PUMA publications for /tag/Simulation%20simtech%20SimTechThu Dec 14 16:12:25 CET 2023Enabling FAIR Data in Computational Science, Engineering and Mathematics through Knowledge Graphs2023cmcs hpc mathematik metadata myown ontoloties simtech simulation Mon Jun 27 16:59:03 CEST 2022Proceedings of the 54th International Symposium on Robotics (ISR)17-25Localization and Tracking of Deformable Linear Objects with Self Organizing Maps2022DataCon SimTech Soft-Tissue-Robotics control grk2198 isw myown simulation Fri Nov 20 11:08:22 CET 2020IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Societyoct310-316Nonlinear Trajectory Control for Deformable Linear Objects based on Physics Simulation2020EXC2075 SimTech control grk2198 myown simulation The handling of deformable linear objects (DLOs), such as cables or hoses, with industrial robots is hardly industrially automated due to the underactuated material behavior. Increasing computing power and decreasing cost of processors over the last decades are now allowing the online computation of more complex handling processes. Within this paper, DLOs are approximated as a multibody chain with a finite number of degrees of freedom. Based on that model, a nonlinear, partially IO-linearizing controller is derived to control an underactuated end point on a trajectory when grasped by a robot arm at the other end. The controller is verified in simulation for high dynamics and shown to significantly reduce the tracking error. A practical evaluation finally shows the qualitative suitability of the multibody approximation and is used to validate the functionality of the controller in an open-loop experiment.Mon Mar 19 16:42:05 CET 2018Algorithm-based fault tolerance for matrix operations on graphics processing units: analysis and extension to autonomous operation.2015ABFT GPGPU GPU SimTech algebra algorithm-based error error-detection fault fault-tolerance linear matrix-operations myown simulation Mon Mar 19 16:15:07 CET 2018Proceedings of the 30th IEEE International Conference on Computer Design (ICCD'12)207--212{Acceleration of Monte-Carlo Molecular Simulations on Hybrid Computing Architectures}2012GPGPU GPU Markov-Chain Monte-Carlo SimTech architectures computer heterogeneous hybrid molecular myown parallel simulation thermodynamics Markov-Chain Monte-Carlo (MCMC) methods are an important class of simulation techniques, which execute a sequence of simulation steps, where each new step depends on the previous ones. Due to this fundamental dependency, MCMC methods are inherently hard to parallelize on any architecture. The upcoming generations of hybrid CPU/GPGPU architectures with their multi-core CPUs and tightly coupled many-core GPGPUs provide new acceleration opportunities especially for MCMC methods, if the new degrees of freedom are exploited correctly. In this paper, the outcomes of an interdisciplinary collaboration are presented, which focused on the parallel mapping of a MCMC molecular simulation from thermodynamics to hybrid CPU/GPGPU computing systems. While the mapping is designed for upcoming hybrid architectures, the implementation of this approach on an NVIDIA Tesla system already leads to a substantial speedup of more than 87x despite the additional communication overheads.Mon Mar 19 16:15:07 CET 2018Proceedings of the IEEE International On-Line Testing Symposium (IOLTS'13)240--243{Efficacy and Efficiency of Algorithm-Based Fault Tolerance on GPUs}2013ABFT GPGPU SimTech algorithm-based computing errors fault fault-tolerance myown scientific simulation Computer simulations drive innovations in science and industry, and they are gaining more and more importance. However, their high computational demand generates extraordinary challenges for computing systems. Typical highperformance computing systems, which provide sufficient performance and high reliability, are extremly expensive. Modern GPUs offer high performance at very low costs, and they enable simulation applications on the desktop. However, they are increasingly prone to transient effects and other reliability threats. To fulfill the strict reliability requirements in scientific computing and simulation technology, appropriate fault tolerance measures have to be integrated into simulation applications for GPUs. Algorithm-Based Fault Tolerance on GPUs has the potential to meet these requirements. In this work we investigate the efficiency and the efficacy of ABFT for matrix operations on GPUs. We compare ABFT against fault tolerance schemes that are based on redundant computations and we evaluate its error detection capabilitiesMon Mar 19 16:15:07 CET 2018Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'12)1--6{Parallel Simulation of Apoptotic Receptor-Clustering on GPGPU Many-Core Architectures}2012GPGPU SimTech apoptosis modeling myown numerical parallel particle receptor-clustering simulation Apoptosis, the programmed cell death, is a physiological process that handles the removal of unwanted or damaged cells in living organisms. The process itself is initiated by signaling through tumor necrosis factor (TNF) receptors and ligands, which form clusters on the cell membrane. The exact function of this process is not yet fully understood and currently subject of basic research. Different mathematical models have been developed to describe and simulate the apoptotic receptor-clustering. In this interdisciplinary work, a previously introduced model of the apoptotic receptor-clustering has been extended by a new receptor type to allow a more precise description and simulation of the signaling process. Due to the high computational requirements of the model, an ef?cient algorithmic mapping to a modern many-core GPGPU architecture has been developed. Such architectures enable high-performance computing (HPC) simulation tasks on the desktop at low costs. The developed mapping reduces average simulation times from months to days (peak speedup of 256x), allowing the productive use of the model in research.Mon Mar 19 16:15:07 CET 2018Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'14)424--431{Adaptive Parallel Simulation of a Two-Timescale-Model for Apoptotic Receptor-Clustering on GPUs}2014Euler-Maruyama GPU SimTech adaptive aggregation approximation computing heterogeneous ligand-receptor-model multi-timescale myown parallel particle simulation Computational biology contributes important solutions for major biological challenges. Unfortunately, most applications in computational biology are highly computeintensive and associated with extensive computing times. Biological problems of interest are often not treatable with traditional simulation models on conventional multi-core CPU systems. This interdisciplinary work introduces a new multi-timescale simulation model for apoptotic receptor-clustering and a new parallel evaluation algorithm that exploits the computational performance of heterogeneous CPU-GPU computing systems. For this purpose, the different dynamics involved in receptor-clustering are separated and simulated on two timescales. Additionally, the time step sizes are adaptively refined on each timescale independently. This new approach improves the simulation performance significantly and reduces computing times from months to hours for observation times of several seconds.Fri Mar 24 09:45:38 CET 2017Expo 2015 - A SimTech Success Story2017cable-driven cable-robot cdpr expo2015 isw pn3-7 simtech simulation xtl Fri Mar 24 09:43:49 CET 201711Cable-Driven Parallel Robots: Expo 2015 - Forth and Back Again2016cable-driven cable-robot cdpr isw pn3-7 simtech simulation 25Fri Mar 24 09:42:56 CET 201711SimTech Status Seminar 2016 - Status Update: Improved Modeling of Cables for Kinematics and Dynamics of Light-weight Robots2016cable-driven cable-robot cdpr isw pn3-7 simtech simulation xtl 25Simulation simtech SimTechCommunity for tag(s) Simulation simtech SimTech