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CRTC Seminars


 CRTC Seminar Series on Mesh Generation

When: Nov. 12, 2015, 10:30AM

Where:  E & CS Auditorium, First Floor


What:  New Approaches to Energy-Efficient and Resilient HPC 


Who:  Professor Dimitrios S. Nikolopoulos 


School of Electronics, Electrical Engineering and Computer Science  


Queen's University of Belfast, UK 


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This talk explore new and unconventional directions towards improving the energy-efficiency of HPC systems. Taking a workload-driven approach, we explore micro-servers with programmable accelerators; non-volatile main memory; workload auto-scaling and structured approximate computing. Our research in these has achieved significant gains in energy-efficiency while meeting application-specific QoS targets. The talk also reflects on a number of UK and European efforts to create a new energy-efficient and disaggregated ICT ecosystem for data analytics.

Bio: Dimitrios S. Nikolopoulos is Professor in the School of EEECS, at Queen's University of Belfast and a Royal Society Wolfson Research Fellow. He holds the Chair in High Performance and Distributed Computing and directs the HPDC Research Cluster, a team of 20 academic and research staff. His research explores scalable computing systems for data-driven applications and new computing paradigms at the limits of performance, power and reliability. Dimitrios received the NSF CAREER Award, the DOE CAREER Award, and the IBM Faculty Award during an eight-year tenure in the United States. He has also been awarded the SFI-DEL Investigator Award, a Marie Curie Fellowship, a HiPEAC Fellowship, and seven Best Paper Awards including some from the leading IEEE and ACM conferences in HPC, such as SC, PPoPP, and IPDPS. His research has produced over 150 top-tier outputs and has received extensive (£10.6m as PI/£39.5m as CoI) and highly competitive research funding from the NSF, DOE, EPSRC, SFI, DEL, Royal Academy of Engineering, Royal Society, European Commission and private sector. Dimitrios is a Fellow of the British Computer Society, Senior Member of the IEEE and Senior Member of the ACM. He earned a PhD (2000) in Computer Engineering and Informatics from the University of Patras.



 CRTC Seminar Series on Mesh Generation


When: Nov. 6, 2015, 10:30AM

Where:  E & CS Auditorium, First Floor


What:  Flow Diverters to Cure Cerebral Aneurysms a Case Study - From Concept to Clinical Implementation


Who:  Professor  Lieber, Baruch Barry


Department of Neurosurgery  

Stony Brook University


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Ten to fifteen million Americans are estimated to harbor intracranial aneurysms (abnormal bulges of blood vessels located in the brain) that can rupture and expel blood directly into the brain space outside of the arteries causing a stroke. A flow diverter, a refined tubular mesh-like device that is inserted through a small incision in the groin area (no need for open brain surgery) and navigated through a catheter into cerebral arteries to treat brain aneurysms is delivered into the artery carrying the aneurysm. The permeability of the device is optimized such that it significantly reduces the blood flow in the aneurysm, while keeping small side branches of the artery open to supply critical brain tissue. The biocompatible device elicits a healthy scar-response from the body that lines the inner metal surface of the device with biological tissue, thus restoring the diseased arterial segment to its normal state. Refinement in the design of such devices and prediction of their long term creative effect, which usually occurs over a period of months can be significantly helped by computer modeling and simulations of the flow alteration such devices impart to the aneurysm. The evolution of these devices will be discussed from conception to their current clinical use.

Bio:  Barry Lieber attended Tel-Aviv University and received a B.Sc. in Mechanical Engineering in 1979. He then attended Georgia Tech and received M.Sc. in 1982 and a Ph.D. in 1985, both in Aerospace Engineering Ph.D. working with Dr. Don P. Giddens. Barry Lieber was a Postdoctoral Fellow from 1985-1987 at the Department of Mechanical Engineering at Georgia Tech and also completed a summer fellowship at Imperial College London in 1986. In 1987 Barry Lieber joined the faculty of the Department of Mechanical and Aerospace Engineering at the State University of New York at Buffalo as Assistant Professor. In 1993 he was promoted to the rank of Associate Professor with tenure and in 1998 was promoted to full professor. In 1994 he became Research Professor of Neurosurgery and in 1997 he became the Director of the Center for Bioengineering at the State University of New York at Buffalo, both position he held until his departure from the university in 2001 to Join the University of Miami as professor in the Department of Biomedical Engineering with a joined appointment in the Department of Radiology. In 2010 he joined the State University of New York at Stony Brook at the rank of professor in the department of Neurosurgery and also serves as program faculty in the department of Biomedical Engineering. Barry Lieber was elected as fellow of the American Institute for Medical and Biomedical Engineering in 1999. He was elected as fellow of the American Society of mechanical Engineers in 2005 and served as the Chairman of the Division of Bioengineering of the American Society of Mechanical Engineers in 2009.



