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Graph signal processing benefits significantly from the direct and highly adaptable supplementary techniques offered by partition of unity methods (PUMs) on graphs. In our approach, we demonstrate the generation of a partition of unity…

Numerical Analysis · Mathematics 2023-11-10 Roberto Cavoretto , Alessandra De Rossi , Sandro Lancellotti , Federico Romaniello

The performance of finite element solvers on modern computer architectures is typically memory bound for sufficiently large problems. The main cause for this is that loading matrix elements from RAM into CPU cache is significantly slower…

Numerical Analysis · Mathematics 2019-05-01 Denis Davydov , Jean-Paul Pelteret , Daniel Arndt , Paul Steinmann

An arbitrary lossless transformation in high-dimensional quantum space can be decomposed into elementary operations which are easy to implement, and an effective decomposition algorithm is important for constructing high-dimensional…

Quantum Physics · Physics 2022-12-07 Dong-Xu Chen , Junliang Jia , Pei Zhang , Chui-Ping Yang

A signed graph is an ordered pair $\Sigma=(G,\sigma),$ where $G=(V,E)$ is the underlying graph of $\Sigma$ with a signature function $\sigma:E\rightarrow \{1,-1\}$. In this article, we define $n^{th}$ power of a signed graph and discuss…

Combinatorics · Mathematics 2020-09-23 Shijin T , Germina K A , Shahul Hameed K

Preconditioning is at the heart of iterative solutions of large, sparse linear systems of equations in scientific disciplines. Several algebraic approaches, which access no information beyond the matrix itself, are widely studied and used,…

Numerical Analysis · Mathematics 2025-01-28 Jie Chen

We consider unimodular matrices $M$ such that neither $M$ nor $M^{-1}$ contain zero entries. Matrices typically exhibit a trade-off: small $M$ imply large $M^{-1}$. We investigate rare cases where both remain small, classify these matrices…

Combinatorics · Mathematics 2026-05-13 Steven Finch

To satisfy the compute and memory demands of deep neural networks, neural processing units (NPUs) are widely being utilized for accelerating deep learning algorithms. Similar to how GPUs have evolved from a slave device into a mainstream…

Hardware Architecture · Computer Science 2019-11-19 Bongjoon Hyun , Youngeun Kwon , Yujeong Choi , John Kim , Minsoo Rhu

We present a highly general implementation of fast multipole methods on graphics processing units (GPUs). Our two-dimensional double precision code features an asymmetric type of adaptive space discretization leading to a particularly…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-02-22 Anders Goude , Stefan Engblom

The simulation of the physical movement of multi-body systems at an atomistic level, with forces calculated from a quantum mechanical description of the electrons, motivates a graph partitioning problem studied in this article. Several…

Permutation polynomials over finite fields are fundamental objects as they are used in various theoretical and practical applications in cryptography, coding theory, combinatorial design, and related topics. This family of polynomials…

Information Theory · Computer Science 2022-10-20 Haode Yan , Sihem Mesnager , Xiantong Tan

We develop methods for computing with matrix groups defined over a range of infinite domains, and apply those methods to the design of algorithms for nilpotent groups. In particular, we provide a practical algorithm to test nilpotency of…

Group Theory · Mathematics 2019-07-16 A. S. Detinko , D. L. Flannery

The analysis of complex nonlinear systems is often carried out using simpler piecewise linear representations of them. A principled and practical technique is proposed to linearize and evaluate arbitrary continuous nonlinear functions using…

Optimization and Control · Mathematics 2017-11-10 Guillermo Gallego , Daniel Berjón , Narciso García

Modern graphics processors provide exceptional computa- tional power, but only for certain computational models. While they have revolutionized computation in many fields, compression has been largely unnaffected. This paper aims to explain…

Data Structures and Algorithms · Computer Science 2011-09-13 Axel Eirola

We show that the Dirac factorization method can be successfully employed to treat problems involving operators raised to a fractional power. The technique we adopt is based on an extension of the Pauli matrices and the properties of the…

Mathematical Physics · Physics 2012-09-12 D. Babusci , G. Dattoli , M. Quattromini , P. E. Ricci

In this article, we construct matrices associated to Pachner $\frac{n-1}{2}$-$\frac{n-1}{2}$ moves for odd $n$ and matrices associated to Pachner $(\frac{n}{2}-1)$-$\frac{n}{2}$ moves for even $n$. The entries of these matrices are rational…

Mathematical Physics · Physics 2025-11-26 Zheyan Wan

We present a single-node, multi-GPU programmable graph processing library that allows programmers to easily extend single-GPU graph algorithms to achieve scalable performance on large graphs with billions of edges. Directly using the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-02 Yuechao Pan , Yangzihao Wang , Yuduo Wu , Carl Yang , John D. Owens

We describe a new variational lower-bound on the minimum energy configuration of a planar binary Markov Random Field (MRF). Our method is based on adding auxiliary nodes to every face of a planar embedding of the graph in order to capture…

Machine Learning · Statistics 2011-04-08 Julian Yarkony , Alexander T. Ihler , Charless C. Fowlkes

Hierarchical matrices (usually abbreviated ${\mathcal H}$-matrices) are frequently used to construct preconditioners for systems of linear equations. Since it is possible to compute approximate inverses or $LU$ factorizations in ${\mathcal…

Numerical Analysis · Mathematics 2014-02-24 Steffen Börm , Jessica Gördes

The main result of the note describes certain optimal-score partitions, which can be interpreted as optimal resource allocations. This result is based on the fact that any nonnegative square matrix whose column sums are the same as the…

Optimization and Control · Mathematics 2019-06-27 Iosif Pinelis

In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns),…

Machine Learning · Statistics 2014-04-07 Nicolas Gillis , Stephen A. Vavasis