Efficient integration of software components for scientific simulations

Abstract unavailable please refer to PD

HepSim: a repository with predictions for high-energy physics experiments

A file repository for calculations of cross sections and kinematic distributions using Monte Carlo generators for high-energy collisions is discussed. The repository is used to facilitate effective preservation and archiving of data from theoretical calculations, as well as for comparisons with experimental data. The HepSim data library is publicly accessible and includes a number of Monte Carlo event samples with Standard Model predictions for current and future experiments. The HepSim project includes a software package to automate the process of downloading and viewing online Monte Carlo event samples. A data streaming over a network for end-user analysis is discussed.Comment: 12 pages, 2 figure

MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007

SysML Output Interface and System-Level Requirement Analyzer for the Horizon Simulation Framework

Model-Based Systems Engineering in industry has been constantly increasing its presence within the aerospace industry. SysML is one such MBSE tool that shows complex system organization and relationships. The Horizon Simulation Framework is another MBSE tool, created by Cal Poly students, that gives users the ability to run “day-in-the-life” simulations of systems. Finding a way to link these two tools could allow systems engineers to reap the benefits of both. This thesis investigates the background and design process involved with developing the code that can convert an output file generated in SysML, into a format specifically made for the Horizon Simulation Framework. The goal was to create an interface that can allow users to model a system in SysML, and analyze the model and verify system requirements using HSF. Another goal was to expand the capabilities of the Horizon Simulation Framework by designing and develop a module that would allow users to define and analyze system-level requirements. To evaluate the effectiveness of both codes, the Aeolus example case was used. A SysML model of the system was created as the product of another thesis; SysML based CubeSat Model Design and Integration with the Horizon Simulation Framework. The Aeolus SysML model was converted and used as input in an HSF simulation. The SysML model simulation data was compared against those of the original test case. To test the requirement module, system level requirements were formulated within the Aeolus system and run in simulation, providing an analysis of the results. The results of the analysis confirmed a successful conversion of the SysML model into an equivalent HSF model and a successful analysis of system-level requirements

A Development Environment for Visual Physics Analysis

The Visual Physics Analysis (VISPA) project integrates different aspects of physics analyses into a graphical development environment. It addresses the typical development cycle of (re-)designing, executing and verifying an analysis. The project provides an extendable plug-in mechanism and includes plug-ins for designing the analysis flow, for running the analysis on batch systems, and for browsing the data content. The corresponding plug-ins are based on an object-oriented toolkit for modular data analysis. We introduce the main concepts of the project, describe the technical realization and demonstrate the functionality in example applications