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Operational computing environment at EARS

This article discusses the history and present state of the operational computing environment at the Environmental Agency of Slovenia (EARS), including the experiences with limited area modeling and the needed ingredients for future systems. It also explores the current hardware and software setup, operational experiences, reliability, optimizations, and future developments in limited area modeling.

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Operational computing environment at EARS

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  1. Jure Jerman Meteorological Office Environmental Agency of Slovenia (EARS) Operational computing environment at EARS

  2. Outline Linux Cluster at Environmental Agency of Slovenia, history and present state Operational experiences Future requirements for limited area modelling Needed ingredients for future system?

  3. History & background EARS: small service, limited resources for NWP Small NWP group, research & operations First research Alpha-Linux cluster (1996) – 20 nodes First Linux operational cluster at EARS (1997) 5 x Alpha CPU One among first operational clusters in Europe in the field of meteorology

  4. Tuba – current cluster system • Installed 3 years ago, already outdated • Important for gathering of experiences • Hardware: • 13 Compute Nodes, • 1 Master Node, Dual Xeon 2.4 Ghz, • 28 GB memory • Gigabit Ethernet • Storage: 4 TB IDE2SCSI disk array, xfs filesystem

  5. Tuba software Open source, whenever possible • Cluster management software: • OS: RH Linux + SCore (5.8.2) (www.pccluster.org) • Mature parallel environment • Lower latency MPI implementation • Transparent to user • Gang scheduling • Pre-empting • Checkpointing • Parallel shell • Automatic fault recovery (hardware or SCore) • FIFO scheduler • Capability of integration with OpenPBS and SGE • Lahey and Intel compilers

  6. Ganglia - Cluster Health monitoring

  7. Operational experiences • In production for almost 3 years • Unmonitored suite • Minimal hardware related problems so far! • Some problems with SCore (mainly related to buffers in MPI) • NFS related problems • ECMWF's SMS, solves majority of problems

  8. Reliability

  9. Operational setup ALADIN model • 290x240x37 domain • 9.3 km resolution • 54h integration • Target: 1 h

  10. Optimizations Not everything in a hardware Code optimizations B-Level parallelization (up two 20 % at greater number of processors) Load balancing of grid point computations (depending on the number of processors) Parameter tuning NPROMA cash tuning MPI message size Improvement in compilers (Lahey –> Intel 8.1 20 – 25 %) Still to work on: OpenMP (better efficiency of memory usage)

  11. Non operational use • Downscaling of ERA-40 reanalysis with ALADIN model • Estimation of wind energy potential over Slovenia • Multiple nesting of target computational domain into ERA-40 data • 10 years period, 8 years / month • Major question: How to ensure coexistence with operational suite

  12. Foreseen developments in limited area modeling Currently ALADIN 9 km 2008-2009 Arome, 2.5 km : ALADIN NH solver + Meso NH physics 3 times more expensive per Grid Point Target Arome: ~200 x – 300 x more expensive (same computational domain, same time range)

  13. How to get there (if?) Linux commodity cluster at EARS? First upgrade in the mid 2006 5 times the current system (if possible, below 64 processors) Tests going on with: New processors: AMD Opteron, Intel Itanium-2 Interconnection: Infinyband, Quadrics? Compilers: PathScale (AMD Opteron) Crucial: Parallel file system (TerraGrid), already installed, replacement of NFS

  14. How to stay at the open side of the fence? Linux and other OpenSource projects are evolving Great number of more and more complex software projects Specific (operational) requirements in meteorology Space for system integrators Price/performance gap between commodity and brand name systems is getting smaller when the size of system is growing Pioneer time of Beowulf clusters seems to be over Importance of extensive test of all cluster components

  15. Conclusions Positive experiences with small commodity Linux cluster, great price/performance ratio Our present type of development of new cluster works for small cluster, might work for medium sized and doesn’t for big systems Future are probably Linux clusters, but branded

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