Advanced simulations within biophysical applications ask for advanced algorithms and implementations which are running efficiently on massively parallel high performance computers. The software framework UG fulfills these preconditions. Therefore, we present insight into the experimental basics, the modelling and simulation details, and the biophysical meaning of the estimation of the diffusion constant of a major player in the replication of the genetic information of the Hepatitis C virus (HCV), namely the NS5A viral protein. NS5A movement is restricted to the surface of the Endoplasmatic Reticulum (ER, a medusa-hair like important cell compartment). Hence, the dynamics of NS5A are described by surface PDEs (sPDE) which mimic experimental FRAP (fluorescence recovery after photobleaching) time series data. The sPDE computations were performed with UG upon large unstructured grids representing realistic reconstructed ER surfaces. We explain the context of the parameter estimations which asked for a substantial amount of single sPDE evaluations which we performed on the HLRS Stuttgart Hermit and Hornet supercomputers for various experimental data sets and for various geometric setups. This enabled us to derive valid final values for the diffusion constant of NS5A on the ER surface. The estimated diffusion constant values are intended to enter spatio-temporal resolved models of HCV replication dynamics at a cellular level.

Viruses are a major challenge to human health and prosperity. This holds true for various viruses which are either threatening Europe (like Dengue and Yellow fever) or which are currently causing big health problems like the hepatitis C virus (HCV). HCV causes chronic liver diseases like cirrhosis and cancer and is the main reason for liver transplantations. Exploring biophysical properties of virus-encoded components and viral life cycle is an exciting new area of current virological research. In this context, spatial resolution is an aspect that has not yet been received much attention despite strong biological evidence suggesting that intracellular spatial dependence is a crucial factor in the viral replication process. We are developing first spatio-temporal resolved models which mimic the behavior of the important components of virus replication within single liver cells. HCV replication is strongly associated to the intracellular Endoplasmatic Reticulum (ER) network. Here, we present the computational basis for the estimation of the diffusion constant of a central component of HCV genome (viral RNA) replication, namely the NS5a protein, on the surface of realistic reconstructed ER geometries. The basic surface partial differential equation (sPDE) evaluations are performed with UG4 using fast massively parallel multigrid solvers. The numerics of the simulations are studied in detail. Integrated concentrations within special subdomains correspond to experimental FRAP time series. In particular, we analyze the refinement stability in time and space for these integrated concentrations based on diffusion sPDEs upon large unstructured surface grids using heuristic values for the NS5a diffusion constant. This builds up a solid basis for future research not included in this presentation. e.g. the presented refinement stability analysis of the single sPDEs allows for parameter estimations for the NS5a diffusion constant. Our advanced Finite Volume/multigrid techniques also could be applied for studying life cycles of other viruses.

In order to enable exascale computing, concepts for substantial energy savings are required. Dynamic voltage and frequency scaling (DVFS) is widely known to provide suitable energy saving potentials. However, the customarily utilized DVFS mechanism of the Linux kernel determines clock frequencies solely based on an idle time analysis. In contrast to this, we use an empirical approach based on preparatory measurements of the energy consumption at all available frequencies. From the resulting data we deduce energy-optimal frequencies, which are used in subsequent production runs. The described methodology can be deployed with routine granularity to account for varying code characteristics. For evaluation purposes, the approach is applied to the UG4 numerical simulation software. First results exhibit an average energy saving potential of approximately 10 % while increasing the runtime by about 19 %.

This research studies what influences various properties of a soundboard may have upon the acoustic feedback to gain a better understanding about the relevance of different properties regarding the sound characteristics. It may also help to improve the quality of simulations. We did a modal analysis of a real soundboard of a harpsichord using a Laser-Doppler-Vibrometer and also simulated several models of the very same soundboard in three space dimensions using the simulation software UG4. The used models of the sound board differed from each other by changing or skipping several properties and components. Then, we compared the simulated vibration patterns with the patterns measured on the real sound board to gain a better understanding about their influences on the vibrations. In particular, we used models with and without soundboard bars and bridge, but also were using different thicknesses for the soundboard itself.

In this paper we describe the concept of the renewed software package UG, that is used as a flexible simulation framework for the solution of partial differential equations. A general overview of the concepts of the new implementation is given: The modularization of the software package into several libraries libGrid, libAlgebra, libDiscretization and pcl is described and all major modules are discussed in detail. User backends through scripting and visual editing are briefly considered and examples show the new features of the current implementation.

Infection with hepatitis C virus (HCV) causes chronic liver diseases. HCV-related liver damage is the main reason for liver transplantations in the western world. Spatial resolution is an aspect that has not yet been appreciated in current modeling simulations despite strong biological evidence that suggests intracellular spatial dependence is a crucial factor in the process the virus uses to replicate its RNA genome. HCV replication is believed to occur in specialized compartments within virus-infected cells, termed replication complexes, which are derived from altered regions (called the membranous web) of the endoplasmic reticulum (ER the ER is a central structure of each cell). Trafficking of both replication complexes, and their components, is likely a dynamic process occurring in three dimensions that is both difficult to capture experimentally and conceptually visualize. Therefore, we are developing a spatially-resolved biophysical model of HCV replication dynamics in single liver cells. We used data derived from 3D confocal microscopy of HCVinfected human hepatoma cells labeled for the ER membrane in order to reconstruct 3D geometries of single hepatocytes using NeuRA2. On top of these geometries, we developed a model using (surface) partial differential equation of viral RNA replication dynamics with particular emphasis upon RNA movement, viral protein production, cleavage and movement, and viral RNA replication within the membranous web. The arising (s)pde s on the ER surface are solved using the simulation platform UG4 within a Finite Volume framework combined with multigrid techniques. Our approach is based on two columns which are intended to grow together in the middle run: On the one hand side, we are doing parameter estimations of single components of viral replication based on the Gauss-Newton algorithm in order for extracting e.g. the diffusion constant of basic viral proteins on the surface of the ER using experimental FRAP time series. On the other hand side, we are developing the model which mimics the interplay of all important component of virus replication, e.g. viral RNA and various states of viral proteins. The estimated parameters are entering the model step by step. Therefore, the presented work is a practical application of the powerful tool UG4 and its multigrid techiques for the case of a huge number of DoFs (about 10) already at base level and demonstrates the excellent usability (and scalability) of UG4 in the context of modern biophysical research.

The modeling of physical phenomena in a variety of fields of scientific interest lead to a formulation in terms of partial differential equations. Especially when complex geometries as the domain of definition are involved, a direct and exact solution is not accessible, but numerical schemes are used to compute an approximate discrete solution. In this report, we focus on elliptic and parabolic types of equations that include spatial operators of second order. When discretizing such problems using commonly known discretization schemes such as finite element methods or finite volume methods, large systems of linear equations arise naturally. Their solution takes the largest amount of the overall computing time.