article

Tpetra, and the use of generic programming in scientific computing

Authors:

M. A. HerouxAuthors Info & Claims

Scientific Programming, Volume 20, Issue 2

Pages 115 - 128

https://doi.org/10.1155/2012/693861

Published: 01 April 2012 Publication History

Abstract

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.

References

[1]

D.H. Bailey, High-precision software directory, http://crd.lbl. gov/~dhbailey/mpdist/, 2011.

[2]

D.H. Bailey, Y. Hida, X.S. Li and O. Thompson, ARPREC: an arbitrary precision computation package, LBNL Technical Report 53651, 2002.

[3]

C.G. Baker, Developing large-scale scientific software for generic multi-core nodes, in: SIAM Conference on Parallel Processing for Scientific Computing, February 2010, available at: http://info.ornl.gov/sites/publications/Files/Pub23325.pptx.

[4]

C.G. Baker, Parallel programming with Kokkos and Tpetra, Trilinos User Group 2010, November 2010, available at: http://info.ornl.gov/sites/publications/Files/Pub27346.pdf.

[5]

C.G. Baker, Tpetra conjugate gradient RTI example, available at: http://trilinos.sandia.gov/packages/docs/dev/packages/tpetra/doc/html/RTIInlineCG_8hpp_source.html or source file Trilinos/packages/tpetra/example/RTInterface/RTIInlineCG. hpp, 2011.

[6]

C.G. Baker, Tpetra recursive mixed-precision conjugate gradient example, file:///Users/ogb/Trilinos/packages/tpetra/doc/html/MultiPrecCG_8hpp_source.html or source file Trilinos/- packages/tpetra/example/MultiPrec/MultiPrecCG.hpp, 2011.

[7]

C.G. Baker, H.C. Edwards, M.A. Heroux and A.B. Williams, An abstract model for programming multi-core nodes, in: SIAM Annual Meeting, July 2009 (contact author for slides).

[8]

C.G. Baker, H.C. Edwards, M.A. Heroux and A.B. Williams, A light-weight API for multicore programming, in: Proc. 18th Euromicro International Conference on Parallel, Distributed and Network-Based Computing, February 2010, available at: http://info.ornl.gov/sites/publications/Files/Pub23109.pdf.

Digital Library

[9]

C.G. Baker, U.L. Hetmaniuk, R.B. Lehoucq and H.K. Thornquist, Anasazi software for the numerical solution of largescale eigenvalue problems, ACM Trans. Math. Softw. 36 (2009), 13:1-13:23.

Digital Library

[10]

S. Balay, J. Brown, K. Buschelman, V. Eijkhout, W.D. Gropp, D. Kaushik, M.G. Knepley, L.C. McInnes, B.F. Smith and H. Zhang, PETSc users manual, Technical Report ANL-95/11, Revision 3.1, Argonne National Laboratory, 2010.

[11]

S. Balay, J. Brown, K. Buschelman, W.D. Gropp, D. Kaushik, M.G. Knepley, L.C. McInnes, B.F. Smith and H. Zhang, PETSc homepage, http://www.mcs.anl.gov/petsc, 2011.

[12]

S. Balay, W.D. Gropp, L.C. McInnes and B.F. Smith, Efficient management of parallelism in object oriented numerical software libraries, in: Modern Software Tools in Scientific Computing, E. Arge, A.M. Bruaset and H.P. Langtangen, eds, Birkhäuser, New York, 1997, pp. 163-202.

[13]

R. Bartlett, Teuchos C++ memory management classes, idioms, and related topic, SNL Technical Report SAND2010- 2234, 2010.

[14]

E. Boman, K. Devine, R. Heaphy, B. Hendrickson, M. Heroux and R. Preis, Ldrd report: parallel repartitioning for optimal solver performance, SNL Technical Report SAND2004-0365, 2004.

[15]

T.A. Davis and Y. Hu, The University of Florida sparse matrix collection, available at: http://www.cise.ufl.edu/research/sparse/matrices.

