When viewing the Technical Program schedule, on the far righthand side
is a column labeled "PLANNER." Use this planner to build your own
schedule. Once you select an event and want to add it to your personal
schedule, just click on the calendar icon of your choice (outlook
calendar, ical calendar or google calendar) and that event will be
stored there. As you select events in this manner, you will have your
own schedule to guide you through the week.
You can also create your personal schedule on the SC11 app (Boopsie) on your smartphone. Simply select a session you want to attend and "add" it to your plan. Continue in this manner until you have created your own personal schedule. All your events will appear under "My Event Planner" on your smartphone.
Extracting Ultra-Scale Lattice Boltzmann Performance via Hierarchical and Distributed Auto-Tuning
SESSION: Application Performance
EVENT TYPE: Paper
TIME: 11:00AM - 11:30AM
AUTHOR(S):Samuel Williams, Leonid Oliker, Jonathan Carter, John Shalf
ABSTRACT: We are witnessing a rapid evolution of HPC node architectures and on-chip parallelism as power and cooling limit increases in microprocessor clock speeds. We demonstrate a hierarchical approach towards effectively extracting performance for a variety of emerging multicore-based supercomputing platforms. Our examined application is a structured grid-based Lattice Boltzmann computation that simulates homogeneous isotropic turbulence in magnetohydrodynamics. First, we examine auto-tuning techniques including loop transformations, virtual vectorization, use of ISA-specific intrinsics, including programming model exploration (flat MPI, MPI-OpenMP, and MPI-Pthreads), as well as data and thread decomposition strategies designed to mitigate communication bottlenecks. We evaluate the impact of our hierarchical tuning techniques using a variety of problem sizes via large-scale simulations on state-of-the-art Cray XT4, Cray XE6, and IBM BlueGene/P platforms. Results show that our approach improves performance and energy by up to 3.4x using 49,152 cores, while providing a portable optimization methodology for a variety of numerical methods.
Samuel Williams - Lawrence Berkeley National Laboratory
Leonid Oliker - Lawrence Berkeley National Laboratory
Jonathan Carter - Lawrence Berkeley National Laboratory
John Shalf - Lawrence Berkeley National Laboratory