@article{16927,
  author       = {{Gharibian, Sevag and Aldi, Marco and de Beaudrap, Niel and Saeedi, Seyran}},
  journal      = {{Communications in Mathematical Physics}},
  title        = {{{On efficiently solvable cases of Quantum k-SAT}}},
  year         = {{2020}},
}

@misc{45232,
  author       = {{N., N.}},
  title        = {{{A Framework for Measurable Value Propositions of Mobile Applications}}},
  year         = {{2020}},
}

@misc{45234,
  author       = {{N., N.}},
  title        = {{{Model-Based Product Configuration in Augmented Reality Applications}}},
  year         = {{2020}},
}

@misc{45235,
  author       = {{N., N.}},
  title        = {{{Design and Implementation of a Crowd-based Prototype Validation Platform}}},
  year         = {{2020}},
}

@misc{21433,
  abstract     = {{Modern machine learning (ML) techniques continue to move into the embedded system space because traditional centralized compute resources do not suit certain application domains, for example in mobile or real-time environments. Google’s TensorFlow Lite (TFLite) framework supports this shift from cloud to edge computing and makes ML inference accessible on resource-constrained devices. While it offers the possibility to partially delegate computation to hardware accelerators, there is no such “delegate” available to utilize the promising characteristics of reconfigurable hardware.
This thesis incorporates modern platform FPGAs into TFLite by implementing a modular delegate framework, which allows accelerators within the programmable logic to take over the execution of neural network layers. To facilitate the necessary hardware/software codesign, the FPGA delegate is based on the operating system for reconfigurable
computing (ReconOS), whose partial reconfiguration support enables the instantiation of model-tailored accelerator architectures. In the hardware back-end, a streaming-based prototype accelerator for the MobileNet model family showcases the working order of the platform, but falls short of the desired performance. Thus, it indicates the need for further exploration of alternative accelerator designs, which the delegate could automatically synthesize to meet a model’s demands.}},
  author       = {{Jentzsch, Felix P.}},
  title        = {{{Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture}}},
  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}},
}

@inproceedings{16898,
  abstract     = {{Electronic structure calculations based on density-functional theory (DFT)
represent a significant part of today's HPC workloads and pose high demands on
high-performance computing resources. To perform these quantum-mechanical DFT
calculations on complex large-scale systems, so-called linear scaling methods
instead of conventional cubic scaling methods are required. In this work, we
take up the idea of the submatrix method and apply it to the DFT computations
in the software package CP2K. For that purpose, we transform the underlying
numeric operations on distributed, large, sparse matrices into computations on
local, much smaller and nearly dense matrices. This allows us to exploit the
full floating-point performance of modern CPUs and to make use of dedicated
accelerator hardware, where performance has been limited by memory bandwidth
before. We demonstrate both functionality and performance of our implementation
and show how it can be accelerated with GPUs and FPGAs.}},
  author       = {{Lass, Michael and Schade, Robert and Kühne, Thomas and Plessl, Christian}},
  booktitle    = {{Proc. International Conference for High Performance Computing, Networking, Storage and Analysis (SC)}},
  location     = {{Atlanta, GA, US}},
  pages        = {{1127--1140}},
  publisher    = {{IEEE Computer Society}},
  title        = {{{A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CP2K}}},
  doi          = {{10.1109/SC41405.2020.00084}},
  year         = {{2020}},
}

@inbook{29042,
  author       = {{Röder, Michael and Sherif, Mohamed and Saleem, Muhammad and Conrads, Felix and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges}},
  editor       = {{Tiddi, Ilaria and Lécué, Freddy and Hitzler, Pascal}},
  keywords     = {{dice group_aksw roeder sherif saleem fconrads ngonga}},
  pages        = {{73--97}},
  publisher    = {{IOS Press}},
  title        = {{{Benchmarking the Lifecycle of Knowledge Graphs}}},
  doi          = {{10.3233/SSW200012}},
  year         = {{2020}},
}

