TWINKLE: A digital-twin-building kernel for real-time computer-aided engineering

被引：12

作者：

Zambrano, V. ^{[1
]}

Rodriguez-Barrachina, R. ^{[1
]}

Calvo, S. ^{[1
]}

Izquierdo, S. ^{[1
]}

机构：

[1] Inst Tecnol Aragon ITAINNOVA, C Maria de Luna 7-8, Zaragoza 50018, Spain

来源：

SOFTWAREX | 2020年 / 11卷

关键词：

Model order reduction; PARAFAC; Machine learning; Data analysis; Tensor decomposition; PROPER GENERALIZED DECOMPOSITION; MODEL-REDUCTION; SYSTEMS;

D O I：

10.1016/j.softx.2020.100419

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

TWINKLE is a library for building families of solvers to perform Canonical Polyadic Decomposition (CPD) of tensors. The common characteristic of these solvers is that the data structure supporting the tuneable solution strategy is based on a Galerkin projection of the phase space. This allows processing and recovering tensors described by highly sparse and unstructured data. For achieving high performance, TWINKLE is written in C++ and uses the Armadillo open source library for linear algebra and scientific computing, based on LAPACK (Linear Algebra PACKage) and BLAS (Basic Linear Algebra Subprograms) routines. The library has been implemented keeping in mind its future extensibility and adaptability to fulfil the different users' needs in academia and industry regarding Reduced Order Modelling (ROM) and data analysis by means of tensor decomposition. It is especially focused on post-processing data from Computer-Aided-Engineering (CAE) simulation tools. (C) 2020 The Authors. Published by Elsevier B.V.

引用

页数：5

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