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HIGH PERFORMANCE COMPUTING IN OPERATIONAL METEOROLOGY

Geoff Love

President of the WMO

Commission for Basic Systems

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OVERVIEW

• A couple of definitions

• Where we have come from

• Where we are now

• Where we might be going in the short- and longer-terms

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DEFINITIONS

• High Performance Computing: Computing performed on

a system that, at the time of its commissioning, qualified

as one of the top 500 (publicly benchmarked) systems in

terms of ability to deliver sustained floating point

operations.

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DEFINITIONS

• Operational Meteorology: “Operational” requires that

production systems are supported in a robust way (code

upgrades are easily facilitated, data management is

streamlined, visualisation tools are available, etc.) - to be

distinguished from, for example, the research environment.

“Meteorology” includes both climate and weather

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WHERE WE HAVE COME FROM ?

YEAR MACHINE GFLOP

• 1968 IBM 360 0.00065

• 1982 FACOM M200 0.006

• 1988 ETA 10P 0.12

• 1990 CRAY X-MP 0.23

• 1992 CRAY Y-MP2E 0.7

• 1993 CRAY Y-MP3E 1

• 1995 CRAY Y-MP4E 1.3

• 1997 NEC SX-4 32

• 1998 2xNEC SX-4 64

• 1999 NEC SX-5 104

• 2000 NEC SX-5 128

• 2001 2xNEC SX-5 256

A

Increase of Computer Power with Time

0123456789

1960 1970 1980 1990 2000 2010

yearlo

g10

of c

ompu

ter

pow

er

(kflo

ps)

LOG COMPUTERPOWER

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WHERE WE HAVE COME FROM ?

A

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WHERE WE HAVE COME FROM ?

•

A

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WHERE WE HAVE COME FROM ?

•

A

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SYSTEM EVOLUTION

1968 Regional analysis, regional prediction

1984 Experimental hemispheric prediction, regional

nesting

1986 Hemispheric prediction, regional prediction

1990 Global prediction

1994 Regional assimilation, global assimilation

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WHERE ARE WE NOW ?

• Global and regional 3-D variational scheme for data

assimilation.

• Global, regional and mesoscale atmospheric and ocean

forecast systems. Ensemble production.

• Air quality modelling, including a variety of chemistry

options.

• Dispersion, tropical cyclone and hydrologic modelling.

• Climate simulation, regional downscaling - eg., catchment

scale water balances.

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SYSTEM AND BASEDATE/TIME

Number ofCPUs used

APPROXIMATE START TIME

SST Analysis (REGIONAL) 1 0115 UTC 15 min

LAPS_PT375 00UTC 4/8 0145 UTC 30 min

MESO_LAPS_PT125 00UTC 8 0200 UTC 120 min

* MESO_LAPS_PT050

(SYDNEY) 00UTC4

0210 UTC 30 min

* MESO_LAPS_PT050

(MELB) 00UTC4

0230 UTC 30 min

EER and atmospheric transportcalculations from LAPSsystems

10235 UTC 55 min

WAVES (REGIONAL andMesoscale) 00UTC

1 0315 UTC 10 min

TLAPS375 00UTC 8 0355 UTC 35 min

EER from TLAPS375 00UTC 1 0500 UTC 20 min

TC_LAPS 00UTC if required 8 0500 UTC 10 min

GASP 00UTC 4/8 0630 UTC 90 min

GASP ensemble – singularvector 1 0700 UTC 120 min

GASP – ensemble prediction 3 0900 UTC 240 min

EER from GASP 00UTC 1 0730 UTC 60 min

WAVES GLOBAL 00UTC 4 0730 UTC 20 min

SPECIAL charts 00UTC 1 0930 UTC 20 min

Multi-operationalsystem environment

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Visualisation

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WHAT IS NEEDED TO SUPPORT THIS EFFORT ?

• Improving hardware, but of relatively stable design.

• Robust hardware.

• Software which can evolve to take best advantage of the

hardware but is sufficiently stable so as to support older

code, robust data management and modern visualisation

(and the like).

• Use of industry standards.

• A mechanism to develop and maintain those standards

likely to be peculiar to meteorology.

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FUTURE TRENDS

.

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FUTURE TRENDS

.

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FUTURE TRENDS

• Centres will specialise - no one will do it all.

• There will be greater, and more successful efforts to

integrate models from different disciplines.

• Systems will be improved incrementally (modular

architecture).

• End-to-end modelling, including data quality monitoring,

assimilation, analysis and prognosis, visualisation,

archival, product generation and dissemination will occur.

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FUTURE TRENDS

• The ultimate goal is clearly earth-system simulation

• The ultimate architecture would appear to be clusters of

powerful computing and data storage environments (the

level of interaction between modules, and time-critical

nature of the various applications / modules will drive

processor power-proximity relationship).

• Data management in meteorology will accommodate

explosive increases in data volumes, and be synergistic with

other geophysical modelling efforts.

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After:http//www.top500.org

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After: http//www.top500.org

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FUTURE TRENDS

• There will always be a role for operational meteorology -

and a need for operational high performance computing.

• Operational meteorology will also be a component of a

more integrated whole.

• There will need to be significantly greater collaboration

across the boundary between meteorology and the other

geophysical and biological scientists performing earth-

system simulation. This interaction will grow in time.

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The operational meteorologists (short) wish list:

• Keep the hardware improving according to Moore’s

law;

• Maintain a software environment that protects our

existing investment in model code;

• Provide the capability to manage and visualise the

increasingly large datasets that models and remote

sensing are providing.

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THANK YOU