A parallel nearly implicit time-stepping scheme

Across-the-space parallelism still remains the most mature, convenient and natural way to parallelize large scale problems. One of the major problems here is that implicit time stepping is often difficult to parallelize due to the structure of the system. Approximate implicit schemes have been suggested to circumvent the problem. These schemes have attractive stability properties and they are also very well parallelizable.\ud The purpose of this article is to give an overall assessment of the parallelism of the method

Solution of the Dirac equation in lattice QCD using a domain decomposition method

Efficient algorithms for the solution of partial differential equations on parallel computers are often based on domain decomposition methods. Schwarz preconditioners combined with standard Krylov space solvers are widely used in this context, and such a combination is shown here to perform very well in the case of the Wilson--Dirac equation in lattice QCD. In particular, with respect to even-odd preconditioned solvers, the communication overhead is significantly reduced, which allows the computational work to be distributed over a large number of processors with only small parallelization losses.Comment: Plain TeX source, 21 pages, figures include

Effective use of product quality information in meat processing

This paper presents a case study on use of advanced product quality information in meat processing. To serve segmented customer demand meat processors consider use of innovative sensor technology to sort meat products to customer orders. To assess the use of this sensor technology a discrete-event simulation model is built. Various scenarios were defined for processing strategy (buffered or non-buffered), the number of end product groups to sort to and the availability of product quality information. The performance of these scenarios is measured w.r.t. order compliance, labor consumption and throughput-time. Our results reveal that the current processing and product sorting strategy is in-effective for sorting to a large number of end product groups. Furthermore, the current availability of product quality information is insufficient to ensure high levels of order compliance for advanced product quality products

Variatie in kiemgetal van boerderijmelk

Om meer zicht te krijgen op de gemiddelde variatie van het kiemgetal van de Nederlandse melk zijn de gegevens voor 1999 op een rij gezet. Dit is gedaan middels beschrijvende statistieken

'Uw lijden is mijn' pijne': Huygens in dialoog met Seneca

The long consolatory poem for the blind, Ooghentroost, written by the Dutch seventeenth-century poet, Constantijn Huygens, looks like an intricate web of dialogues. The text is first of all a letter from Huygens to Lucretia van Trello, an older friend of the author who suffered from cataract. One can regard this poem also as a collection of links between the lines in Dutch and the margin of the poem, a subtext of references to the oeuvres of diverse authorities such as playwrights (Euripides, Seneca, ...), philosophers (Plato, Cicero, ...), poets (Homer, Ovid, ...), Church Fathers and the Bible. In this paper I examine one specific dialogue – a conversation between Huygens and Lucius Annaeus Seneca. Huygens frequently refers to Seneca’s philosophical and literary work but his entretien with the Roman writer is not in the least unproblematic. To fit Seneca’s stoic ideas into his own Christian discourse on those who are morally blind the poet cannot but manipulate the words of his illustrious interlocutor

Computational science curriculum in Utrecht

In 1993 Utrecht University has started a curriculum in Computational Science, starting at the undergraduate level and leading to the Dutch `Doctorandus' degree (wich is more or less comparable to the Master's degree). The curriculum has been st up as a joint collaboration between the Departments of Mathematics & Computer Science, and Physics. It aims at a complete and self-contained educational program that should fulll society's growing demand for scientic computing, and it does so by trying to make students familiar with computational models (physics), applied mathematics (with emphasis on numerical analysis), and computer possibilities (computer science). In our presentation we will discuss the ideas behind this new study, the perspectives for students with respect to carreer, and we will report on our experiences during the rst two years of existence of the new curriculum

Parallel Iterative Solution Methods for Linear Systems arising from Discretized PDE's

In these notes we will present an overview of a number of related iterative methods for the solution of linear systems of equations. These methods are so-called Krylov projection type methods and the include popular methods as Conjugate Gradients, Bi-Conjugate Gradients, CGST Bi-CGSTAB, QMR, LSQR and GMRES. We will show how these methods can be derived from simple basic iteration formulas. We will not give convergence proofs, but we will refer for these, as far as available, to litterature. Iterative methods are often used in combination with so-called preconditioning operators (approximations for the inverses of the operator of the system to be solved). Since these preconditions are not essential in the derivation of the iterative methods, we will not give much attention to them in these notes. However, in most of the actual iteration schemes, we have included them in order to facilitate the use of these schemes in actual computations. For the application of the iterative schemes one usually thinks of linear sparse systems, e.g., like those arising in the finite element or finite difference approximatious of (systems of) partial differential equations. However, the structure of the operators plays no explicit role in any of these schemes, and these schemes might also successfully be used to solve certain large dense linear systems. Depending on the situation that might be attractive in terms of numbers of floating point operations. It will turn out that all of the iterative are parallelizable in a straight forward manner. However, especially for computers with a memory hierarchy (i.e. like cache or vector registers), and for distributed memory computers, the performance can often be improved significantly through rescheduling of the operations. We will discuss parallel implementations, and occasionally we will report on experimental findings