Task parallel implementation of a solver for electromagnetic scattering problems

Electromagnetic computations, where the wavelength is small in relation to the geometry of interest, become computationally demanding. In order to manage computations for realistic problems like electromagnetic scattering from aircraft, the use of parallel computing is essential. In this paper, we describe how a solver based on a hierarchical nested equivalent source approximation can be implemented in parallel using a task based programming model. We show that the effort for moving from the serial implementation to a parallel implementation is modest due to the task based programming paradigm, and that the performance achieved on a multicore system is excellent provided that the task size, depending on the method parameters, is large enough.

[1]  Sverker Holmgren,et al.  Dynamic Autotuning of Adaptive Fast Multipole Methods on Hybrid Multicore CPU and GPU Systems , 2013, SIAM J. Sci. Comput..

[2]  Giuseppe Vecchi,et al.  Wideband Fast Kernel-Independent Modeling of Large Multiscale Structures Via Nested Equivalent Source Approximation , 2015, IEEE Transactions on Antennas and Propagation.

[3]  Lexing Ying,et al.  A Parallel Directional Fast Multipole Method , 2013, SIAM J. Sci. Comput..

[4]  Satoshi Matsuoka,et al.  Tapas: An Implicitly Parallel Programming Framework for Hierarchical N-Body Algorithms , 2016, 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS).

[5]  Bo Zhang,et al.  Asynchronous Task Scheduling of the Fast Multipole Method Using Various Runtime Systems , 2014, 2014 Fourth Workshop on Data-Flow Execution Models for Extreme Scale Computing.

[6]  Emmanuel Agullo,et al.  Task-Based FMM for Multicore Architectures , 2014, SIAM J. Sci. Comput..

[7]  Jin-Fa Lee,et al.  A fast IE-FFT algorithm for solving PEC scattering problems , 2005 .

[8]  Cédric Augonnet,et al.  StarPU: a unified platform for task scheduling on heterogeneous multicore architectures , 2011, Concurr. Comput. Pract. Exp..

[9]  Francesca Vipiana,et al.  EFIE Modeling of High-Definition Multiscale Structures , 2010, IEEE Transactions on Antennas and Propagation.

[10]  Elisabeth Larsson,et al.  DuctTeip : A task-based parallel programming framework for distributed memory architectures , 2016 .

[11]  Stefan Engblom.  On well-separated sets and fast mutipole methods , 2010, ArXiv.

[12]  Elisabeth Larsson,et al.  Resource-Aware Task Scheduling , 2015, ACM Trans. Embed. Comput. Syst..

[13]  M. Vouvakis,et al.  The adaptive cross approximation algorithm for accelerated method of moments computations of EMC problems , 2005, IEEE Transactions on Electromagnetic Compatibility.

[14]  Elisabeth Larsson,et al.  DuctTeip: An efficient programming model for distributed task based parallel computing , 2018, Parallel Comput..

[15]  Jiming Song,et al.  Multilevel fast multipole algorithm for electromagnetic scattering by large complex objects , 1997 .

[16]  Cyril Bordage,et al.  Parallelization on Heterogeneous Multicore and Multi-GPU Systems of the Fast Multipole Method for the Helmholtz Equation Using a Runtime System , 2012 .

[17]  Martin Tillenius,et al.  SuperGlue: A Shared Memory Framework Using Data Versioning for Dependency-Aware Task-Based Parallelization , 2015, SIAM J. Sci. Comput..

[18]  Francesca Vipiana,et al.  A Doubly Hierarchical MoM for High-Fidelity Modeling of Multiscale Structures , 2014, IEEE Transactions on Electromagnetic Compatibility.

[19]  S. Velamparambil,et al.  Analysis and performance of a distributed memory multilevel fast multipole algorithm , 2005, IEEE Transactions on Antennas and Propagation.

[20]  Ozgur Ergul,et al.  Hierarchical parallelization of the multilevel fast multipole algorithm (MLFMA) , 2013 .

[21]  Simon McIntosh-Smith,et al.  On the Performance of Parallel Tasking Runtimes for an Irregular Fast Multipole Method Application , 2017, IWOMP.

[22]  Mario Bebendorf,et al.  Approximation of boundary element matrices , 2000, Numerische Mathematik.

[23]  Richard W. Vuduc,et al.  A massively parallel adaptive fast-multipole method on heterogeneous architectures , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[24]  Emmanuel Agullo,et al.  Bridging the Gap Between OpenMP and Task-Based Runtime Systems for the Fast Multipole Method , 2017, IEEE Transactions on Parallel and Distributed Systems.

[25]  Thomas Hérault,et al.  PaRSEC: Exploiting Heterogeneity to Enhance Scalability , 2013, Computing in Science & Engineering.

[26]  Plasma , 2019, Reactions Weekly.

[27]  Jakub Kurzak,et al.  Massively parallel implementation of a fast multipole method for distributed memory machines , 2005, J. Parallel Distributed Comput..

[28]  Francesca Vipiana,et al.  Nested Equivalent Source Approximation for the Modeling of Multiscale Structures , 2014, IEEE Transactions on Antennas and Propagation.

[29]  David E. Long,et al.  IES3: a fast integral equation solver for efficient 3-dimensional extraction , 1997, ICCAD.

[30]  Jesús Labarta,et al.  A dependency-aware task-based programming environment for multi-core architectures , 2008, 2008 IEEE International Conference on Cluster Computing.

[31]  Jesús Labarta,et al.  ClusterSs: a task-based programming model for clusters , 2011, HPDC '11.

[32]  Hatem Ltaief,et al.  Data‐driven execution of fast multipole methods , 2012, Concurr. Comput. Pract. Exp..

[33]  Matthew G. Knepley,et al.  PetFMM—A dynamically load‐balancing parallel fast multipole library , 2009, ArXiv.

[34]  Cédric Augonnet,et al.  StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators , 2012, EuroMPI.

[35]  Eric Darve,et al.  The fast multipole method on parallel clusters, multicore processors, and graphics processing units , 2011 .

[36]  Jack Dongarra,et al.  QUARK Users' Guide: QUeueing And Runtime for Kernels , 2011 .

[37]  Elisabeth Larsson,et al.  A scalable RBF-FD method for atmospheric flow , 2015, J. Comput. Phys..