MESQUITE: Mesh Optimization Toolkit
Brian Miller, LLNL
miller125@llnl.gov
A) Project Overview
• Science goal: Algorithms for improving unstructured mesh
quality, achieved through optimization techniques.
– Provide library of high quality mesh optimization tools to simulation
code projects (Mesquite).
• Pat Knupp (SNL) project PI
– Brian Miller, Lori Diachin (LLNL)
– Carl Ollivier-Gooch (UBC)
• Long history of support through DoE Office of Science
– Several successful collaborations with both SciDAC and ASC code groups.
• Goals in CScADS context: Apply threaded parallelism to
Mesquite optimization solvers.
– Evolve algorithms and software to take advantage of current and
emerging hardware and software capabilities (multicore, many core,
etc.)
B) Science Lesson
• MESQUITE poses unstructured mesh quality improvement as an
optimization problem.
– Element Quality:
• Ideal element as defined by the user drives this.
– Mesh quality objective function:
• How local element qualities are summed into the global objective
function. Again, user defined.
– Optimization problem: min(F(x))
• Optimization problems solved using included solvers ranging from
simple steepest descent to more sophisticated Feasible Newton and
Active Set solvers. Again user chooses solver method.
C/D) Methods and Programming Model
• Pretty basic C++ .
• No third party libraries except for unit testing (cppunit).
• MPI parallelism, mostly low volume nearest neighbor
communication.
• No threaded parallelism currently – we intend to change this.
• Fairly portable code including recent runs on LLNL dawn BG/P
machine.
• Optimization solvers included in the code, no interface to
external optimization libraries.
• Designed to meet TSTTM mesh query interface and have
demonstrated its use in several code interfaces.
E) I/O and Viz
• I/O:
– Not really applicable since Mesquite is intended for use within an existing
code framework.
– For standalone use and testing we typically read/write one file per MPI
task.
• Viz:
– Visit or paraview for viewing parallel mesh files.
– Optional Gnuplot output of convergence histories.
• Analysis:
– Internal mechanism for mesh quality calculations.
G/H) Tools and Performance
• What tools do you use?
– TAU/OpenSpeedShop/Intel tools for performance analysis and thread
checks.
– Totalview, valgrind for debugging.
– Some internal debugging output available.
• What do you believe is your current bottleneck to better
performance?
– Serial performance is sub-optimal. A route is needed from the generic
algorithms provided in Mesquite to tight, high performance loops.
• What do you believe is your current bottleneck to better
scaling?
– Scaling hasn’t been a problem (yet.)
• What features would you like to see in performance tools?
– Better derived hardware metrics/more sophisticated analysis.
I) Status and Scalability
• Goal in one year: Similar graph but with threads added.
• Top Pains:
– Must add threading to existing code – not enough resources to rewrite.
– Require portable threading model.
– How to inherit simulation threading model.
J) Roadmap
• Where will your science take you over the next 2 years?
– Desire to support runs on significantly larger systems (Sequoia)
• What do you hope to learn / discover?
– Extent of MPI scalability.
– Effect of adding threading on MPI scalability.
• What improvements will you need to make?
– New threaded global solver algorithms.
– Gradual evolution to threaded implementation.
• What are your plans?
– OpenMP threading in limited regions of the code – specific algorithms
with good available parallelism initially.
– Extending threads to other areas may require algorithmic changes.
– Explore other threading models: OpenCL, OpenACC, CUDA, etc.