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[Licence| Download | New Version Template] aehu_v1_0.tar.gz(985 Kbytes)
Manuscript Title: Large-Scale Linear Systems Solver using Secondary Storage: Self-energy in hybrid nanostructures
Authors: J.M. Badia, J.L. Movilla, J.I. Climente, M. Castillo, M. Marqués, R. Mayo, E.S. Quintana-Ortí, J. Planelles
Program title: HDSS - (Huge Dense System Solver)
Catalogue identifier: AEHU_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 182(2011)533
Programming language: Fortran90, C.
Computer: parallel architectures: multiprocessors, computer clusters.
Operating system: Linux/Unix.
Has the code been vectorised or parallelized?: Yes. 4 processors used in the sample tests; tested from 1 to 288 processors.
RAM: 2Gb for the sample tests; tested for up to 80Gb.
Keywords: LU decomposition, Out-of-core, Dielectric confinement, Self-energy.
PACS: 02.60.-x, 73.21.-b, 73.22.-f, 77.22.Ch, 78.67.-n.
Classification: 7.3.

External routines: MPI, BLAS, PLAPACK, POOCLAPACK. PLAPACK and POOCLAPACK are included in the distribution file.

Nature of problem:
Huge scale dense systems of linear equations, Ax = B, beyond standard LAPACK capabilities. Application to calculations of self-energy potential in dielectrically mismatched semiconductor quantum dots.

Solution method:
The linear systems are solved by means of parallelized routines based on the LU factorization, using efficient secondary storage algorithms when the available main memory is insufficient. The self-energy solver relies on an induced charge computation method. The differential equation is discretized to yield linear systems of equations, which we then solve by calling the HDSS library.

Simple precision. For the self-energy solver, axially symmetric systems must be considered.

Running time:
About 32 minutes to solve a system with approximately 100,000 equations and more than 6,000 right-hand side vectors using a four-node commodity cluster with a total of 32 Intel cores.