MICSIM : Concept, Developments and Applications of a PC-Microsimulation Model for Research and Teaching

It is the growing societal interest about the individual and its behaviour in our and 'modern' societies which is asking for microanalyses about the individual situation. In order to allow these microanalyses on a quantitative and empirically based level microsimulation models were developed and increasingly used for economic and social policy impact analyses. Though microsimulation is known and applied (mainly by experts), an easy to use and powerful PC microsimulation model is hard to find. The overall aim of this study and of MICSIM - A PC Microsimulation Model is to describe and offer such a user-friendly and powerful general microsimulation model for (almost) any PC, to support the impact microanalyses both in applied research and teaching. Above all, MICSIM is a general microdata handler for a wide range of typical microanalysis requirements. This paper presents the concept, developments and applications of MICSIM. After some brief remarks on microsimulation characteristics in general, the concept and substantive domains of MICSIM: the simulation, the adjustment and aging, and the evaluation of microdata, are described by its mode of operation in principle. The realisations and developments of MICSIM then are portrayed by the different versions of the computer program. Some MICSIM applications and experiences in research and teaching are following with concluding remarks.Economic and Social Policy Analyses, Microsimulation (dynamic and static), Simulation, Adjustment and Evaluation of Microdata, PC Computer Program for Microanalyses in General

Models in the Cloud: Exploring Next Generation Environmental Software Systems

There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science

Julia: A Fresh Approach to Numerical Computing

Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast. Julia questions notions generally held as "laws of nature" by practitioners of numerical computing: 1. High-level dynamic programs have to be slow. 2. One must prototype in one language and then rewrite in another language for speed or deployment, and 3. There are parts of a system for the programmer, and other parts best left untouched as they are built by the experts. We introduce the Julia programming language and its design --- a dance between specialization and abstraction. Specialization allows for custom treatment. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Abstraction, what good computation is really about, recognizes what remains the same after differences are stripped away. Abstractions in mathematics are captured as code through another technique from computer science, generic programming. Julia shows that one can have machine performance without sacrificing human convenience.Comment: 37 page

Software development tools: A bibliography, appendix C.

A bibliography containing approximately 200 citations on tools which help software developers perform some development task (such as text manipulation, testing, etc.), and which would not necessarily be found as part of a computing facility is given. The bibliography comes from a relatively random sampling of the literature and is not complete. But it is indicative of the nature and range of tools currently being prepared or currently available

A software system for laboratory experiments in image processing

Laboratory experiments for image processing courses are usually software implementations of processing algorithms, but students of image processing come from diverse backgrounds with widely differing software experience. To avoid learning overhead, the software system should be easy to learn and use, even for those with no exposure to mathematical programming languages or object-oriented programming. The class library for image processing (CLIP) supports users with knowledge of C, by providing three C++ types with small public interfaces, including natural and efficient operator overloading. CLIP programs are compact and fast. Experience in using the system in undergraduate and graduate teaching indicates that it supports subject matter learning with little distraction from language/system learning

The GeoClaw software for depth-averaged flows with adaptive refinement

Many geophysical flow or wave propagation problems can be modeled with two-dimensional depth-averaged equations, of which the shallow water equations are the simplest example. We describe the GeoClaw software that has been designed to solve problems of this nature, consisting of open source Fortran programs together with Python tools for the user interface and flow visualization. This software uses high-resolution shock-capturing finite volume methods on logically rectangular grids, including latitude--longitude grids on the sphere. Dry states are handled automatically to model inundation. The code incorporates adaptive mesh refinement to allow the efficient solution of large-scale geophysical problems. Examples are given illustrating its use for modeling tsunamis, dam break problems, and storm surge. Documentation and download information is available at www.clawpack.org/geoclawComment: 18 pages, 11 figures, Animations and source code for some examples at http://www.clawpack.org/links/awr10 Significantly modified from original posting to incorporate suggestions of referee

Towards quantum-chemical method development for arbitrary basis functions

We present the design of a flexible quantum-chemical method development framework, which supports employing any type of basis function. This design has been implemented in the light-weight program package molsturm, yielding a basis-function-independent self-consistent field scheme. Versatile interfaces, making use of open standards like python, mediate the integration of molsturm with existing third-party packages. In this way both rapid extension of the present set of methods for electronic structure calculations as well as adding new basis function types can be readily achieved. This makes molsturm well-suitable for testing novel approaches for discretising the electronic wave function and allows comparing them to existing methods using the same software stack. This is illustrated by two examples, an implementation of coupled-cluster doubles as well as a gradient-free geometry optimisation, where in both cases, an arbitrary basis functions could be used. molsturm is open-source and can be obtained from https://molsturm.org.Comment: 15 pages and 7 figure