DMI Update

DMI UpdateWWW.DMI.DK

Leif Laursen ( [email protected] )

Jan Boerhout ( [email protected] )

CAS2K3, September 7-11, 2003

Annecy, France

Danish Meteorological Institute

• DMI is the national weather service for Denmark, Greenland and the Faeroes.

• Weather forecasting, Oceanography, Climate Research and Environmental studies

• Use of numerical models in all areas

• Increased used of automatic products

• Demanding high availability of systems

32 Kbyte/s

10 Mbyte/s

24 processor

SGI

ORIGIN 200

data processing

graphics

verification

operational database

NEC-SX6

preprocessing

analysis

initialisation

forecast

postprocessing

Mass storage device

GTS-observations

ECMWF boundary files

00Z ECMWFboundaries

Valid time start end Model Forecast

length Valid time start end

00 0140 0200 DMI-HIRLAM-G 60 12 1340 1400 00 0143 0205 DMI-HIRLAM-E 48 12 1343 1405 00 0230 0245 DMI-HIRLAM-D 36 12 1430 1445 00 0255 0310 DMI-HIRLAM-N 36 12 1455 1505 06 0737 0800 DMI-HIRLAM-G 60 18 1937 2000 06 0743 0805 DMI-HIRLAM-E 48 18 1943 2005 00 1100 1105 DMI-HIRLAM-G 3 12 2245 2250 03 1105 1115 DMI-HIRLAM-G 3 15 2250 2300 06 1115 1125 DMI-HIRLAM-G 3 18 2300 2310 09 1125 1135 DMI-HIRLAM-G 3 21 2310 2320 03 1135 1140 DMI-HIRLAM-E 3 15 2320 2325 06 1140 1145 DMI-HIRLAM-E 3 18 2325 2330 09 1145 1150 DMI-HIRLAM-E 3 21 2330 2335 03 1147 1149 DMI-HIRLAM-D 3 15 2335 2337 06 1149 1151 DMI-HIRLAM-D 3 18 2337 2339 09 1151 1153 DMI-HIRLAM-D 3 21 2339 2341 03 1153 1155 DMI-HIRLAM-N 3 15 2341 2343 06 1155 1157 DMI-HIRLAM-N 3 18 2343 2345 09 1157 1159 DMI-HIRLAM-N 3 21 2345 2345

12Z ECMWFboundaries

06Z ECMWFboundaries

18Z ECMWFboundaries

Evolution in RMS for MSLP

Quality of 24h forecasts of 10m wind speeds >= 8 m/s

Weibull distributions for 24 hour forecasts E, D, ECMWF and UKMO is also shown as well as curve for the observations.

The new NEC-SX6 computer at DMI

April 2002 March 2003

16+2 60+2

Memory 96 Gbyte 320 Gbyte

Peak 128 Gflops+ 16 480 Gflops+ 16

Increase 4 15

Disc 1 Tbyte 4 Tbyte

Front end2 AzusA systems with 4 cpu’s and 4 Gbyte each

PLUS 2 AsamA systems with 4 cpu’s and 8 Gbyte each

Total peak 25.6 Gflops 25.6+51.2 Gflops

SXSX--66/8/864GB64GB

AsAmA AsAmA 44 CPU CPU 88GBGBAsAmA AsAmA 44 CPU CPU 88GBGB

80 x 80FC Switch

8*4

X 8

1.1TB

1TB

1TB 1.1TB1.1TB

1TB1TB

1TBX 8

X 8

SIOXHP L-class

DMI Phase2 ConfigurationDMI Phase2 ConfigurationSXSX--66//60M860M8, , 320320GB GB

