ScaLAPACK

From HP-SEE Wiki

(Difference between revisions)
Jump to: navigation, search
(→Recommendations for Configuration and Usage)
 
Line 77: Line 77:
http://icl.cs.utk.edu/lapack-forum/viewforum.php?f=4&sid=2f9d2b65f8138bbd5d38d35f988e519b
http://icl.cs.utk.edu/lapack-forum/viewforum.php?f=4&sid=2f9d2b65f8138bbd5d38d35f988e519b
-
 
-
Please describe here any common settings, configurations or conventions that would make the usage of this resource (library or tool) more interoperable or scalable across the HP-SEE resources. These recommendations should include anything that is related to the resource and is agreed upon by administrators and users, or across sites and applications. These recommendations should emerge from questions or discussions opened by site administrators or application developers, at any stage, including installation, development, usage, or adaptation for another HPC centre.
 
-
 
-
Provided descriptions should describe general or site specific aspects of resource installation, configuration and usage, or describe the guidelines or convention for deploying or using the resource within the local (user/site) or temporary environment (job). Examples are:
 
-
 
-
* Common configuration settings of execution environment
 
-
* Filesystem path or local access string
 
-
* Environment variables to be set or used by applications
 
-
* Options (e.g. additional modules) that are needed or required by applications and should be present
 
-
* Minimum quantitative values (e.g. quotas) offered by the site
 
-
* Location and format of some configuration or usage hint instructing applications on proper use of the resource or site specific policy
 
-
* Key installation or configuration settings that should be set to a common value, or locally tweaked by local site admins
 
-
* Conventions for application or job bound installation and usage of the resource
 

Latest revision as of 13:15, 23 August 2011

Contents


Authors/Maintainers

Summary

ScaLAPACK is a library of high-performance linear algebra routines for distributedmemory message-passing MIMD computers and networks of workstations supporting PVM or MPI. It is a continuation of the LAPACK project, which designed and produced analogous software for workstations, vector supercomputers, and shared-memory parallel computers. Both libraries contain routines for solving systems of linear equations, least squares problems, and eigenvalue problems. The goals of both projects are efficiency (to run as fast as possible), scalability (as the problem size and number of processors grow), reliability (including error bounds), portability (across all important parallel machines), flexibility (so users can construct new routines from well-designed parts), and ease of use (by making the interface to LAPACK and ScaLAPACK look as similar as possible). Many of these goals, particularly portability, are aided by developing and promoting standards, especially for low-level communication and computation routines. We have been successful in attaining these goals, limiting most machine dependencies to two standard libraries called the BLAS, or Basic Linear Algebra Subprograms, and BLACS, or Basic Linear Algebra Communication Subprograms. LAPACK will run on any machine where the BLAS are available, and ScaLAPACK will run on any machine where both the BLAS and the BLACS are available. Like LAPACK, the ScaLAPACK routines are based on block-partitioned algorithms in order to minimize the frequency of data movement between different levels of the memory hierarchy. The fundamental building blocks of the ScaLAPACK library are distributed memory versions (PBLAS) of the Level 1, 2 and 3 BLAS, and a set of Basic Linear Algebra Communication Subprograms (BLACS) for communication tasks that arise frequently in parallel linear algebra computations. The library is currently written in Fortran 77 (with the exception of a few symmetric eigenproblem auxiliary routines written in C to exploit IEEE arithmetic) in a Single Program Multiple Data (SPMD) style using explicit message passing for interprocessor communication. The name ScaLAPACK is an acronym for Scalable Linear Algebra PACKage, or Scalable LAPACK. ScaLAPACK is designed for heterogeneous computing and is portable on any computer that supports MPI or PVM.

Features

http://www.netlib.org/scalapack/slug/node159.html#SECTION04800000000000000000

Architectural/Functional Overview

http://www.netlib.org/scalapack/slug/node104.html#SECTION04500000000000000000 http://icl.cs.utk.edu/lapack-forum/viewforum.php?f=6&sid=2f9d2b65f8138bbd5d38d35f988e519b

Usage Overview

http://www.netlib.org/scalapack/slug/node179.html#SECTION041000000000000000000

Dependacies

HP-SEE Applications

  • HMLQCD (Hadron Masses from Lattice QCD)
  • NUQG (Numerical study of ultra-cold quantum gases)
  • GENETATOMIC (Genetic algorithms in atomic collisions)

Resource Centers

  • BG, BG
  • HPCG, BG
  • NCIT-Cluster, RO
  • NIIFI SC, HU
  • PARADOX, RS

Usage by Other Projects and Communities

  • If any

Recommendations for Configuration and Usage

http://icl.cs.utk.edu/lapack-forum/viewforum.php?f=4&sid=2f9d2b65f8138bbd5d38d35f988e519b

Retrieved from "http://hpseewiki.ipb.ac.rs/index.php/ScaLAPACK"