service
Provider

Retailing
Business Experiment
Value Chain
Aerospace SP
SP Textile
Engineering
Ship Environmental
Building Science Government - Public
service

BEinGRID Approach

BE1 BE2 BE3 BE4 BE5 BE18

Trust & Security ...

Architecture & Interop
Technical
cross
activities Service & Data Mgt
.
.
.

VO Management
Repository

Market Study
Business
cross Business Modeling
activities .
.
.

Dissem. & Exploitation
Mdw-1 Mdw -2 Mdw -n
Selected branches: GTv4, UNICORE/GS, g-Lite, GRIA, WS-*


Grid Technology Adoption Life-cycle

The Chasm
Main Street

Initial Market
BEinGRID bowling

Grid
Science
Computing
The tornado
Next Generation Grid
Enterprise Applications

Grid Enterprise
Service Oriented The Bowling Infrastructure
Utility for the Alley (on-demand)
Niche
Knowledge Marketing
Economy
Early Early Late Laggards
Innovators Adopters Majority Majority (skeptics)
(visionaries) (pragmatics) (conservatives)


Grids for Science

Grids provide access to:
Very large data collections
Terascale computing resources
High performance visualisation
Connected by high-bandwidth networks

Grids support global collaborations enabled by the
internet


The European e-Infrastructure

EGEE: Enabling Grid for E-sciencE
GEANT2 Network Collaboration

Operations, Support and
• To underpin European science and
technology in the service of society
• To link with and build on
– National, regional and
Pan-European Grid
international initiatives
• To foster international cooperation

training
– both in the creation and the use
of the e-infrastructure

• One of the largest worldwide Network infrastructure
grid infrastructure to date linking resource centres

EGEE worldwide cooperation

In ~80 countries in 2008


GEANT2 Network(World wide)


1 TByte between 2 points
Line type Bandwidth Duration
theoretical
Internet 2Mb/s 45 days
100Mb/s 22 hours
1Gb/s 2.2 hours
Experimental Best in France 10Gb/s 13 minutes
Carriocas 40Gb/s 3.3 minutes

Line type Bandwidth Actual Duration
actual
EGEE- 2Mb/s 1.8Mb/s 49 days
CGGVeritas
Marseille-Lyon 2.5Gb/s shared 88Mb/s 1 day
CGGVeritas 100Mb/s 41Mb/s ! 2 days
CERN-Caltech One stream (2006) 2,38Gb/s 1 hour
(10000km) Multiple streams 5,44 Gb/s 30mn
(2003)

EGEE: Enabling Grid for E-sciencE

240 sites/ 45 countries
~40000 CPUs / 5 PBytes
200 VOs

Sep 07


EGEE in motion
24/7 available, secure access
Generic grid, multiples local scheduler supported
Data storage and replication mechanism
1000 persons/60 middleware developers
Open source
Up to 100,000 jobs a day,
More than 1 million jobs per month

Global scheduling


Grid Applications
High Energy Physics (analysising the
results from particle collisions )

Medical/Healthcare (imaging, diagnosis
and treatment )

Bioinformatics (study of the human
genome and proteome to understand
genetic diseases)

Nanotechnology (design of new
materials from the molecular scale)

Engineering (design optimization,
simulation, failure analysis and remote
Instrument access and control)

Natural Resources and the
Environment (weather forecasting,
earth observation, modeling and
prediction of complex systems)

High-end example: The LHC Experiments

ATLAS CMS

~6-8 PetaBytes / year
~108 events/year
~103 batch and interactive users

LHCb

Just a comparison…

6-8 Petabytes 5 times the
˜10.000.000 CD-ROM Eiffel Tower
˜1500 m
Produced each year


Grid Applications: Earth Observation

ENVISAT
• 3500 Meuro programme cost
• Launched on February 28, 2002
• 10 instruments on board
• 200 Mbps data rate to ground
• 400 Tbytes data archived/year
• 10+ dedicated facilities in Europe
• ~700 approved science user projects


Earth Science Requirements
First guess Optimal Global, regional, local multi-
re
Trajectory
Coupled
interdisciplinary
mo
sp
he
disciplinary applications
processes Large historical distributed
At

Complex Noisy archives
Cryosphere data observations
analysis Near real-time access to
Biosphere data
n
ea

Integrate different data
Oc

sources
Science, institutional and
industrial communities
Models to provide long term
Sub-surface trends and forecast
complex
modelling Complex
web of
sensor System-level science


And Seismic Processing?