[16]

Epetra 10.6 release notes, http://trilinos.sandia.gov/changelog- 10.6.html, 2010.

[17]

M.A. Heroux, R.A. Bartlett, V.E. Howle, R.J. Hoekstra, J.J. Hu, T.G. Kolda, R.B. Lehoucq, K.R. Long, R.P. Pawlowski, E.T. Phipps, A.G. Salinger, H.K. Thornquist, R.S. Tuminaro, J.M. Willenbring, A. Williams and K.S. Stanley, An overview of the trilinos project, ACM Trans. Math. Softw. 31 (2005), 397-423.

Digital Library

[18]

Y. Hida, X.S. Li and D.H. Bailey, Algorithms for quad-double precision floating point arithmetic, in: Proc. 15th IEEE Symposium on Computer Arithmetic, IEEE Computer Society, Washington, DC, USA, 2001, pp. 155-162.

[19]

J. Hoberock and N. Bell, Thrust: a parallel template library, Version 1.3.0, available at: http://www.meganewtons.com, 2010.

[20]

Intel Corporation, Intel threading building blocks homepage, http://www.threadingbuildingblocks.org, 2006.

[21]

R.B. Lehoucq, D.C. Sorensen and C. Yang, Arpack Users' Guide, Soc. Industr. Appl. Math., Philadephia, PA, 1998.

[22]

R.B. Lehoucq, D.C. Sorensen and C. Yang, ARPACK homepage, http://www.caam.rice.edu/software/ARPACK, 2011.

[23]

NVIDIA Corporation, NVIDIA CUDA homepage, http://www.nvidia.com/cuda, 2009.

[24]

OpenMP ARB, OpenMP official homepage, http://openmp. org/wp, 1997.

[25]

E.T. Phipps, R.A. Bartlett, D.M. Gay and R.J. Hoekstra, Large-scale transient sensitivity analysis of a radiationdamaged bipolar junction transistor via automatic differentiation, in: Advances in Automatic Differentiation, C.H. Bischof, H.M. Bcker, P. Hovland, U. Naumann and J. Utke, eds, Lecture Notes in Computational Science and Engineering, Vol. 64, Springer, Berlin, 2008, pp. 351-362.

[26]

J. Reinders, Intel Threading Building Blocks, 1st edn, O'Reilly & Associates, Sebastopol, CA, 2007.

[27]

A. Stathopoulos and J.R. McCombs, PRIMME: preconditioned iterative multimethod eigensolver-methods and software description, ACM Trans. Math. Softw. 37 (2010), 21:1- 21:30.

Digital Library

[28]

A. Stathopoulos and J.R. McCombs, PRIMME homepage, http://www.cs.wm.edu/~andreas/software, 2011.

[29]

B. Stroustrup, The C++ Programming Language: Special Edition, 3rd edn, Addison-Wesley, Reading, MA, 2000.

[30]

The Khronos Group, OpenCL overview, available at: http://www.khronos.org/opencl, 2008.

[31]

The Open Group, ¿pthread.h¿, http://www.opengroup.org/onlinepubs/007908799/xsh/pthread.h.html, 1997.

[32]

Trilinos homepage, http://trilinos.org, 2012.

[33]

Trilinos packages list, http://trilinos.sandia.gov/packages/.

[34]

Wikipedia, C++ classes - Wikipedia, the free encyclopedia, available at: http://en.wikipedia.org/w/index.php?title= C%2B%2B_classes, 2012 (online; accessed 18 April 2012).

[35]

Wikipedia, Template (C++) - Wikipedia, the free encyclopedia, http://en.wikipedia.org/w/index.php?title=Template_ (C%2B%2B) (online; accessed 18 April 2012).