@inproceedings{21632,
  abstract     = {{FPGAs have found increasing adoption in data center applications since a new generation of high-level tools have become available which noticeably reduce development time for FPGA accelerators and still provide high-quality results. There is, however, no high-level benchmark suite available, which specifically enables a comparison of FPGA architectures, programming tools, and libraries for HPC applications. To fill this gap, we have developed an OpenCL-based open-source implementation of the HPCC benchmark suite for Xilinx and Intel FPGAs. This benchmark can serve to analyze the current capabilities of FPGA devices, cards, and development tool flows, track progress over time, and point out specific difficulties for FPGA acceleration in the HPC domain. Additionally, the benchmark documents proven performance optimization patterns. We will continue optimizing and porting the benchmark for new generations of FPGAs and design tools and encourage active participation to create a valuable tool for the community. To fill this gap, we have developed an OpenCL-based open-source implementation of the HPCC benchmark suite for Xilinx and Intel FPGAs. This benchmark can serve to analyze the current capabilities of FPGA devices, cards, and development tool flows, track progress over time, and point out specific difficulties for FPGA acceleration in the HPC domain. Additionally, the benchmark documents proven performance optimization patterns. We will continue optimizing and porting the benchmark for new generations of FPGAs and design tools and encourage active participation to create a valuable tool for the community.}},
  author       = {{Meyer, Marius and Kenter, Tobias and Plessl, Christian}},
  booktitle    = {{2020 IEEE/ACM International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC)}},
  isbn         = {{9781665415927}},
  keywords     = {{FPGA, OpenCL, High Level Synthesis, HPC benchmarking}},
  title        = {{{Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite}}},
  doi          = {{10.1109/h2rc51942.2020.00007}},
  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}},
}

@inproceedings{52936,
  author       = {{Dubslaff, Clemens and Koopmann, Patrick and Turhan, Anni-Yasmin}},
  booktitle    = {{Proceedings of the 33rd International Workshop on Description Logics (DL 2020) co-located with the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020), Online Event [Rhodes, Greece], September 12th to 14th, 2020}},
  editor       = {{Borgwardt, Stefan and Meyer, Thomas}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{Give Inconsistency a Chance: Semantics for Ontology-Mediated Verification}}},
  volume       = {{2663}},
  year         = {{2020}},
}

@inbook{35821,
  author       = {{Budde, Lea and Frischemeier, Daniel and Biehler, Rolf and Fleischer, Franz Yannik and Gerstenberger, Dietrich and Podworny, Susanne and Schulte, Carsten}},
  booktitle    = {{New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE), July 2020}},
  editor       = {{Arnold, P.}},
  publisher    = {{ISI/IASE}},
  title        = {{{Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP}}},
  year         = {{2020}},
}

@inproceedings{20510,
  author       = {{Benz, Manuel and Krogh Kristensen, Erik and Luo, Linghui and P. Borges Jr., Nataniel and Bodden, Eric and Zeller, Andreas}},
  booktitle    = {{International Conference for Software Engineering (ICSE)}},
  title        = {{{Heaps'n Leaks: How Heap Snapshots Improve Android Taint Analysis}}},
  year         = {{2020}},
}

@article{20508,
  author       = {{Nguyen Quang Do, Lisa and Bodden, Eric}},
  journal      = {{IEEE Transactions on Software Engineering}},
  title        = {{{Explaining Static Analysis with Rule Graphs}}},
  year         = {{2020}},
}

@article{60386,
  abstract     = {{<jats:p>We propose a novel approach to represent maps between two discrete surfaces of the same genus and to minimize intrinsic mapping distortion. Our maps are well-defined at every surface point and are guaranteed to be continuous bijections (surface homeomorphisms). As a key feature of our approach, only the images of vertices need to be represented explicitly, since the images of all other points (on edges or in faces) are properly defined implicitly. This definition is via unique geodesics in metrics of constant Gaussian curvature. Our method is built upon the fact that such metrics exist on surfaces of arbitrary topology, without the need for any cuts or cones (as asserted by the uniformization theorem). Depending on the surfaces' genus, these metrics exhibit one of the three classical geometries: Euclidean, spherical or hyperbolic. Our formulation handles constructions in all three geometries in a unified way. In addition, by considering not only the vertex images but also the discrete metric as degrees of freedom, our formulation enables us to simultaneously optimize the images of these vertices and images of all other points.</jats:p>}},
  author       = {{Schmidt, Patrick and Campen, Marcel and Born, Janis and Kobbelt, Leif}},
  issn         = {{0730-0301}},
  journal      = {{ACM Transactions on Graphics}},
  number       = {{4}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Inter-surface maps via constant-curvature metrics}}},
  doi          = {{10.1145/3386569.3392399}},
  volume       = {{39}},
  year         = {{2020}},
}

