Jan Zapletal

Boundary element based multiresolution shape optimisation in electrostatics

We consider the shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. The geometry of the domain is described with subdivision surfaces and different resolutions of the same geometry are used for optimisation and analysis. The primal and adjoint problems are discretised with the boundary element method using a sufficiently fine control mesh. For shape optimisation the geometry is updated starting from the coarsest control mesh with increasingly finer control meshes. The multiresolution approach effectively prevents the appearance of non-physical geometry oscillations in the optimised shapes. Moreover, there is no need for mesh regeneration or smoothing during the optimisation due to the absence of a volume mesh. We present several numerical experiments and one industrial application to demonstrate the robustness and versatility of the developed approach.

Acceleration of boundary element method by explicit vectorization

The in-core vectorization of the Galerkin BEM using the Vc library is proposed.Fully numerical and semi-analytical integration schemes are discussed.Numerical experiments show significant speedup of the BEM computation. Although parallelization of computationally intensive algorithms has become a standard with the scientific community, the possibility of in-core vectorization is often overlooked. With the development of modern HPC architectures, however, neglecting such programming techniques may lead to inefficient code hardly utilizing the theoretical performance of nowadays CPUs. The presented paper reports on explicit vectorization for quadratures stemming from the Galerkin formulation of boundary integral equations in 3D. To deal with the singular integral kernels, two common approaches including the semi-analytic and fully numerical schemes are used. We exploit modern SIMD (Single Instruction Multiple Data) instruction sets to speed up the assembly of system matrices based on both of these regularization techniques. The efficiency of the code is further increased by standard shared-memory parallelization techniques and is demonstrated on a set of numerical experiments.

Many Core Acceleration of the Boundary Element Method

The paper presents the boundary element method accelerated by the Intel Xeon Phi coprocessors. An overview of the boundary element method for the 3D Laplace equation is given followed by the discretization and its parallelization using OpenMP and the offload features of the Xeon Phi coprocessor are discussed. The results of numerical experiments for both single- and double-layer boundary integral operators are presented. In most cases the accelerated code significantly outperforms the original code running solely on Intel Xeon processors.

A parallel library for boundary element discretization of engineering problems

In this paper we present a software for parallel solution of engineering problems based on the boundary element method. The library is written in C++ and utilizes OpenMP and MPI for parallelization in both shared and distributed memory. We give an overview of the structure of the library and present numerical results related to 3D sound-hard scattering in an unbounded domain represented by the boundary value problem for the Helmholtz equation. Scalability results for the assembly of system matrices sparsified by the adaptive cross approximation are also presented.

Boundary element quadrature schemes for multi- and many-core architectures

In the paper we study the performance of the regularized boundary element quadrature routines implemented in the BEM4I library developed by the authors. Apart from the results obtained on the classical multi-core architecture represented by the Intel Xeon processors we concentrate on the portability of the code to the many-core family Intel Xeon Phi. Contrary to the GP-GPU programming accelerating many scientific codes, the standard x86 architecture of the Xeon Phi processors allows to reuse the already existing multi-core implementation. Although in many cases a simple recompilation would lead to an inefficient utilization of the Xeon Phi, the effort invested in the optimization usually leads to a better performance on the multi-core Xeon processors as well. This makes the Xeon Phi an interesting platform for scientists developing a software library aimed at both modern portable PCs and high performance computing environments. Here we focus at the manually vectorized assembly of the local element contributions and the parallel assembly of the global matrices on shared memory systems. Due to the quadratic complexity of the standard assembly we also present an assembly sparsified by the adaptive cross approximation based on the same acceleration techniques. The numerical results performed on the Xeon multi-core processor and two generations of the Xeon Phi many-core platform validate the proposed implementation and highlight the importance of vectorization necessary to exploit the features of modern hardware.

A novel boundary element library with applications

We present a newly developed library based on the boundary element method (BEM) for solving boundary value problems in 3D. The advantage of BEM over the widely used finite element method is clear when discretizing a problem in an unbounded domain. This is, for example, the case of sound scattering problems modelled by the Helmholtz equation, which is one of the possible applications of the library and is discussed in this paper.

Domain knowledge specification for energy tuning: Domain knowledge specification for energy tuning

To overcome the challenges of energy consumption of HPC systems, the European Union Horizon 2020 READEX (Runtime Exploitation of Application Dynamism for Energy‐efficient Exascale computing) project uses an online auto‐tuning approach to improve energy efficiency of HPC applications. The READEX methodology pre‐computes optimal system configurations at design‐time, such as the CPU frequency, for instances of program regions and switches at runtime to the configuration given in the tuning model when the region is executed. READEX goes beyond previous approaches by exploiting dynamic changes of a regions characteristics by leveraging region and characteristic specific system configurations. While the tool suite supports an automatic approach, specifying domain knowledge such as the structure and characteristics of the application and application tuning parameters can significantly help to create a more refined tuning model. This paper presents the means available for an application expert to provide domain knowledge and presents tuning results for some benchmarks.

Evaluation of the Intel Xeon Phi offload runtimes for domain decomposition solvers

Abstract In the paper we provide a comparison of several runtimes which can be used for offloading computationally intensive kernels to the Intel Xeon Phi coprocessors. The presented benchmark application is a stripped-down version of an iterative solver used within the Schur complement finite or boundary element tearing and interconnecting (FETI, BETI) domain decomposition methods where the sparse solve with local stiffness matrices is replaced by the multiplication with dense matrices in order to exploit coalesced memory access patterns. We present offload approaches based on the Intel Language Extension for Offload (LEO), Hetero Streams Library (hStreams), and Heterogeneous Active Messages (HAM), and compare their performance and ease of use.

Parallel Assembly of ACA BEM Matrices on Xeon Phi Clusters

The paper presents parallelization of the boundary element method in distributed memory of a cluster equipped with many-core based compute nodes. A method for efficient distribution of boundary element matrices among MPI processes based on the cyclic graph decompositions is described. In addition, we focus on the intra-node optimization of the code, which is necessary in order to fully utilize the many-core processors with wide SIMD registers. Numerical experiments carried out on a cluster consisting of the Intel Xeon Phi processors of the Knights Landing generation are presented.

MERIC and RADAR Generator: Tools for Energy Evaluation and Runtime Tuning of HPC Applications

This paper introduces two tools for manual energy evaluation and runtime tuning developed at IT4Innovations in the READEX project. The MERIC library can be used for manual instrumentation and analysis of any application from the energy and time consumption point of view. Besides tracing, MERIC can also change environment and hardware parameters during the application runtime, which leads to energy savings.