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Accurate triangulation of the domain plays a pivotal role in computing the numerical approximation of the differential operators. A good triangulation is the one which aids in reducing discretization errors. In a standard collocation…

Numerical Analysis · Mathematics 2024-02-22 Shylaja G. , Kesavulu Naidu V. , Venkatesh B. , S. M. Mallikarjunaiah

Matrix decompositions are ubiquitous in machine learning, including applications in dimensionality reduction, data compression and deep learning algorithms. Typical solutions for matrix decompositions have polynomial complexity which…

Machine Learning · Computer Science 2024-03-13 Łukasz Struski , Paweł Morkisz , Przemysław Spurek , Samuel Rodriguez Bernabeu , Tomasz Trzciński

The main objective of this work consists in analyzing sub-structuring method for the parallel solution of sparse linear systems with matrices arising from the discretization of partial differential equations such as finite element, finite…

Numerical Analysis · Mathematics 2021-08-31 Abal-Kassim Cheik Ahamed , Frédéric Magoulès

General Purpose Graphic Processing Unit(GPGPU) is used widely for achieving high performance or high throughput in parallel programming. This capability of GPGPUs is very famous in the new era and mostly used for scientific computing which…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-10 Vajira Thambawita , Roshan G. Ragel , Dhammike Elkaduwe

Matrix Factorization (MF) on large scale data takes substantial time on a Central Processing Unit (CPU). While Graphical Processing Unit (GPU)s could expedite the computation of MF, the available memory on a GPU is finite. Leveraging GPUs…

Machine Learning · Computer Science 2023-04-28 Prasad Bhavana , Vineet Padmanabhan

In this paper we present a methodology for data accesses when solving batches of Tridiagonal and Pentadiagonal matrices that all share the same left-hand-side (LHS) matrix. The intended application is to the numerical solution of Partial…

Computational Physics · Physics 2021-07-13 Enda Carroll , Andrew Gloster , Miguel D. Bustamante , Lennon Ó' Náraigh

Boundary element methods (BEM) reduce a partial differential equation in a domain to an integral equation on the domain's boundary. They are particularly attractive for solving problems on unbounded domains, but handling the dense matrices…

Numerical Analysis · Mathematics 2020-06-30 Steffen Börm

The IEEE 754-2008 standard recommends the correct rounding of some elementary functions. This requires to solve the Table Maker's Dilemma which implies a huge amount of CPU computation time. We consider in this paper accelerating such…

Mathematical Software · Computer Science 2013-06-06 Pierre Fortin , Mourad Gouicem , Stef Graillat

We present a fast and memory-efficient algorithm for transient, space-time-domain, and elastodynamic boundary-integral analysis. Associated data-sparse approximations and operations are named fast domain partitioning hierarchical matrices…

Computational Physics · Physics 2026-03-20 Dye SK Sato , Ryosuke Ando

We report an efficient algorithm for calculating momentum-space integrals in solid state systems on modern graphics processing units (GPUs). Our algorithm is based on the tetrahedron method, which we demonstrate to be ideally suited for…

Computational Physics · Physics 2018-06-19 Daniel Guterding , Harald O. Jeschke

This paper is devoted to GPU kernel optimization and performance analysis of three tensor-product operators arising in finite element methods. We provide a mathematical background to these operations and implementation details. Achieving…

Mathematical Software · Computer Science 2017-11-15 Kasia Świrydowicz , Noel Chalmers , Ali Karakus , Timothy Warburton

We investigate numerically efficient approximations of eigenspaces associated to symmetric and general matrices. The eigenspaces are factored into a fixed number of fundamental components that can be efficiently manipulated (we consider…

Machine Learning · Computer Science 2021-09-29 Cristian Rusu , Lorenzo Rosasco

Edge computing's growing prominence, due to its ability to reduce communication latency and enable real-time processing, is promoting the rise of high-performance, heterogeneous System-on-Chip solutions. While current approaches often…

Artificial Intelligence · Computer Science 2024-09-24 Rakshith Jayanth , Neelesh Gupta , Viktor Prasanna

Linearly implicit Runge-Kutta methods with approximate matrix factorization can solve efficiently large systems of differential equations that have a stiff linear part, e.g. reaction-diffusion systems. However, the use of approximate…

Numerical Analysis · Computer Science 2014-08-19 Hong Zhang , Adrian Sandu , Paul Tranquilli

The graphics processing unit (GPU) has emerged as a powerful and cost effective processor for general performance computing. GPUs are capable of an order of magnitude more floating-point operations per second as compared to modern central…

Computation · Statistics 2012-07-24 Mark Franey , Pritam Ranjan , Hugh Chipman

In this paper, we present algorithms and implementations for the end-to-end GPU acceleration of matrix-free low-order-refined preconditioning of high-order finite element problems. The methods described here allow for the construction of…

Mathematical Software · Computer Science 2023-06-05 Will Pazner , Tzanio Kolev , Jean-Sylvain Camier

This paper presents a Graphics Processing Units (GPUs) acceleration method of an iterative scheme for gas-kinetic model equations. Unlike the previous GPU parallelization of explicit kinetic schemes, this work features a fast converging…

Computational Physics · Physics 2020-01-08 Lianhua Zhu , Peng Wang , Songze Chen , Zhaoli Guo , Yonghao Zhang

Electro-quasistatic field problems involving nonlinear materials are commonly discretized in space using finite elements. In this paper, it is proposed to solve the resulting system of ordinary differential equations by an explicit…

Computational Engineering, Finance, and Science · Computer Science 2017-09-26 Christian Richter , Sebastian Schöps , Markus Clemens

This paper introduces an efficient and generic framework for finite-element simulations under an implicit time integration scheme. Being compatible with generic constitutive models, a fast matrix assembly method exploits the fact that…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-12 Ziqiu Zeng , Hadrien Courtecuisse

Computational fluid dynamics and fluid-structure interaction simulations involving moving and deforming bodies is extremely hard. In this work, we present a graphical processing unit (GPU) optimized implementation of the sharp-interface…

Computational Physics · Physics 2026-05-07 Sushrut Kumar , Joshua Romero , Jung-Hee Seo , Massimiliano Fatica , Rajat Mittal