TY - GEN

T1 - Scheduling parallel eigenvalue computations in a quantum chemistry code

AU - Roderus, Martin

AU - Berariu, Anca

AU - Bungartz, Hans Joachim

AU - Krüger, Sven

AU - Matveev, Alexei

AU - Rösch, Notker

N1 - Funding Information:
The work was funded by the Munich Centre of Advanced Computing (MAC) and Fonds der Chemischen Industrie.

PY - 2010

Y1 - 2010

N2 - The application of High Performance Computing to Quantum Chemical (QC) calculations faces many challenges. A central step is the solution of the generalized eigenvalue problem of a Hamilton matrix. Although in many cases its execution time is small relative to other numerical tasks, its complexity of Script O sign(N3) is higher, thus more significant in larger applications. For parallel QC codes, it therefore is advantageous to have a scalable solver for this step. We investigate the case where the symmetry of a molecule leads to a block-diagonal matrix structure, which complicates an efficient use of available parallel eigensolvers. We present a technique which employs a malleable parallel task scheduling (MPTS) algorithm to schedule instances of sequential and parallel eigensolver routines from LAPACK and ScaLAPACK. In this way, an efficient use of hardware resources is guaranteed while overall scalability is facilitated. Finally, we evaluate the proposed technique for electronic structure calculations of real chemical systems. For the systems considered, the performance was improved by factors of up to 8.4, compared to the previously used, non-malleable parallel scheduling approach.

AB - The application of High Performance Computing to Quantum Chemical (QC) calculations faces many challenges. A central step is the solution of the generalized eigenvalue problem of a Hamilton matrix. Although in many cases its execution time is small relative to other numerical tasks, its complexity of Script O sign(N3) is higher, thus more significant in larger applications. For parallel QC codes, it therefore is advantageous to have a scalable solver for this step. We investigate the case where the symmetry of a molecule leads to a block-diagonal matrix structure, which complicates an efficient use of available parallel eigensolvers. We present a technique which employs a malleable parallel task scheduling (MPTS) algorithm to schedule instances of sequential and parallel eigensolver routines from LAPACK and ScaLAPACK. In this way, an efficient use of hardware resources is guaranteed while overall scalability is facilitated. Finally, we evaluate the proposed technique for electronic structure calculations of real chemical systems. For the systems considered, the performance was improved by factors of up to 8.4, compared to the previously used, non-malleable parallel scheduling approach.

UR - http://www.scopus.com/inward/record.url?scp=78249268237&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-15291-7_12

DO - 10.1007/978-3-642-15291-7_12

M3 - Conference contribution

AN - SCOPUS:78249268237

SN - 3642152902

SN - 9783642152900

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 113

EP - 124

BT - Euro-Par 2010 Parallel Processing - 16th International Euro-Par Conference, Proceedings

T2 - 16th International Euro-Par Conference on Parallel Processing, Euro-Par 2010

Y2 - 31 August 2010 through 3 September 2010

ER -