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We present randomized distributed algorithms for the maximal independent set problem (MIS) that, while keeping the time complexity nearly matching the best known, reduce the energy complexity substantially. These algorithms work in the…

Data Structures and Algorithms · Computer Science 2023-05-24 Mohsen Ghaffari , Julian Portmann

The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n^3) time using Nussinov's dynamic programming algorithm. The Four-Russians method…

Quantitative Methods · Quantitative Biology 2013-08-02 Balaji Venkatachalam , Dan Gusfield , Yelena Frid

Massively-parallel graph algorithms have received extensive attention over the past decade, with research focusing on three memory regimes: the superlinear regime, the near-linear regime, and the sublinear regime. The sublinear regime is…

Data Structures and Algorithms · Computer Science 2023-03-01 Orr Fischer , Adi Horowitz , Rotem Oshman

Mutual exclusion is one of the most commonly used techniques to handle contention in concurrent systems. Traditionally, mutual exclusion algorithms have been designed under the assumption that a process does not fail while…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-19 Sahil Dhoked , Neeraj Mittal

Variational minimization of the ground-state energy as a function of the two-electron reduced density matrix (2-RDM), constrained by necessary $N$-representability conditions, provides a polynomial-scaling approach to studying strongly…

Quantum Physics · Physics 2011-11-09 Kasra Naftchi-Ardebili , Nathania W. Hau , David A. Mazziotti

In the Nonnegative Matrix Factorization (NMF) problem we are given an $n \times m$ nonnegative matrix $M$ and an integer $r > 0$. Our goal is to express $M$ as $A W$ where $A$ and $W$ are nonnegative matrices of size $n \times r$ and $r…

Data Structures and Algorithms · Computer Science 2011-11-04 Sanjeev Arora , Rong Ge , Ravi Kannan , Ankur Moitra

This work proposes an $r$-adaptive finite element method (FEM) using neural networks (NNs). The method employs the Ritz energy functional as the loss function, currently limiting its applicability to symmetric and coercive problems, such as…

A singularly (near) optimal distributed algorithm is one that is (near) optimal in \emph{two} criteria, namely, its time and message complexities. For \emph{synchronous} CONGEST networks, such algorithms are known for fundamental…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-05 Fabien Dufoulon , Shay Kutten , William K. Moses , Gopal Pandurangan , David Peleg

The Massively Parallel Computation (MPC) model serves as a common abstraction of many modern large-scale parallel computation frameworks and has recently gained a lot of importance, especially in the context of classic graph problems.…

Data Structures and Algorithms · Computer Science 2018-07-20 Sebastian Brandt , Manuela Fischer , Jara Uitto

In this paper, we consider partitioned numerical methods for quasi-static multiple-network poroelasticity (MPET) equations, generalizations of the Biot model in poroelasticity for multiple pore networks. Two partitioned numerical methods…

Numerical Analysis · Mathematics 2024-12-20 Jeonghun J. Lee

We study the design of energy-efficient algorithms for the LOCAL and CONGEST models. Specifically, as a measure of complexity, we consider the maximum, taken over all the edges, or over all the nodes, of the number of rounds at which an…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-06 Pierre Fraigniaud , Pedro Montealegre , Ivan Rapaport , Ioan Todinca

A matching in a graph is a set of edges no two of which share a common vertex. A matching M is an induced matching if no edge connects two edges of M. The problem of finding a maximum induced matching is known to be NP-hard in general and…

Discrete Mathematics · Computer Science 2014-04-28 Ruzayn Quaddoura

High-energy astrophysical systems and compact objects are frequently modeled using ideal relativistic magnetohydrodynamic (MHD) or force-free electrodynamic (FFE) simulations, with the underlying assumption that the discretisation from the…

High Energy Astrophysical Phenomena · Physics 2025-09-25 Michael P. Grehan , Tanisha Ghosal , James R. Beattie , Bart Ripperda , Oliver Porth , Fabio Bacchini

Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that…

Numerical Analysis · Mathematics 2020-02-26 Kailai Xu , Eric Darve

We further develop the large $ N $ formalism presented by some of us in earlier works in order to recursively calculate the partition function of a singly pseudoknotted RNA. We demonstrate that this calculation takes time proportional to…

Soft Condensed Matter · Physics 2009-09-29 M. Pillsbury , J. A. Taylor , H. Orland , A. Zee

This paper introduces a parallel directional fast multipole method (FMM) for solving N-body problems with highly oscillatory kernels, with a focus on the Helmholtz kernel in three dimensions. This class of oscillatory kernels requires a…

Numerical Analysis · Mathematics 2018-01-08 Austin R. Benson , Jack Poulson , Kenneth Tran , Björn Engquist , Lexing Ying

The potential of mean force (PMF) between two nano crystals (NCs) represents an effective interaction potential that can be used to study the assembly of NCs to various superstructures. For a given temperature, the effective interaction is…

Mesoscale and Nanoscale Physics · Physics 2015-12-31 Alexander Lange , Fabian Danecker , Gernot Bauer , Nadezda Gribova , Joachim Gross

Interfacial dynamics underlie a wide range of phenomena, including phase transitions, microstructure coarsening, pattern formation, and thin-film growth, and are typically described by stiff, time-dependent nonlinear partial differential…

We present an accurate, efficient and massively parallel finite-element code, DFT-FE, for large-scale ab-initio calculations (reaching $\sim 100,000$ electrons) using Kohn-Sham density functional theory (DFT). DFT-FE is based on a local…

Computational Physics · Physics 2020-01-08 Phani Motamarri , Sambit Das , Shiva Rudraraju , Krishnendu Ghosh , Denis Davydov , Vikram Gavini

We introduce a logic called distance neighborhood logic with acyclicity and connectivity constraints ($\mathsf{A\&C~DN}$ for short) which extends existential $\mathsf{MSO_1}$ with predicates for querying neighborhoods of vertex sets and for…

Data Structures and Algorithms · Computer Science 2022-12-09 Benjamin Bergougnoux , Jan Dreier , Lars Jaffke
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