Michael A. Heroux

Damian Rouson

Special Issue on the Trilinos Project, Part 2 of 2

sundanc packag trilino suit design provid highlevel compon develop highperform pde simul builtin capabl pdeconstrain optim review implic pdeconstrain optim simul design requir survey architectur sundanc problem specif compon these compon allow immedi extens forward simul use optim context show exampl use compon develop fullspac reducedspac code linear nonlinear pdeconstrain invers problem

Kevin Long

Paul T. Boggs

Bart G. van Bloemen Waanders

Sundance: High-Level Software for PDE-Constrained Optimization

the second edit comput physic rubin landau manuel paez cristian bordeianu publish wiley hit bookshelv 2007 steadili make it way physic classroom across unite state your review first encount book stanford campus book store where presum be put good use student faculti the first edit publish 1997 landau paez author comput physic 1st edn wiley new york 1997 rubin landau veri experienc comput physicist staff member oregon state univers corval where direct comput physic undergradu cours teach use book landau incred activ teacher put mild code book suppli accompani dvd also post applet video lectur his cours his web page http wwwphysicsorstedu rubin

Adrian Brown

Book Review

templatebas generic program approach present part seri paper sci program 20 2012 197219 separ develop effort program physic model from comput addit quantiti deriv need embed analysi algorithm paper describ implement detail use templatebas generic program approach simul analysi partial differenti equat pdes detail sever hurdl have encount some softwar infrastructur develop overcom them end demonstr where present shape optim uncertainti quantif result pde applic

Roger P. Pawlowski

Eric T. Phipps

Andrew G. Salinger

Steven J. Owen

Christopher M. Siefert

Matthew L. Staten

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations

solver larg spars linear system come two categori direct iter amesos2 packag trilino softwar project provid direct method belo anoth trilino packag provid iter method amesos2 offer common interfac mani differ spars matrix factor code can handl ani implement spars matric vector via easytoextend trait interfac can also factor matric whose entri have arbitrari scalar type enabl extendedprecis mixedprecis algorithm belo includ mani differ iter method solv larg spars linear system leastsquar problem unlike compet iter solver librari belo complet decoupl algorithm from implement under linear algebra object this let belo exploit latest hardwar without chang code belo favor algorithm solv higherlevel problem multipl simultan linear system sequenc relat linear system faster than standard algorithm the packag also support extendedprecis mixedprecis algorithm togeth amesos2 belo form complet suit spars linear solver

Eric Bavier

Mark Hoemmen

Sivasankaran Rajamanickam

Heidi Thornquist

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

Dan Nagle

this paper introduc playa highlevel user interfac layer compos algorithm complex multiphys problem out object from other trilino packag among other featur playa provid veri highperform overload oper implement through express templat mechan paper give overview central playa object from user perspect show applic sequenc increas complex solver algorithm provid time result playa overload oper other function briefli survey some implement issu involv

Victoria E. Howle

Robert C. Kirby

Brian Brennan

Kimberly Kennedy

Playa: High-Performance Programmable Linear Algebra

pytrilino set python interfac compil trilino packag this collect support serial parallel dens linear algebra serial parallel spars linear algebra direct iter linear solut techniqu algebra multilevel precondition nonlinear solver continu algorithm eigensolv partit algorithm also includ varieti relat util function class includ distribut color algorithm matrix generat pytrilino vector object compat popular numpi python packag python front end compil librari pytrilino take advantag flexibl eas use python effici under fortran numer kernel this paper cover recent previous unpublish advanc pytrilino packag

William F. Spotz

PyTrilinos: Recent Advances in the Python Interface to Trilinos

muelu librari within trilino softwar project overview trilino technic report sand20032927 sandia nation laboratori 2003 provid framework parallel multigrid precondit method larg spars linear system while provid effici implement modern multigrid method base smooth aggreg energi minim concept muelu design custom extend this articl give overview design consider muelu packag user interfac intern design data manag usag modern softwar construct leverag trilino capabl linear algebra oper advanc applic

Jérémie Gaidamour

Jonathan Hu

Chris Siefert

Ray Tuminaro

Design Considerations for a Flexible Multigrid Preconditioning Library

present first threedimension partial differenti equat solver built atop recent releas opensourc fortrilino packag http trilinossandiagov packag fortrilino fortrilino current provid portabl objectori fortran 2003 interfac packag epetra aztecoo pliri trilino librari framework acm tran math softw 31 3 2005 397423 epetra provid distribut matrix vector storag basic linear algebra calcul pliri provid direct solver dens linear system aztecoo provid iter spars linear solver demonstr how build parallel applic encapsul messag pass interfac mpi without requir user make direct call mpi except startup shutdown the present exampl demonstr level effort requir set highord finitediffer solut cartesian grid the exampl employ abstract data type adt calculus sci program 16 4 2008 329339 empow programm write serial code lowerlevel abstract resolv distributedmemori parallel implement the adt calculus use compil fortran construct resembl mathemat formul partial differenti equat interest

Karla Morris

Damian W.I. Rouson

M. Nicole Lemaster

Salvatore Filippone

Exploring Capabilities within ForTrilinos by Solving the 3D Burgers Equation

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.

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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.

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Scientific Programming | Hindawi

Scientific Programming

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

Scientific Programming

A New Overview of the Trilinos Project – Part 2

A New Overview of the Trilinos Project – Part 2

Articles

Special Issue on the Trilinos Project, Part 2 of 2

Sundance: High-Level Software for PDE-Constrained Optimization

Book Review

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

Book Review

Playa: High-Performance Programmable Linear Algebra

PyTrilinos: Recent Advances in the Python Interface to Trilinos

Design Considerations for a Flexible Multigrid Preconditioning Library

Exploring Capabilities within ForTrilinos by Solving the 3D Burgers Equation