Cited By

Watkins JCarlson MShan KTezaur IPerego MBertagna LKao CHoffman MPrice S(2023)Performance portable ice-sheet modeling with MALIInternational Journal of High Performance Computing Applications10.1177/1094342023118368837:5(600-625)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1177/10943420231183688
Liegeois KPerego MHartland T(2023)PyAlbanyJournal of Computational and Applied Mathematics10.1016/j.cam.2022.115037425:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.cam.2022.115037
Spies LBienz AMoulton DOlson LReisner A(2022)TauschParallel Computing10.1016/j.parco.2022.102973114:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.parco.2022.102973
Show More Cited By

Tpetra, and the use of generic programming in scientific computing
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages

Recommendations

A Pthreads Wrapper for Fortran 2003

With the advent of multicore processors, numerical and mathematical software relies on parallelism in order to benefit from hardware performance increases. We present the design and use of a Fortran 2003 wrapper for POSIX threads, called forthreads. ...
A comparative study of language support for generic programming
OOPSLA '03: Proceedings of the 18th annual ACM SIGPLAN conference on Object-oriented programing, systems, languages, and applications

Many modern programming languages support basic generic programming, sufficient to implement type-safe polymorphic containers. Some languages have moved beyond this basic support to a broader, more powerful interpretation of generic programming, and ...
Efficient run-time dispatching in generic programming with minimal code bloat

Generic programming with C++ templates results in efficient but inflexible code: efficient, because the exact types of inputs to generic functions are known at compile time; inflexible because they must be known at compile time. We show how to achieve ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Scientific Programming

Scientific Programming Volume 20, Issue 2

A New Overview of the Trilinos Project --Part 1

April 2012

138 pages

Issue’s Table of Contents

Publisher

IOS Press

Netherlands

Publication History

Published: 01 April 2012

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 23 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Watkins JCarlson MShan KTezaur IPerego MBertagna LKao CHoffman MPrice S(2023)Performance portable ice-sheet modeling with MALIInternational Journal of High Performance Computing Applications10.1177/1094342023118368837:5(600-625)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1177/10943420231183688
Liegeois KPerego MHartland T(2023)PyAlbanyJournal of Computational and Applied Mathematics10.1016/j.cam.2022.115037425:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.cam.2022.115037
Spies LBienz AMoulton DOlson LReisner A(2022)TauschParallel Computing10.1016/j.parco.2022.102973114:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.parco.2022.102973
Bogle IDevine KPerego MRajamanickam SSlota G(2019)A Parallel Graph Algorithm for Detecting Mesh Singularities in Distributed Memory Ice Sheet SimulationsProceedings of the 48th International Conference on Parallel Processing10.1145/3337821.3337841(1-10)Online publication date: 5-Aug-2019
https://dl.acm.org/doi/10.1145/3337821.3337841
Kotteda VKumar VSpotz W(2018)Performance of preconditioned iterative solvers in MFiX---Trilinos for fluidized bedsThe Journal of Supercomputing10.1007/s11227-018-2415-574:8(4104-4126)Online publication date: 1-Aug-2018
https://dl.acm.org/doi/10.1007/s11227-018-2415-5
Kreutzer MThies JRöhrig-Zöllner MPieper AShahzad FGalgon MBasermann AFehske HHager GWellein G(2017)GHOSTInternational Journal of Parallel Programming10.1007/s10766-016-0464-z45:5(1046-1072)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1007/s10766-016-0464-z
Papadopoulos IThomas NFidel AAmato NRauchwerger LBhuyan LChong FSarkar V(2015)STAPL-RTSProceedings of the 29th ACM on International Conference on Supercomputing10.1145/2751205.2751233(425-434)Online publication date: 8-Jun-2015
https://dl.acm.org/doi/10.1145/2751205.2751233
Elliott JHoemmen MMueller FKielmann THildebrand DTaufer M(2015)A Numerical Soft Fault Model for Iterative Linear SolversProceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing10.1145/2749246.2749254(271-274)Online publication date: 15-Jun-2015
https://dl.acm.org/doi/10.1145/2749246.2749254
Bachelet BMahul AYon L(2013)Template metaprogramming techniques for concept-based specializationScientific Programming10.1155/2013/58139721:1-2(43-61)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1155/2013/581397

View Options

View options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents