A high-performance interactive computing framework for engineering applications

To harness the potential of advanced computing technologies, efficient (real time) analysis of large amounts of data is as essential as are front-line simulations. In order to optimise this process, experts need to be supported by appropriate tools that allow to interactively guide both the computation and data exploration of the underlying simulation code. The main challenge is to seamlessly feed the user requirements back into the simulation. State-of-the-art attempts to achieve this, have resulted in the insertion of so-called check- and break-points at fixed places in the code. Depending on the size of the problem, this can still compromise the benefits of such an attempt, thus, preventing the experience of real interactive computing. To leverage the concept for a broader scope of applications, it is essential that a user receives an immediate response from the simulation to his or her changes. Our generic integration framework, targeted to the needs of the computational engineering domain, supports distributed computations as well as on-the-fly visualisation in order to reduce latency and enable a high degree of interactivity with only minor code modifications. Namely, the regular course of the simulation coupled to our framework is interrupted in small, cyclic intervals followed by a check for updates. When new data is received, the simulation restarts automatically with the updated settings (boundary conditions, simulation parameters, etc.). To obtain rapid, albeit approximate feedback from the simulation in case of perpetual user interaction, a multi-hierarchical approach is advantageous. Within several different engineering test cases, we will demonstrate the flexibility and the effectiveness of our approach.

[1]  Rüdiger Westermann,et al.  Computational Steering for Patient-Specific Implant Planning in Orthopedics , 2008, VCBM.

[2]  Katarzyna Rycerz,et al.  Problem Solving Environment for Distributed Interactive Applications , 2006, CoreGRID Integration Workshop.

[3]  H. Bungartz,et al.  Extending the p -Version of Finite Elements by an Octree-Based Hierarchy , 2007 .

[4]  Kurt Zimmerman,et al.  Visualization in the SCIRun Problem-Solving Environment , 2005, The Visualization Handbook.

[5]  Jarke J. van Wijk,et al.  A survey of computational steering environments , 1999, Future Gener. Comput. Syst..

[6]  Ralf-Peter Mundani,et al.  Interactive Computing in Numerical Modelling of Particle Transport Methods , 2012 .

[7]  Ralf-Peter Mundani,et al.  Interactive Computing Framework for Engineering Applications , 2011 .

[8]  John Brooke,et al.  Computational steering in realitygrid , 2003 .

[9]  Ralf-Peter Mundani,et al.  Schedule Optimisation for Interactive Parallel Structure Simulations , 2012, PARA.

[10]  Ernst Rank,et al.  Collaborative HVAC design using interactive fluid simulations: A geometry-focused collaboration platform , 2005 .

[11]  Jason F. Shepherd,et al.  Hexahedral mesh generation for biomedical models in SCIRun , 2009, Engineering with Computers.

[12]  Philip J Podrid,et al.  Epidemiology and stratification of risk for sudden cardiac death , 2005, Clinical cardiology.

[13]  Mathieu Hursin,et al.  AGENT Code: Open-Architecture Analysis and Configuration of Research Reactors - Neutron Transport Modeling with Numerical Examples , 2004 .

[14]  Jens H. Krüger,et al.  Tuvok, an Architecture for Large Scale Volume Rendering , 2010, VMV.

[15]  Ralf-Peter Mundani Interactive Computing for Engineering Applications , 2010 .

[16]  Jarke J. van Wijk,et al.  Logging in a Computational Steering Environment , 1995, Visualization in Scientific Computing.

[17]  Michelle Miller,et al.  An integrated problem solving environment: the SCIRun computational steering system , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[18]  Jarke J. van Wijk,et al.  CSE: a modular architecture for computational steering , 1996 .

[19]  Tatjana Jevremovic,et al.  Visual Simulation Steering for a 3D Neutron Transport AGENT Code System , 2012 .

[20]  Steven G. Parker,et al.  Uintah: a massively parallel problem solving environment , 2000, Proceedings the Ninth International Symposium on High-Performance Distributed Computing.

[21]  Olivier Coulaud,et al.  Toward a Computational Steering Environment for Legacy Coupled Simulations , 2007, Sixth International Symposium on Parallel and Distributed Computing (ISPDC'07).

[22]  Rüdiger Westermann,et al.  Finite cell method with fast integration - an efficient and accurate analysis method for ct/mri derived models , 2010 .

[23]  Rüdiger Westermann,et al.  Stress Tensor Field Visualization for Implant Planning in Orthopedics , 2009, IEEE Transactions on Visualization and Computer Graphics.

[24]  Karsten Schwan,et al.  High performance computational steering of physical simulations , 1997, Proceedings 11th International Parallel Processing Symposium.

[25]  Ernst Rank,et al.  Interactive Computing in Pre-operative Planning of Joint Replacement , 2011 .

[26]  Ernst Rank,et al.  Interactive Computing−Virtual Planning of Hip Joint Surgeries with Real-Time Structure Simulations , 2011 .

[27]  Christoph van Treeck,et al.  UTILIZING HIGH PERFORMANCE SUPERCOMPUTING FACILITIES FOR INTERACTIVE THERMAL COMFORT ASSESSMENT , 2007 .

[28]  Ernst Rank,et al.  Interactive Indoor Air Flow Analysis using High Performance Computing and Virtual Reality Techniques , 2004 .

[29]  James Arthur Kohl,et al.  Cumulvs: Providing Fault Toler. Ance, Visualization, and Steer Ing of Parallel Applications , 1996, Int. J. High Perform. Comput. Appl..

[30]  Ernst Rank,et al.  The finite cell method for three-dimensional problems of solid mechanics , 2008 .