Chapter

Applied Parallel Computing. State of the Art in Scientific Computing

Volume 4699 of the series Lecture Notes in Computer Science pp 11-23

Prospectus for the Next LAPACK and ScaLAPACK Libraries

  • James W. DemmelAffiliated withUniversity of California, Berkeley CA 94720
  • , Jack DongarraAffiliated withUniversity of Tennessee, Knoxville TN 37996Oak Ridge National Laboratory, Oak Ridge, TN 37831
  • , Beresford ParlettAffiliated withUniversity of California, Berkeley CA 94720
  • , William KahanAffiliated withUniversity of California, Berkeley CA 94720
  • , Ming GuAffiliated withUniversity of California, Berkeley CA 94720
  • , David BindelAffiliated withUniversity of California, Berkeley CA 94720
  • , Yozo HidaAffiliated withUniversity of California, Berkeley CA 94720
  • , Xiaoye LiAffiliated withUniversity of California, Berkeley CA 94720
  • , Osni MarquesAffiliated withUniversity of California, Berkeley CA 94720
    • , E. Jason RiedyAffiliated withUniversity of California, Berkeley CA 94720
    • , Christof VömelAffiliated withUniversity of California, Berkeley CA 94720
    • , Julien LangouAffiliated withUniversity of Tennessee, Knoxville TN 37996
    • , Piotr LuszczekAffiliated withUniversity of Tennessee, Knoxville TN 37996
    • , Jakub KurzakAffiliated withUniversity of Tennessee, Knoxville TN 37996
    • , Alfredo ButtariAffiliated withUniversity of Tennessee, Knoxville TN 37996
    • , Julie LangouAffiliated withUniversity of Tennessee, Knoxville TN 37996
    • , Stanimire TomovAffiliated withUniversity of Tennessee, Knoxville TN 37996

* Final gross prices may vary according to local VAT.

Get Access

Abstract

New releases of the widely used LAPACK and ScaLAPACK numerical linear algebra libraries are planned. Based on an on-going user survey (www.netlib.org/lapack-dev) and research by many people, we are proposing the following improvements: Faster algorithms, including better numerical methods, memory hierarchy optimizations, parallelism, and automatic performance tuning to accommodate new architectures; More accurate algorithms, including better numerical methods, and use of extra precision; Expanded functionality, including updating and downdating, new eigenproblems, etc. and putting more of LAPACK into ScaLAPACK; Improved ease of use, e.g., via friendlier interfaces in multiple languages. To accomplish these goals we are also relying on better software engineering techniques and contributions from collaborators at many institutions.