@article{60385,
  abstract     = {{<jats:p>We present a mesh generation algorithm for the curvilinear triangulation of planar domains with piecewise polynomial boundary. The resulting mesh consists of regular, injective higher-order triangular elements and precisely conforms with the domain's curved boundary. No smoothness requirements are imposed on the boundary. Prescribed piecewise polynomial curves in the interior, like material interfaces or feature curves, can be taken into account for precise interpolation by the resulting mesh's edges as well. In its core, the algorithm is based on a novel explicit construction of guaranteed injective Bézier triangles with certain edge curves and edge parametrizations prescribed. Due to the use of only rational arithmetic, the algorithm can optionally be performed using exact number types in practice, so as to provide robustness guarantees.</jats:p>}},
  author       = {{Mandad, Manish and Campen, Marcel}},
  issn         = {{0730-0301}},
  journal      = {{ACM Transactions on Graphics}},
  number       = {{4}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Bézier guarding}}},
  doi          = {{10.1145/3386569.3392372}},
  volume       = {{39}},
  year         = {{2020}},
}

@article{60383,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The problem of seamless parametrization of surfaces is of interest in the context of structured quadrilateral mesh generation and spline‐based surface approximation. It has been tackled by a variety of approaches, commonly relying on continuous numerical optimization to ultimately obtain suitable parameter domains. We present a general combinatorial seamless parameter domain construction, free from the potential numerical issues inherent to continuous optimization techniques in practice. The domains are constructed as abstract polygonal complexes which can be embedded in a discrete planar grid space, as unions of unit squares. We ensure that the domain structure matches any prescribed parametrization singularities (cones) and satisfies seamlessness conditions. Surfaces of arbitrary genus are supported. Once a domain suitable for a given surface is constructed, a seamless and locally injective parametrization over this domain can be obtained using existing planar disk mapping techniques, making recourse to Tutte's classical embedding theorem.</jats:p>}},
  author       = {{Zhou, Jiaran and Tu, Changhe and Zorin, Denis and Campen, Marcel}},
  issn         = {{0167-7055}},
  journal      = {{Computer Graphics Forum}},
  number       = {{2}},
  pages        = {{179--190}},
  publisher    = {{Wiley}},
  title        = {{{Combinatorial Construction of Seamless Parameter Domains}}},
  doi          = {{10.1111/cgf.13922}},
  volume       = {{39}},
  year         = {{2020}},
}

@article{60382,
  author       = {{Mandad, Manish and Campen, Marcel}},
  issn         = {{0010-4485}},
  journal      = {{Computer-Aided Design}},
  publisher    = {{Elsevier BV}},
  title        = {{{Efficient piecewise higher-order parametrization of discrete surfaces with local and global injectivity}}},
  doi          = {{10.1016/j.cad.2020.102862}},
  volume       = {{127}},
  year         = {{2020}},
}

@article{21267,
  author       = {{Budde, Lea and Schulte, Carsten and Buhl, Heike M. and Muehling, Andreas}},
  journal      = {{Seventh International Conference on Learning and Teaching in Computing and Engineeringe}},
  keywords     = {{⛔ No DOI found}},
  publisher    = {{(IEEE)}},
  title        = {{{Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows)}}},
  year         = {{2020}},
}

@article{15266,
  author       = {{Yigitbas, Enes and Jovanovikj, Ivan and Biermeier, Kai and Sauer, Stefan and Engels, Gregor}},
  journal      = {{International Journal on Software and Systems Modeling (SoSyM)}},
  publisher    = {{Springer}},
  title        = {{{Integrated Model-driven Development of Self-adaptive User Interfaces }}},
  year         = {{2020}},
}