TY - CHAP A1 - Skoblin, Viktor A1 - Höfling, Felix A1 - Christgau, Steffen T1 - Gaining Cross-Platform Parallelism for HAL’s Molecular Dynamics Package using SYCL T2 - 29. PARS-Workshop 2023 N2 - Molecular dynamics simulations are one of the methods in scientific computing that benefit from GPU acceleration. For those devices, SYCL is a promising API for writing portable codes. In this paper, we present the case study of HAL’s MD package that has been successfully migrated from CUDA to SYCL. We describe the different strategies that we followed in the process of porting the code. Following these strategies, we achieved code portability across major GPU vendors. Depending on the actual kernels, both significant performance improvements and regressions are observed. As a side effect of the migration process, we obtained impressing speedups also for execution on CPUs. Y1 - 2023 SN - 0177-0454 VL - 36 ER - TY - JOUR A1 - Clausecker, Robert A1 - Lemire, Daniel T1 - Transcoding unicode characters with AVX-512 instructions JF - Software: Practice and Experience N2 - Intel includes in its recent processors a powerful set of instructions capable of processing 512-bit registers with a single instruction (AVX-512). Some of these instructions have no equivalent in earlier instruction sets. We leverage these instructions to efficiently transcode strings between the most common formats: UTF-8 and UTF-16. With our novel algorithms, we are often twice as fast as the previous best solutions. For example, we transcode Chinese text from UTF-8 to UTF-16 at more than 5 GiB s−1 using fewer than 2 CPU instructions per character. To ensure reproducibility, we make our software freely available as an open-source library. Our library is part of the popular Node.js JavaScript runtime. Y1 - 2023 U6 - https://doi.org/10.1002/spe.3261 VL - 53 IS - 12 SP - 2430 EP - 2462 PB - John Wiley & Sons Ltd. ER - TY - JOUR A1 - Gholami, Masoud A1 - Schintke, Florian T1 - CAWL: A Cache-aware Write Performance Model of Linux Systems JF - arXiv Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2306.05701 SP - 1 EP - 22 ER - TY - JOUR A1 - Schintke, Florian A1 - De Mecquenem, Ninon A1 - Guarino, Vanessa Emanuela A1 - Hilbrich, Marcus A1 - Lehmann, Fabian A1 - Sattler, Rebecca A1 - Sparka, Jan Arne A1 - Speckhard, Daniel A1 - Stolte, Hermann A1 - Vu, Anh Duc A1 - Leser, Ulf T1 - Validity Constraints for Data Analysis Workflows JF - arXiv Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2305.08409 SP - 1 EP - 28 ER - TY - JOUR A1 - Rodrigues Pela, Ronaldo A1 - Vona, Cecilia A1 - Lubeck, Sven A1 - Alex, Ben A1 - Gonzalez Oliva, Ignacio A1 - Draxl, Claudia T1 - Critical assessment of G0W0 calculations for 2D materials: the example of monolayer MoS2 JF - npj Comput. Mater. Y1 - 2024 U6 - https://doi.org/10.1038/s41524-024-01253-2 VL - 10 SP - 77 ER - TY - JOUR A1 - Charron, Nicholas A1 - Musil, Félix A1 - Guljas, Andrea A1 - Chen, Yaoyi A1 - Bonneau, Klara A1 - Pasos-Trejo, Aldo A1 - Jacopo, Venturin A1 - Daria, Gusew A1 - Zaporozhets, Iryna A1 - Krämer, Andreas A1 - Templeton, Clark A1 - Atharva, Kelkar A1 - Durumeric, Aleksander A1 - Olsson, Simon A1 - Pérez, Adrià A1 - Majewski, Maciej A1 - Husic, Brooke A1 - Patel, Ankit A1 - De Fabritiis, Gianni A1 - Noé, Frank A1 - Clementi, Cecilia T1 - Navigating protein landscapes with a machine-learned transferable coarse-grained model JF - Nature Chemistry N2 - The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model with similar prediction performance has been a long-standing challenge. By combining recent deep learning methods with a large and diverse training set of all-atom protein simulations, we here develop a bottom-up CG force field with chemical transferability, which can be used for extrapolative molecular dynamics on new sequences not used during model parametrization. We demonstrate that the model successfully predicts folded structures, intermediates, metastable folded and unfolded basins, and the fluctuations of intrinsically disordered proteins while it is several orders of magnitude faster than an all-atom model. This showcases the feasibility of a universal and computationally efficient machine-learned CG model for proteins. Y1 - 2025 U6 - https://doi.org/10.1038/s41557-025-01874-0 VL - 17 SP - 1284 EP - 1292 ER - TY - JOUR A1 - Krishnadas, Anirudh A1 - Charron, Nicolas A1 - Fournier, Rene T1 - Melting Transitions in Small Aluminum Clusters Simulated with Energies Approaching DFT Accuracy. JF - ACS Publications- Journal of Chemical Theory and Computation N2 - We describe a computational framework for modelling melting-like transitions in atomic clusters that combines first-principles energy calculations, global optimization, and machine-learned interatomic potentials. A diverse set of configurations is generated by global optimization, and energies are calculated by Density Functional Theory. The energies