Presentation
Moment Representation in the Lattice Boltzmann Method on Massively Parallel Hardware
SessionCompression
Event Type
Paper
TP
Algorithms
Data Compression
Data Management
Graph Algorithms
I/O
Memory
Parallel Application Frameworks
Performance
TimeWednesday, 20 November 201911am - 11:30am
Location405-406-407
DescriptionThe widely-used lattice Boltzmann method (LBM) for computational fluid dynamics is highly scalable, but also significantly memory bandwidth-bound on current architectures. This paper presents a new regularized LBM implementation that reduces the memory footprint by only storing macroscopic, moment-based data. We show that the amount of data that must be stored in memory during a simulation is reduced by up to 47%. We also present a technique for cache-aware data re-utilization and show that optimizing cache utilization to limit data motion results in a similar improvement in time to solution. These new algorithms are implemented in the hemodynamics solver HARVEY and demonstrated using both idealized and realistic biological geometries. We develop a performance model for the moment representation algorithm and evaluate the performance on Summit.
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