Skip to main content
SpringerLink
Log in

Towards Distributed Heterogenous High-Performance Computing with ViennaCL

  • Conference paper
Large-Scale Scientific Computing (LSSC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7116))

Included in the following conference series:

Abstract

One of the major drawbacks of computing with graphics adapters is the limited available memory for relevant problem sizes. To overcome this limitation for the ViennaCL library, we investigate a partitioning approach for one of the standard benchmark problems in High-Performance Computing (HPC), namely the dense matrix-matrix product. We apply this partitioning approach to problems exceeding the available memory on graphics adapters. Moreover, we investigate the applicability on distributed memory systems by facilitating the Message Passing Interface (MPI). Our approach is presented in detail and benchmark results are given.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agullo, E., et al.: Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects. Journal of Physics: Conference Series 180 (2009)

    Google Scholar 

  2. Bell, N., Garland, M.: Efficient Sparse Matrix-Vector Multiplication on CUDA. Tech. Rep. NVR-2008-004, NVIDIA (2008)

    Google Scholar 

  3. Lawlor, O.S.: Message Passing for GPGPU Clusters: cudaMPI. In: IEEE Cluster PPAC Workshop (2009)

    Google Scholar 

  4. Rupp, K., Rudolf, F., Weinbub, J.: ViennaCL - A High Level Linear Algebra Library for GPUs and Multi-Core CPUs. In: Proceedings International Workshop on GPUs and Scientific Applications (GPUScA), pp. 51–56 (2010)

    Google Scholar 

  5. Rupp, K., Weinbub, J., Rudolf, F.: Automatic Performance Optimization in ViennaCL for GPUs. In: Proceedings Parallel/High-Performance Object-Oriented Scientific Computing Workshop, POOSC (2011)

    Google Scholar 

  6. Tomov, S., Dongarra, J., Baboulin, M.: Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems. Parallel Computing 36, 232–240 (2010)

    Article  MATH  Google Scholar 

  7. Zee, F.G.V., et al.: The libflame Library for Dense Matrix Computations. Computing in Science and Engineering 11, 56–63 (2009)

    Article  Google Scholar 

  8. AMD Accelerated Parallel Processing SDK, http://developer.amd.com/gpu/amdappsdk/

  9. Boost uBLAS, http://www.boost.org/libs/numeric/ublas/

  10. Eigen, http://eigen.tuxfamily.org

  11. GotoBLAS2, http://www.tacc.utexas.edu/tacc-projects/gotoblas2/

  12. Khronos OpenCL, http://www.khronos.org/opencl/

  13. libflame, http://z.cs.utexas.edu/wiki/flame.wiki/libflame/

  14. NVIDIA CUDA, http://www.nvidia.com/cuda/

  15. SimuNova Matrix Template Library 4, http://www.simunova.com

  16. ViennaCL, http://viennacl.sourceforge.net

Download references

Author information

Authors and Affiliations

  1. Institute for Microelectronics, TU Wien, Vienna, Austria

    Josef Weinbub, Karl Rupp & Siegfried Selberherr

  2. Institute for Analysis and Scientific Computing, TU Wien, Vienna, Austria

    Karl Rupp

Authors
  1. Josef Weinbub
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karl Rupp
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siegfried Selberherr
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev, Block 25A, 1113, Sofia, Bulgaria

    Ivan Lirkov  & Svetozar Margenov  & 

  2. Department of Informatics and Mathematical Modelling, Technical University of Denmark, Richard Petersens Plads, Building 321,, 2800, Kongens Lyngby, Denmark

    Jerzy Waśniewski

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Weinbub, J., Rupp, K., Selberherr, S. (2012). Towards Distributed Heterogenous High-Performance Computing with ViennaCL. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2011. Lecture Notes in Computer Science, vol 7116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29843-1_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29843-1_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29842-4

  • Online ISBN: 978-3-642-29843-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation