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Graph embedding aims at learning a vector-based representation of vertices that incorporates the structure of the graph. This representation then enables inference of graph properties. Existing graph embedding techniques, however, do not…

In this paper, we propose an orbital iteration based parallel approach for electronic structure calculations. This approach is based on our understanding of the single-particle equations of independent particles that move in an effective…

Numerical Analysis · Mathematics 2014-11-06 Xiaoying Dai , Xingao Gong , Aihui Zhou , Jinwei Zhu

Satisfiability-based verification techniques, leveraging modern Boolean satisfiability (SAT) and Satisfiability Modulo Theories (SMT) solvers, have demonstrated efficacy in addressing practical problem instances within program analysis.…

Logic in Computer Science · Computer Science 2025-09-23 Markus Krahl , Matthias Güdemann , Stefan Wallentowitz

A class of abstract nonlinear time-periodic evolution problems is considered which arise in electrical engineering and other scientific disciplines. An efficient solver is proposed for the systems arising after discretization in time based…

Numerical Analysis · Mathematics 2025-03-03 Herbert Egger , Andreas Schafelner

We present an analysis of different methods to calculate the classical electrostatic Hartree potential created by charge distributions. Our goal is to provide the reader with an estimation on the performance ---in terms of both numerical…

We describe an important addition to the parallel implementation of our generalized NLTE stellar atmosphere and radiative transfer computer program PHOENIX. In a previous paper in this series we described data and task parallel algorithms…

Astrophysics · Physics 2009-10-30 E. Baron , Peter H. Hauschildt

As multicore computing is now standard, it seems irresponsible for constraints researchers to ignore the implications of it. Researchers need to address a number of issues to exploit parallelism, such as: investigating which constraint…

Artificial Intelligence · Computer Science 2018-03-30 Ian P. Gent , Ciaran McCreesh , Ian Miguel , Neil C. A. Moore , Peter Nightingale , Patrick Prosser , Chris Unsworth

Real-time embedded systems require precise timing and fault detection to ensure correct behavior. Traditional tracing tools often rely on local desktops with limited processing and storage capabilities, which hampers large-scale analysis.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-29 David Jannis Schmidt , Grigory Fridman , Florian von Zabiensky

The time domain analysis of eddy current problems often requires the simulation of long time intervals, e.g. until a steady state is reached. Fast-switching excitations e.g. in pulsedwidth modulated signals require in addition very small…

Numerical Analysis · Mathematics 2021-01-05 Idoia Cortes Garcia , Iryna Kulchytska-Ruchka , Markus Clemens , Sebastian Schöps

In this era of large-scale data, distributed systems built on top of clusters of commodity hardware provide cheap and reliable storage and scalable processing of massive data. Here, we review recent work on developing and implementing…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-28 Jiyan Yang , Xiangrui Meng , Michael W. Mahoney

The ability to leverage large-scale hardware parallelism has been one of the key enablers of the accelerated recent progress in machine learning. Consequently, there has been considerable effort invested into developing efficient parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-19 Vitaly Aksenov , Dan Alistarh , Janne H. Korhonen

Parallel batched data structures are designed to process synchronized batches of operations in a parallel computing model. In this paper, we propose parallel combining, a technique that implements a concurrent data structure from a parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-14 Vitaly Aksenov , Petr Kuznetsov , Anatoly Shalyto

Coded distributed computing has been considered as a promising technique which makes large-scale systems robust to the "straggler" workers. Yet, practical system models for distributed computing have not been available that reflect the…

Information Theory · Computer Science 2019-01-17 Muah Kim , Jy-yong Sohn , Jaekyun Moon

Unmanned aerial vehicles (UAVs) are becoming a viable platform for sensing and estimation in a wide variety of applications including disaster response, search and rescue, and security monitoring. These sensing UAVs have limited battery and…

Networking and Internet Architecture · Computer Science 2022-06-08 Lorson Blair , Carlos A. Varela , Stacy Patterson

The modeling of atmospheric processes in the context of weather and climate simulations is an important and computationally expensive challenge. The temporal integration of the underlying PDEs requires a very large number of time steps,…

Numerical Analysis · Mathematics 2020-01-03 Francois P. Hamon , Martin Schreiber , Michael L. Minion

We present a hybrid approach combining isogeometric analysis with deep operator networks to solve electromagnetic scattering problems. The neural network takes a computer-aided design representation as input and predicts the electromagnetic…

Computational Engineering, Finance, and Science · Computer Science 2024-11-19 Merle Backmeyer , Stefan Kurz , Matthias Möller , Sebastian Schöps

We compute multiprecision solutions of the Lane-Emden equation. This differential equation arises when introducing the well-known polytropic model into the equation of hydrostatic equilibrium for a nondistorted star. Since such…

Solar and Stellar Astrophysics · Physics 2016-04-28 Vassilis S. Geroyannis , Vasileios G. Karageorgopoulos

Many integral equation-based methods are available for problems of time-harmonic electromagnetic scattering from perfect electric conductors. Among the many challenges that arise in such calculations are the avoidance of spurious…

Numerical Analysis · Mathematics 2025-07-17 Felipe Vico , Leslie Greengard , Michael O'Neil , Manas Rachh

Open-source matters, not just to the current cohort of HPC users but also to potential new HPC communities, such as machine learning, themselves often rooted in open-source. Many of these potential new workloads are, by their very nature,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-27 Nick Brown , Oliver Thomson Brown , J. Mark Bull

This paper considers the challenging computational task of estimating nested expectations. Existing algorithms, such as nested Monte Carlo or multilevel Monte Carlo, are known to be consistent but require a large number of samples at both…

Machine Learning · Statistics 2025-06-05 Zonghao Chen , Masha Naslidnyk , François-Xavier Briol