ANNOUNCEMENT: NAG Launches PINEAPL Library

The Numerical Algorithms Group Ltd (NAG) is pleased to announce the availability of Release 1 of the PINEAPL Library. This library has been developed in the HPCN Fourth Framework project on Parallel Industrial NumErical Applications and Portable Libraries (PINEAPL), in which NAG is currently coordinating. This Library is the result of a coordinated effort by the Center for Research on Parallel Computing and Supercomputers National Research Council (Naples, Italy), NAG Ltd (Oxford, UK) and the Centre for Novel Computing of the University of Manchester (Manchester, UK). One of the main goals of the project is to increase the suitability of the existing NAG Parallel Library for dealing with computationally intensive industrial applications by appropriately extending the range of library routines. Additionally, several industrial applications are being ported onto parallel computers within the PINEAPL project by replacing sequential code sections with calls to appropriate parallel library routines. Consequently, the coverage of the PINEAPL Library is to a large extent driven by the demands of the end-user applications with the project and focuses on three major numerical areas: Additional utility routines for data distribution, input/output and process management purposes shield users to a large extent from having to deal explicitly with the message-passing system - which may be either MPI or PVM - on which the library is based. The PINEAPL Library enables users to take advantage of the increased computing power and memory capacity offered by parallel and distributed computing environments. Targeted primarily at distributed memory computers and networks of workstations, the PINEAPL Library also performs well on shared memory computers whenever efficient implementations of MPI or PVM are available. It offers increased speed of execution over sequential numerical software on these systems and allows problems to be solved which are beyond the memory capacity of single processor systems.

The Library Contents

Sparse Linear Algebra:

The sparse linear algebra section includes iterative solvers for symmetric and unsymmetric linear systems of equations, domain decomposition and SSOR preconditioners, as well as a range of auxiliary subprograms, for instance, a matrix-vector multiplication routine. An important application area of this section is the solution of partial differential equations using finite difference, finite volume or finite element methods. All sparse linear algebra routines can be used with either regular or irregular data distributions, thereby supporting both problems with regular and unstructured grids. Additional graph partitioning software enables users to generate data distributions which are tailored to the structure of the particular problem at hand.

FFTs:

The routines in the Fast Fourier Transform section calculate the Discrete Fourier Transform (DFT) or the inverse DFT of a one-, two- or three-dimensional sequence of complex data values.

Optimization:

The constraint non-linear optimization routines enable users to minimize a given objective function based on either an easy-to-use quasi-Newton method or a sequential quadratic programming algorithm. The independent variables are constrained by simple upper and lower bounds in the quasi-Newton method, whereas a mixture of linear and nonlinear equality or inequality constraints can be imposed in the sequential quadratic programming algorithm.

Support/Utility Facilities:

These utility routines shield users to a large extent from having to deal explicitly with the message-passing system. Routines are provided for process Management routines (under PVM or MPI), Input/Output (for distributed data), data distribution (dense and sparse matrices) and basic sparse matrix operations (eg matrix-vector multiplication, transposed matrix multiplication, etc.)

Contact

Please contact Mishi Derakhshan for details of how to obtain a copy of the library. The use of the library is initially free for a trial period, but is subject to a signed collaboration agreement.

Mishi Derakhshan
NAG Ltd, Wilkinson House, Jordan Hill Rd, OXFORD, OX2 8DR, UK
E-mail: mishi@nag.co.uk, OR na.mderakhshan@na-net.ornl.gov
Tel: +44 (1865) 511 245 Fax: +44 (1865) 310 139