Sea, Wind, & Fire (Wednesday
Chair: Tony Drummond, Lawrence Berkeley National Laboratory
Coastal Ocean Modeling of the U.S. West Coast with Multiblock
Grid and Dual-Level Parallelism
Phu V. Luong (Engineer Research and Development Center, Major
Shared Resource Center)
Clay P. Breshears (KAI Software, A Division of Intel Americas,
Le N. Ly (Naval Postgraduate School)
In coastal ocean modeling, a one-block rectangular grid for
a large domain has large memory requirements and long processing
times. With complicated coastlines, the number of grid points
used in the calculation is often the same or smaller than
the number of unused grid points. These problems have been
a major concern for researchers in this field.
Multiblock grid generation and dual-level parallel
techniques are solutions that can overcome these problems.
The Multiblock Grid Princeton Ocean Model (MGPOM) uses Message
Passing Interface (MPI) to parallelize computations by assigning
each grid block to a unique processor. Since not all grid
blocks are of the same size, the workload between MPI processes
varies. Pthreads is used to improve load balance.
Performance results from the MGPOM model on a
one-block grid and a 29-block grid simulation for the U.S.
west coast demonstrate the efficacy of both the MPI-Only and
MPI-Pthreads code versions.
Terascale spectral element dynamical core for atmospheric
general circulation models
Richard D. Loft (National Center for Atmospheric Research)
Stephen J. Thomas (National Center for Atmospheric Research)
John M. Dennis (National Center for Atmospheric Research)
Gordon Bell Prize Finalist
Climate modeling is a grand challenge problem where scientific
progress is measured not in terms of the largest problem that
can be solved but by the highest achievable integration rate.
These models have been notably absent in previous Gordon Bell
competitions due to their inability to scale to large processor
counts. A scalable and efficient spectral element atmospheric
model is presented. A new semi-implicit time stepping scheme
accelerates the integration rate relative to an explicit model
by a factor of two, achieving 130 years per day at T63L30
equivalent resolution. Execution rates are reported for the
standard shallow water and Held-Suarez climate benchmarks
on IBM SP clusters. The explicit T170 equivalent multi-layer
shallow water model sustains 343 Gflops at NERSC, 206 Gflops
at NPACI (SDSC) and 127 Gflops at NCAR. An explicit Held-Suarez
integration sustains 369 Gflops on 128 16-way IBM nodes at
High Resolution Weather Modeling for Improved Fire Management
Kevin Roe (Maui High Performance Computing Center)
Duane Stevens(University of Hawaii)
Carol McCord (Maui High Performance Computing Center)
A critical element to the accurate prediction of fire/weather
behaviour is the knowledge of near-surface weather. Weather
variables, such as wind, temperature, humidity and precipitation,
make direct impacts on the practice of managing prescribed
burns and fighting wild fires. State-of-the-art Numerical
Weather Prediction (NWP), coupled with the use of high performance
computing, now enable significantly improved short-term forecasting
of near-surface weather at a 1-3 km grid resolution.
This proof of concept project integrates two
complementary model types to aid federal agencies in real-time
management of fire. (1) A highly complex, full-physics mesoscale
weather prediction model (MM5) which is applied in order to
estimate the weather fields up to 72 hours in advance. (2)
A diagnostic fire behavior model (FARSITE) takes the near-surface
weather fields and computes the expected spread rate of a
fire driven by wind, humidity, terrain, and fuels (i.e. vegetation).