A COMPARISON OF PRECONDITIONING TECHNIQUES FOR PARALLELIZED PCG SOLVERS FOR THE CELL-CENTERED FINITE-DIFFERENCE PROBLEM

Abstract This paper reports on a parallelization of the preconditioned conjugate gradient algorithm for sparse, symmetric matrices. Parallelization is based in domain partitioning into non-overlapping subdomains; the resulting parallelized algorithm is briefly described. Comparisons are made between three block preconditioners commonly used in the parallelization of the preconditoned conjugate gradient methods: Jacobi, incomplete Choleski, and Gauss Seidel. Basic timing and iteration results for these preconditioners are presented; these results tentatively indicate that the simpler block Jacobi algorithm is as efficient as the more complex block incomplete Cholesky and block Gauss Seidel

Policy Environment and Public Service Motivation

This article analyzes whether and to what extent the policy environment of civil servants has an impact on their level of Public Service Motivation (PSM). It hypothesizes that public employees working in different policy domains and stages of the policy cycle are diversely motivated by four PSM orientations (Compassion, Commitment to the public interest, Self-sacrifice and Attraction to politics). The empirical results are based on a survey of 6885 Swiss civil servants. They show that those in charge of Welfare State policies are inclined to have higher levels of 'Compassion', whereas those performing core state functions report lower levels. Furthermore, employees whose main tasks are related to policy formulation display high levels of the 'Attraction to politics' dimension of PSM. This study questions the generalization of previous findings on PSM that are based on heterogeneous survey populations