@article{28099, abstract = {{N-body methods are one of the essential algorithmic building blocks of high-performance and parallel computing. Previous research has shown promising performance for implementing n-body simulations with pairwise force calculations on FPGAs. However, to avoid challenges with accumulation and memory access patterns, the presented designs calculate each pair of forces twice, along with both force sums of the involved particles. Also, they require large problem instances with hundreds of thousands of particles to reach their respective peak performance, limiting the applicability for strong scaling scenarios. This work addresses both issues by presenting a novel FPGA design that uses each calculated force twice and overlaps data transfers and computations in a way that allows to reach peak performance even for small problem instances, outperforming previous single precision results even in double precision, and scaling linearly over multiple interconnected FPGAs. For a comparison across architectures, we provide an equally optimized CPU reference, which for large problems actually achieves higher peak performance per device, however, given the strong scaling advantages of the FPGA design, in parallel setups with few thousand particles per device, the FPGA platform achieves highest performance and power efficiency.}}, author = {{Menzel, Johannes and Plessl, Christian and Kenter, Tobias}}, issn = {{1936-7406}}, journal = {{ACM Transactions on Reconfigurable Technology and Systems}}, number = {{1}}, pages = {{1--30}}, title = {{{The Strong Scaling Advantage of FPGAs in HPC for N-body Simulations}}}, doi = {{10.1145/3491235}}, volume = {{15}}, year = {{2021}}, } @article{32246, abstract = {{

State-of-the-art methods in materials science such as artificial intelligence and data-driven techniques advance the investigation of photovoltaic materials.

}}, author = {{Mirhosseini, Hossein and Kormath Madam Raghupathy, Ramya and Sahoo, Sudhir K. and Wiebeler, Hendrik and Chugh, Manjusha and Kühne, Thomas D.}}, issn = {{1463-9076}}, journal = {{Physical Chemistry Chemical Physics}}, keywords = {{Physical and Theoretical Chemistry, General Physics and Astronomy}}, number = {{46}}, pages = {{26682--26701}}, publisher = {{Royal Society of Chemistry (RSC)}}, title = {{{In silico investigation of Cu(In,Ga)Se2-based solar cells}}}, doi = {{10.1039/d0cp04712k}}, volume = {{22}}, year = {{2020}}, } @article{12878, abstract = {{In scientific computing, the acceleration of atomistic computer simulations by means of custom hardware is finding ever-growing application. A major limitation, however, is that the high efficiency in terms of performance and low power consumption entails the massive usage of low precision computing units. Here, based on the approximate computing paradigm, we present an algorithmic method to compensate for numerical inaccuracies due to low accuracy arithmetic operations rigorously, yet still obtaining exact expectation values using a properly modified Langevin-type equation.}}, author = {{Rengaraj, Varadarajan and Lass, Michael and Plessl, Christian and Kühne, Thomas}}, journal = {{Computation}}, number = {{2}}, publisher = {{MDPI}}, title = {{{Accurate Sampling with Noisy Forces from Approximate Computing}}}, doi = {{10.3390/computation8020039}}, volume = {{8}}, year = {{2020}}, } @article{16277, abstract = {{CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-theart ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.