1. Climate-Weather modeling studies Using a Prototype Global Cloud-System Resolving Model Zhi Liang (GFDL/DRC)

2. A) Project Overview The project Climate-Weather modeling studies Using a Prototype Global Cloud-System Resolving Model Science goals Study the effect of clouds in climate-weather models The participants, description of team Chris Kerr (GFDL/UCAR, PI) V. Balaji (GFDL/Princeton University, PI) Zhi Liang (GFDL/DRC) Sponsor GFDL/NOAA

3. B) Science Lesson What does the application do, and how? Study the effect of clouds in climate-weather models:  Role of clouds is critical in global climate models  First generation experiments: atmospheric model  Second generation experiments: coupled atmosphere, ocean, … models Experiments will focus on 2008 "Year of Tropical Convection” research program:  12 km HIRAM hydrostatic model  3.5 km HIRAM non-hydrostatic model

4. C) Parallel Programming Model Hybrid model of MPI and OpenMP. Languages: Fortran 90 and C. Runtime libraries: netcdf, mpich Platforms: Cray XT6, Blue Gene/P, Blue Gene/Q, SGI Altix Ice Status: Runs OK Future Plan: Performance analysis on Blue Gene/Q.

5. E) I/O Patterns and Strategy Input I/O and output I/O patterns Distribute I/O. Use netcdf4. Approximate sizes of inputs and outputs Output about 600G for 1 month model time. Checkpoint / Restart capabilities Reproduce and intermediate restart. Future plans for I/O Improve the I/O scaling.

6. G) Performance What tools do you use now to explore performance Hardware performance counters, tau, Craypat What do you believe is your current bottleneck to better performance/scaling? Under investigation. Current status and future plans for improving performance Improve the MPI, OpenMP and I/O scaling.

7. H) Tools How do you debug your code? Print statement totalview ddt

8. I) Status and Scalability How does your application scale now? OK. Where do you want to be in a year? Better scaling. What are your top 5 pains? (be specific) –I/O scaling: large output. –MPI and OpenMP scaling. What did you change to achieve current scalability? Non-blocking communication, distributed IO.

9. Scalability

10. J) Roadmap What do you hope to learn / discover? Tools for OpenMP performance analysis. What improvements will you need to make: MPI, OpenMP and I/O scaling, load balance. What are your plans? Performance analysis.