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ScaLAPACK (Scalable LAPACK) is a linear algebra library for parallel computers. Routines are available to diagonalize or solve dense and narrow band systems of linear equations.

ScaLAPACK implements block-oriented LAPACK linear algebra routines, adding a special set of communication routines to copy blocks of data between processors as required. Similar to LAPACK, a single subroutine call typically carries out the necessary computations.

ScaLAPACK installations include the following libraries: scalapack, redist, pblas, tools, blacs, blacsCinit, and blacsF77init.

An meeting with Professor Choi J. which a member of ScaLAPACK

• What is the Block-Oriented?
• Why use shared memory instead of files?
• Are there any ways (or methods) to handle to files?
• What are the relative merits and demerits of the ScaLAPACK?
• Performance Results?
  

And, In the last question

• What do you think about the Hama approaches?
• Is Hama a good fit with a blocked algorithms?