}}, author = {{Kühne, Thomas and Iannuzzi, Marcella and Ben, Mauro Del and Rybkin, Vladimir V. and Seewald, Patrick and Stein, Frederick and Laino, Teodoro and Khaliullin, Rustam Z. and Schütt, Ole and Schiffmann, Florian and Golze, Dorothea and Wilhelm, Jan and Chulkov, Sergey and Mohammad Hossein Bani-Hashemian, Mohammad Hossein Bani-Hashemian and Weber, Valéry and Borstnik, Urban and Taillefumier, Mathieu and Jakobovits, Alice Shoshana and Lazzaro, Alfio and Pabst, Hans and Müller, Tiziano and Schade, Robert and Guidon, Manuel and Andermatt, Samuel and Holmberg, Nico and Schenter, Gregory K. and Hehn, Anna and Bussy, Augustin and Belleflamme, Fabian and Tabacchi, Gloria and Glöß, Andreas and Lass, Michael and Bethune, Iain and Mundy, Christopher J. and Plessl, Christian and Watkins, Matt and VandeVondele, Joost and Krack, Matthias and Hutter, Jürg}}, journal = {{The Journal of Chemical Physics}}, number = {{19}}, title = {{{CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations}}}, doi = {{10.1063/5.0007045}}, volume = {{152}}, year = {{2020}}, } @article{21, abstract = {{We address the general mathematical problem of computing the inverse p-th root of a given matrix in an efficient way. A new method to construct iteration functions that allow calculating arbitrary p-th roots and their inverses of symmetric positive definite matrices is presented. We show that the order of convergence is at least quadratic and that adaptively adjusting a parameter q always leads to an even faster convergence. In this way, a better performance than with previously known iteration schemes is achieved. The efficiency of the iterative functions is demonstrated for various matrices with different densities, condition numbers and spectral radii.}}, author = {{Richters, Dorothee and Lass, Michael and Walther, Andrea and Plessl, Christian and Kühne, Thomas}}, journal = {{Communications in Computational Physics}}, number = {{2}}, pages = {{564--585}}, publisher = {{Global Science Press}}, title = {{{A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices}}}, doi = {{10.4208/cicp.OA-2018-0053}}, volume = {{25}}, year = {{2019}}, } @article{12871, author = {{Platzner, Marco and Plessl, Christian}}, issn = {{0170-6012}}, journal = {{Informatik Spektrum}}, title = {{{FPGAs im Rechenzentrum}}}, doi = {{10.1007/s00287-019-01187-w}}, year = {{2019}}, } @article{7689, author = {{Riebler, Heinrich and Vaz, Gavin Francis and Kenter, Tobias and Plessl, Christian}}, journal = {{ACM Trans. Archit. Code Optim. (TACO)}}, keywords = {{htrop}}, number = {{2}}, pages = {{14:1–14:26}}, publisher = {{ACM}}, title = {{{Transparent Acceleration for Heterogeneous Platforms with Compilation to OpenCL}}}, doi = {{10.1145/3319423}}, volume = {{16}}, year = {{2019}}, } @article{6516, author = {{Mertens, Jan Cedric and Boschmann, Alexander and Schmidt, M. and Plessl, Christian}}, issn = {{1369-7072}}, journal = {{Sports Engineering}}, number = {{4}}, pages = {{441--451}}, publisher = {{Springer Nature}}, title = {{{Sprint diagnostic with GPS and inertial sensor fusion}}}, doi = {{10.1007/s12283-018-0291-0}}, volume = {{21}}, year = {{2018}}, } @article{13348, author = {{Luk, Samuel M. H. and Lewandowski, P. and Kwong, N. H. and Baudin, E. and Lafont, O. and Tignon, J. and Leung, P. T. and Chan, Ch. K. P. and Babilon, M. and Schumacher, Stefan and Binder, R.}}, issn = {{0740-3224}}, journal = {{Journal of the Optical Society of America B}}, number = {{1}}, title = {{{Theory of optically controlled anisotropic polariton transport in semiconductor double microcavities}}}, doi = {{10.1364/josab.35.000146}}, volume = {{35}}, year = {{2018}}, } @article{20, abstract = {{Approximate computing has shown to provide new ways to improve performance and power consumption of error-resilient applications. While many of these applications can be found in image processing, data classification or machine learning, we demonstrate its suitability to a problem from scientific computing. Utilizing the self-correcting behavior of iterative algorithms, we show that approximate computing can be applied to the calculation of inverse matrix p-th roots which are required in many applications in scientific computing. Results show great opportunities to reduce the computational effort and bandwidth required for the execution of the discussed algorithm, especially when targeting special accelerator hardware.}}, author = {{Lass, Michael and Kühne, Thomas and Plessl, Christian}}, issn = {{1943-0671}}, journal = {{Embedded Systems Letters}}, number = {{2}}, pages = {{ 33--36}}, publisher = {{IEEE}}, title = {{{Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots}}}, doi = {{10.1109/LES.2017.2760923}}, volume = {{10}}, year = {{2018}}, }