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HPC challenges in Switzerland

Marie-Christine Sawley

General Manager CSCS

SOS8, Charleston April, 122003

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A short history of CSCS

1991- 1999

National service with a wide customer base

Since 2000

National service with strong leadership in computational science

2004-2010

National service with strong leadership for IT and scientific

computing support and development

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Outline of the presentation

• Brief recap on present status

• Strategy 2004-2007

• Major choices and challenges

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CSCS Autonomy

• Unit of ETHZ managed under performance

mandate and global budget

• New business models

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Driving forces

CapabilityAbility to serve the projects of the highest scientific quality requiring intensive resources

Sustainability

Clear line of funding, economy of scale and total cost of ownership

Scalability

Streamlining a set of services from the desktop to highest end servers

Flexibility Capacity to evolve according to the pace of technology

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New thrust areas for scientific computing

Discipline Description

Visualization Imaging, virtual reality,

Numerics & Benchmarking Optimisation, selection and development of solvers and

other mathematical methods

Data Intensive Computing Data mining, knowledge management, information

management and retrieval, machine learning,

geographical information systems

Grid and Distributed

Computing

Grid computing, networking, communications, agents,

distributed services

Visiting scientists program Organisation of courses and summer schools, visiting

scientists

Modelling Framework

Support

Hosting and fostering a software framework that is being

used as the community model of a research discipline

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CSCS in 2007

HPCN31%

Scientific computing

59%

Administration

8%

Expertise development at CSCS

CSCS Today

HPCN65%

Scientific computing

15%

Administration20%

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Usage by field, 2003

Bio/Chemistry9%

Engineering26%

Material Science

8%

Physics16%Mathematics

0%

Environment41%

PVP NEC SX-5

MPP IBM Power4

Bio/Chemistry51%

Environment9%

Material Science

32%

Mathematics0%

Physics7%

Engineering1%

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CSCS configuration

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HB networksmake locality less of an issue

ETHZ

•HP Superdome

•256 Opteron Cluster

EPFL

•HP SC 45, 100 Alpha

•Origin 3800 128 Mips

•100 P4 Cluster

UNIZH

•zBox 288 Intel IA32

•512 Opteron Cluster, myrinet

PSI

•64 Opteron Cluster

CSCS

•NEC SX5 16 Vector

•p690 IBM 256 Power4

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Meteo and clima modelling frameworkEach day, MeteoSwiss produces its numerical weather predictions, including daily operational short range weather forecasts and research activities are run at CSCS.

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Biological material modelling(prof. M. Parrinello)

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Fundamental CFD (prof. L. Kleiser)

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Particle physicsLHC in CH

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Roadmap

03 04 05 06 07

HEP

Bio

AstrophysReactor phy

SMP/vector Next generation

08

MPP

Visualization

Funding

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Risks and challenges

• Scientific group needs

– Facilitate multi disciplinary

collaboration

– Improve operating efficiency

– Tools for extracting scientific

information from complex and

massive data

• IT Needs

– Optimize Infrastructure,

computing on demand

– Integrate distributed resources

– Enable data access, integration

and curation

• Risks

– Dispersion of resources

– Not enough impact

– Balkanisation

• Weaknesses

– Insufficient coordination

– Resource allocation procedure

• Opportunities

– Establish a strong collaboration

platform

• Strengths

– Scientific portfolio

– Flexible organizations

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Please visit us

• On www.cscs.ch

• And for SOS9, March 2005