CGGVeritas is the world’s leading international
pure-play geophysical company delivering a wide
range of technologies, services and equipment to
its broad base of customers mainly throughout the
global oil and gas industry

Focused on Performance . Passion for Innovation . Powered by People . Delivered with Integrity


CGGVeritas in the Oil & Gas Industry

Reservoir services
Spec data

Processing
(software, site design
& services)

Acquisition
(equipment & services)


Data Processing & Imaging

Stavanger
Oslo Oslo
Calgary
Aberdeen
London Moscow
Crawley Assen
Paris Vienna
Milan
Pau

Houston
Tripoli Abu Dhabi
Cairo
Villahermosa MuscatMumbaï
Caracas
Lagos Kuala Lumpur
Maracaibo / PLCruz
Port Harcourt Singapore
Jakarta
Luanda
Rio

Perth
Buenos Aires

28 Open Centres

15 Single-Client Dedicated Centres


Worldwide R&D

London Tyumen
Calgary
Brno
Paris
Houston
Mumbai
Mexico

Singapore


Challenges (1): Computing power

CGGVeritas Gflops evolution vs Moore law

1000000

100000
Gflops (logarithmic scale)

10000
Gflops@CGGVeritas
Moore (vector)
1000 Moore (numa)
Moore (cluster)
Gflops trend
100

10

1
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008


Storage and Computing

1 Pflops in 2009?

400+ TFlops in 2007
8 PBytes of disc


Challenges (2): Technology based strategy

Technical excellence
Research – Innovation – Industrialization

Looking for Talents with strong scientific background
Collaboration with Research Labs


Cluster to Grid Computing
More Computing&Storage resources to solve
complex problems such as full wave equation in complex
earth models

To optimize IT infrastructure
Load balancing between Processing Centres
Smoothing peaks of production (up to 100 TFlops)
Service continuity
Better fault tolerant system and applications

To share and acquire knowledge
Best practices and programming models
Attract and keep talents (researchers)


Business value

Short term
Ability to reach new customers:
SMEs and middle size National Oil&Gas Companies
Innovative and simple route for R-I collaboration

Longer term
Leading Edge technology => competitive advantage
Lehman Brothers & Smith Barney

Capital Expenditures
G$ Exploration & Dev.
Association for the Study of Peak Oil & Gas 250
215 G$
191 G$
200
166 G$
2015-2025
150

100

50

0
2003 2004 2005 (e)

Innovation

Pre-competitive research: experiment
Develop and share technical expertise
Assess maturity of technology for operational / business
projects
Feedback from Industry to Research

eInfrastructure: the foundation
Real scale, production-quality Grid
Network
Computing resources
Middleware
IT administration

Experiment with the future


Innovation and Business? EGEODE initiative

Collaboration Research - Industry
EGEODE V.O. (Expanding Geosciences On Demand)
Share Hardware and state of the art Software (Geocluster®)

WITHOUT software and IT administration
overhead

eInfrastructure for Research: EGEE (gLite)
Performances, IT adm, Training
Open to any Public-Private Lab

eInfrastructure for Business: CGGVeritas (gLite)+partners
Security, confidentiality, reliability

More effective worldwide collaboration R-R-I

EGEODE Portal

EGEODE VO

Portal

SDS grid ETools GCT
BEinGRID

Production
GRID DEV
Collaborative Middleware GGS
EGEE

Operating System
Hardware
Network

Slide 39

EGEODE

With EGEODE:
Any Geophysicist can process Any data
from Anywhere at Anytime

AAA enabled
(Authentication, Authorization and Accounting) 7/24/365
(dynamic upgrade)
VO centric (Virtual Organisation)

Remote center
Client location Referenced in the Grid File System
Home Copy (GridFTP), Replication,…


EGEODE : Example of seismic processing workflow

•Velocity •Time •Depth
•Pre-processing •Reservoir
•Analysis •Imaging •Imaging
•(1D, 2D) •Geophysics
•(1D,2D,3D) •(3D) •(3D)

•Rock properties
•Run on EGEODE

•3D seismic •Velocity model •Structural model

Production

Remote processing from small dedicated centers
Collaborative session with the client
Remote Internship with University
Intranet remote processing with Pau, Moscow, Oslo


New Business Opportunities

Business Model
1. Sell Computing-On-Demand (COD) services
– Value chain
CGGVeritas

Grid Grid Grid

Component Resource Operator User

Provider Provider

2. Provide EGEODE services to SMEs using a WEB
portal
– Value chain
BE18 Association (CGGVeritas, TNO, NICE, Petrosoft)

Grid Grid Solution
Grid Access
Component Resource (Service) User
Provider Provider Operator Provider Provider


Business Aspects

Business Plan
1. Computing-On-Demand services
Sell unused compute resources through a COD service
– Market: O&G companies
~9500 O&G Companies
– Success factors:
Low and simple pricing strategy
IT resources optimization and High availability
Increased business flexibility
More reactive to the market shifts and greater market penetration
Rapid decision-making

NO demand from large organizations to offload to someone else’s
No need for interoperation between them

Demand is coming from SMEs


Business Aspects

Business Plan
2. Expanding-Geosciences-On-Demand (EGEODE)
services

– Market: small O&G structures
1035 O&G companies in EU CGGVeritas market

93% are SMEs; 63% < 10 employees High Tech.,
Large studies
Research labs
Very small projects of large companies EGEODE market

– Success factors:
Conventional, smalll
Simplified administration and IT resources optimization
Capacity to meet market shifts and increase business flexibility
Cost-effective and fast data processing


Summary Grid

Cooperation with EGEE and BEinGRID:
learn and experiment

Innovation creates Business Value

Collaboration Public-Private Research is a must

EGEODE : an enabler …

EGEE : http://www.eu-egee.org
EGEODE : http://www.egeode.org
CGGVeritas : http://www.cggveritas.com

Grid: New Business Opportunities?

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