SXSX--66/8/83232GBGB

SXSX--66/8/864GB64GB






AsAmA AsAmA 44 CPU CPU 88GBGBAsAmA AsAmA 44 CPU CPU 88GBGB

1.1TB

1TB

1TB 1.1TB1.1TB

1TB1TB

1TB

X 8

AAzuszusA A 44 CPU CPU 88GBGBAAzuszusA A 44 CPU CPU 88GBGB

AAzuszusA A 44 CPU CPU 88GBGBAAzuszusA A 44 CPU CPU 88GBGB

X 4 X 4

GE

FEGE

FE

FE

GE

IXS

Some events during the migration to the NEC-SX6

• Oct. 01: Signature of contract between NEC and DMI• April 02: Upgrade (advection scheme for q, CW and TKE) • May 02: Installation of phase 1 of SX6• May 02: Parallel system on SX6 • June 02: DMI-HIRLAM-I (0.014 degree, 602x600 grid) on SX-6 • July 02: Stability test passed • Sep. 02: Operational suite on SX6, later removal of SX4• Sep. 02: Testing of new developments (diff. and convection)• Dec. 02: Upgrade: 40 levels, reduced time step, AMSU-A data• Jan. 03: Revised contract between NEC and DMI • Mar. 03: Installation of phase 2 of SX6• July 03: Stability test passed. • Sep. 03: Improvement in data-assimilation (FGAT, QuikScat etc.)• Early 04: New operational HIRLAM set-up using 6 nodes

HIRLAM Scalability Optimization

• Methods

• Implementation

• Performance

Optimization Focus

• Data transposition– from 2D to FFT distribution and reverse– from FFT to TRI distribution and reverse

• Exchange of halo points– between north and south– between east and west

• GRIB File I/O• Statistics

Approach

• First attempt: straight-forward conversion from SHMEM to MPI-2 put/get calls– it works, but:– too much overhead due to fine granularity

• Redesign of transposition and halo swap routinesless and larger messagesindependent message passing process groups

2D Sub Grids

• HIRLAM sub grid definition in TWOD data distribution

• Processors:

0 1 2

3 4 5

6 7 8

9 10 11

nprocynprocxnproc

lati

tud

e

longitude

levels

Original FFT Sub Grids

• HIRLAM sub grid definition in FFT data distribution

• Each processor handles slabs of full longitude lines

lati

tud

e

longitude

levels

2D↔FFT Redistribution

Sub grid data to be distributed to all processors:

send-receive pairs

4

2nproc

lati

tud

e

longitude

levels

3 4 5

2D↔FFT Redistribution

• Sub grids in east-west direction form full longitude lines

• nprocy independent sets of nprocx2 send-receive pairs, or:

send-receive pairs

• nprocy x less messages

nprocy

nproc 2

lati

tud

e

longitude

levels

5

4

3

Transpositions 2D↔FFT↔TRI

0 1 2

3 4 5

6 7 8

9 10 11

2

1

0

5

4

3

8

7

6

11

10

9

2 5 8 111 4 7 10

0 3 6 9

2D FFT TRI

lati

tud

e

longitude

levels

MPI Methods

• Transfer Methods– Remote Memory Access: mpi_put, mpi_get– Async Point-to-Point: mpi_isend, mpi_irecv– All-to-All: mpi_alltoallv,

mpi_alltoallw

• Buffering vs. direct– Explicit buffering– MPI derived types

(Method selection by environment variables)

Test grid Details

Parameter Value Notes

Longitudes 602

Latitudes 568

Levels 60

NSTOP 40 steps

Initialization none

Time step 180 seconds

Performance

Parallel Speedup on NEC SX-6

• Cluster of 8 NEC SX-6 nodes at DMI

• Up to 60 processors:

7 nodes with 8 processors per node

1 node with 4 processors

• Parallel efficiency 78% on 60 processors

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

0 10 20 30 40 50 60

Processors

Sp

eed

up

ideal original optimized

Performance - Observations

• New data redistribution method much more efficient (78% vs. 45% on 60 processors)

• No performance advantage with RMA (one-sided MP) or All-to-All over plain Point-to-Point method

• Elegant code with MPI derived types, but:• Explicit buffering faster

Questions?

• Thank you!

Documents

DMI Update