are fitted to an accuracy of 10 meV/atom or better with an Allegro E(3)-equivariant neural network potential. The model allows efficient parallel tempering Monte Carlo simulations with near DFT-level accuracy. This methodology was validated by simulating Na_20 and comparing it to earlier experimental and computational results. We used it to study melting-like transitions in Al_n+ clusters (n=9 to 16), and Al_n and Al_n^- (n=12, 13,14). The simulated heat capacity of these clusters, in particular Al_16+, are in qualitative agreement with experiments. The melting point of Al_n+ clusters with n=11-16 are well above the bulk melting point (934 K). The closed-shell Al_13- species has an exceptionally high melting point, close to 2100 K. Y1 - 2025 ER - TY - JOUR A1 - Krishnadas, Anirudh A1 - Moshi, Maryam A1 - Quintana, Ramon Alain Miranda A1 - Fournier, Rene T1 - Geometric Features and a Neural Network Classifier for Detecting Melting-Like Transitions in Clusters. JF - AIP Publications - The Journal of Chemical Physics N2 - Melting-like transitions in clusters are normally identified by a peak in the heat capacity curve C(T ) at T = Tc. Computing C(T ) requires costly simulations with millions of steps. We discuss four easily calculated functions of temperature that help detect and characterize melting-like transitions. The first, f1 (or WU ), is the width of the potential energy distribution which shows an abrupt increase near Tc. The other three are statistics of the ordered set of N(N − 1)/2 interatomic distances rij: (i) f2 is a measure of dissimilarity to the lowest energy configuration, or global minimum; (ii) f3 is the effective number of rij’s found in a small interval centered around (r1 + r2)/2 where r1, r2 are the positions of the first two peaks in the pair distribution function; and (iii) f4 is a measure of non-uniformity in the distribution of the ri j’s. Numerical tests with empirical potentials that model three types of bonding (van der Waals, covalent, and metallic) show that f1, f2, f3, and f4 produce estimates for the middle of the melting region in general agreement with Tc. An Artificial Neural Network (ANN) classifier that takes, as inputs, f2, f3, and many variants of f4, is used to calculate the solid fraction FS(T) and find the solid-liquid coexistence region between freezing and melting temperatures, [Tf , Tm]. Inflection points in f3(T ) and FS(T ) are very sensitive indicators of phase transitions. Estimates of Tc obtained from them converge one to three orders of magnitude faster, in simulation time, than those obtained with C(T ). Y1 - 2025 ER - TY - JOUR A1 - Clausecker, Robert A1 - Lemire, Daniel A1 - Schintke, Florian T1 - Faster Positional‐Population Counts for AVX2, AVX‐512, and ASIMD JF - Concurrency and Computation: Practice and Experience Y1 - 2025 U6 - https://doi.org/10.1002/cpe.70435 SN - 1532-0626 VL - 37 IS - 27-28 PB - Wiley ER - TY - JOUR A1 - Hölter, Arne A1 - Lemke, Mathias A1 - Weinzierl, Stefan A1 - Stein, Lewin T1 - Non-Reflecting Characteristic Boundary Conditions for Adjoint Time-Domain Acoustic Simulations JF - Journal of Theoretical and Computational Acoustics N2 - Accurate acoustic simulations in the free field require non-reflective boundary conditions to suppress spurious reflections at the computational domain boundaries. Although several characteristic-based formulations for direct (forward) simulations have been proposed in recent decades, the adjoint formulations of such characteristic-based boundary conditions (CBCs) have received limited atten- tion in the literature and lack a comprehensive analysis. This paper presents the derivation and evaluation of adjoint CBCs complementing the existing direct CBCs. Both the forward and adjoint CBCs are applied to the (nonlinear) Euler equations and linear acoustic equations in time-domain simulations. In this manner, the CBCs are investigated and subsequently compared to assess their respective accuracy and consistency. The CBCs were implemented using both a single-point and a zonal approach, with the former optionally combined with a sponge layer. Both approaches yielded comparable results in direct and adjoint simulations, while the zonal CBC exhibited improved ac- curacy at lower frequencies. Across the evaluated frequency range of approximately 350 – 5600 Hz, spurious reflections were attenuated by up to −70dB in both forward and adjoint cases, demon- strating the effectiveness and consistency of the proposed boundary treatment. Y1 - 2025 ER - TY - JOUR A1 - Raharinirina, Nomenjanahary Alexia A1 - Sunkara, Vikram A1 - von Kleist, Max A1 - Fackeldey, Konstantin A1 - Weber, Marcus T1 - Multi-Input data ASsembly for joint Analysis (MIASA): A framework for the joint analysis of disjoint sets of variables JF - PLOS ONE Y1 - 2024 U6 - https://doi.org/10.1371/journal.pone.0302425 VL - 19 IS - 5 PB - Public Library of Science ER -