Intrepid is a Trilinos package for advanced discretizations of Partial Differential Equations (PDEs). The package provides a comprehensive set of tools for local, cell-based construction of a wide range of numerical methods for PDEs. This paper describes the mathematical ideas and software design principles incorporated in the package. We also provide representative examples showcasing the use of Intrepid both in the context of numerical PDEs and the more general context of data analysis.

P. Bochev

H.C. Edwards

R.C. Kirby

K. Peterson

D. Ridzal

Solving PDEs with Intrepid

We present Tpetra, a Trilinos package for parallel linear algebra primitives implementing the Petra object model. We describe Tpetra's design, based on generic programming via C++ templated types and template metaprogramming. We discuss some benefits of this approach in the context of scientific computing, with illustrations consisting of code and notable empirical results.

C.G. Baker

M.A. Heroux

Tpetra, and the Use of Generic Programming in Scientific Computing

Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs), and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1) manycore compute devices each with its own memory space, (2) data parallel kernels and (3) multidimensional arrays. Kernel execution performance is, especially for NVIDIA&#xae; devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices &#x2013; potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1) separating data access patterns from computational kernels through a multidimensional array API and (2) introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].

H. Carter Edwards

Daniel Sunderland

Vicki Porter

Chris Amsler

Sam Mish

Manycore Performance-Portability: Kokkos Multidimensional Array Library

Partitioning and load balancing are important problems in scientific computing that can be modeled as combinatorial problems using graphs or hypergraphs. The Zoltan toolkit was developed primarily for partitioning and load balancing to support dynamic parallel applications, but has expanded to support other problems in combinatorial scientific computing, including matrix ordering and graph coloring. Zoltan is based on abstract user interfaces and uses callback functions. To simplify the use and integration of Zoltan with other matrix-based frameworks, such as the ones in Trilinos, we developed Isorropia as a Trilinos package, which supports most of Zoltan's features via a matrix-based interface. In addition to providing an easy-to-use matrix-based interface to Zoltan, Isorropia also serves as a platform for additional matrix algorithms. In this paper, we give an overview of the Zoltan and Isorropia toolkits, their design, capabilities and use. We also show how Zoltan and Isorropia enable large-scale, parallel scientific simulations, and describe current and future development in the next-generation package Zoltan2.

Erik G. Boman

&#xdc;mit V. &#xc7;ataly&#xfc;rek

C&#xe9;dric Chevalier

Karen D. Devine

The Zoltan and Isorropia Parallel Toolkits for Combinatorial Scientific Computing: Partitioning, Ordering and Coloring

An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering.

Roger P. Pawlowski

Eric T. Phipps

Andrew G. Salinger

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part I: Template-Based Generic Programming

Since An Overview of the Trilinos Project [ACM Trans. Math. Softw. 31(3) (2005), 397&#x2013;423] was published in 2005, Trilinos has grown significantly. It now supports the development of a broad collection of libraries for scalable computational science and engineering applications, and a full-featured software infrastructure for rigorous lean/agile software engineering. This growth has created significant opportunities and challenges. This paper focuses on some of the most notable changes to the Trilinos project in the last few years. At the time of the writing of this article, the current release version of Trilinos was 10.12.2.

Michael A. Heroux

James M. Willenbring

A New Overview of The Trilinos Project

Trilinos I/O Support (Trios) is a new capability area in Trilinos that serves two important roles: (1) it provides and supports I/O libraries used by in-production scientific codes; (2) it provides a research vehicle for the evaluation and distribution of new techniques to improve I/O on advanced platforms. This paper provides a brief overview of the production-grade I/O libraries in Trios as well as some of the ongoing research efforts that contribute to the experimental libraries in Trios.

Ron A. Oldfield

Gregory D. Sjaardema

Gerald F. Lofstead II

Todd Kordenbrock

Trilinos I/O Support (Trios)

Damian Rouson

Special Issue on The Trilinos Project, Part 1 of 2

About this journal

Scientific Programming provides a forum for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.

Journal profile

Meet the editorial board

Chief Editor&nbsp;Professor Tramontana&nbsp;is based at the University of Catania and his research primarily concerns the areas of software engineering and distributed systems.

Editor spotlight

Submit your proposal

Do you think there is an emerging area of research that really needs to be highlighted? Or an existing research area that has been overlooked or would benefit from deeper investigation? Raise the profile of a research area by leading a Special Issue.

Special Issues

Author guidelines

Editorial board

Databases and indexing

title

Scientific Programming provides a forum for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.

description

https://images.hindawi.com/journals/sp/sp.banner.jpg

twitter:card

twitter:description

twitter:site

twitter:title

twitter:url

twitter:image

Scientific Programming | Hindawi

Scientific Programming

This Issue is now open for submissions.
Papers are published upon acceptance, regardless of the Special Issue publication date.