 CRTC Seminar Series on Mesh Generation


When: July 31, 2015, 10:30AM

Where:  E & CS Auditorium, First Floor


What:  Enhanced Surface Definition in Moving-Boundary Flow Simulation


Who:  Professor  Marek Behr


Chair for Computational Analysis of Technical 

RWTH Aachen University

Systems, Schinkelstr. 2, 52062 Aachen, Germany


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Moving-boundary flow simulations are an important design and analysis tool in many areas of engineering, including civil and biomedical engineering, as well as production engineering [1]. While interface-capturing offers unmatched flexibility for complex free-surface motion, the interface-tracking approach is very attractive due to its better mass conservation properties at low resolution. We focus on interface-tracking moving-boundary flow simulations based on stabilized discretizations of Navier-Stokes equations, space-time formulations on moving grids, and mesh update mechanisms based on elasticity. However, we also develop techniques that promise to increase the fidelity of the interface-capturing methods.

In order to obtain accurate and smooth shape description of the free surface, as well as accurate flow approximation on coarse meshes, the approach of NURBS-enhanced finite elements (NEFEM) [2] is being applied to various aspects of free-surface flow computations. In NEFEM, certain parts of the boundary of the computational domain are represented using non-uniform rational B-splines (NURBS), therefore making it an effective technique to accurately treat curved boundaries, not only in terms of geometry representation, but also in terms of solution accuracy.

As a step in the direction of NEFEM, the benefits of a purely geometrical NURBS representation of the free-surface could already be shown [3]. The first results with a full NEFEM approach for the flow variables in the vicinity of the moving free surface have also been obtained. The applications include both production engineering, i.e., die swell in plastics processing simulation, and safety engineering, i.e., sloshing phenomena in fluid tanks subjected to external excitation.

Space-time approaches offer some not-yet-fully-exploited advantages when compared to standard discretizations (finite-difference in time and finite-element in space, using either method of Rothe or method of lines); among them, the potential to allow some degree of unstructured space-time meshing. A method for generating simplex space-time meshes is presented, allowing arbitrary temporal refinement in selected portions of space-time slabs. The method increases the flexibility of space-time discretizations, even in the absence of dedicated space-time mesh generation tools. The resulting tetrahedral (for 2D problems) and pentatope (for 3D problems) meshes are tested in the context of advection-diffusion equation, and are shown to provide reasonable solutions, while enabling varying time refinement in portions of the domain [4].

[1] S. Elgeti, M. Probst, C. Windeck, M. Behr, W. Michaeli, and C. Hopmann, "Numerical shape optimization as an approach to extrusion die design", Finite Elements in Analysis and Design, 61, 35–43 (2012).

[2] R. Sevilla, S. Fernandez-Mendez and A. Huerta, "NURBS-Enhanced Finite Element Method (NEFEM)", International Journal for Numerical Methods in Engineering, 76, 56–83 (2008).

[3] S. Elgeti, H. Sauerland, L. Pauli, and M. Behr, "On the Usage of NURBS as Interface Representation in Free-Surface Flows", International Journal for Numerical Methods in Fluids, 69, 73–87 (2012).

[4] M. Behr, "Simplex Space-Time Meshes in Finite Element Simulations", International Journal for Numerical Methods in Fluids, 57, 1421–1434, (2008).

Bio: Prof. Marek Behr obtained his Bachelor's and Ph.D. degrees in Aerospace Engineering and Mechanics form the University of Minnesota in Minneapolis. After faculty appointments at the University of Minnesota and at Rice University in Houston, he was appointed in 2004 as a Professor of Mechanical Engineering and holder of the Chair for Computational Analysis of Technical Systems at the RWTH Aachen University. Since 2006, he is the Scientific Director of the Aachen Institute for Advanced Study in Computational Engineering Science, focusing on inverse problems in engineering and funded in the framework of the Excellence Initiative in Germany. Behr advises or has advised over 40 doctoral students, and has published over 65 refereed journal articles and a similar number of conference publications and book chapters. Behr is one of the main developers of the stabilized space-time finite element formulation for deforming-domain flow problems, which has been recently extended to unstructured space-time meshes. He is a long-time expert on parallel computation and large-scale flow simulations and on numerical methods for non-Newtonian fluids. He is a member of several advisory and editorial boards of international journals, and the member of the executive council of the German Association for Computational Mechanics and of the general council of the International Association for Computational Mechanics.



 CRTC Seminar Series on Mesh Generation


When: June 25, 2015, 10:30AM

Where:  E & CS Auditorium, First Floor


What:  Disrupting the power/performance/quality tradeoff through approximate and error-tolerant computing

Who: Professor  Christos Antonopoulos


Department of Electrical and Computer Engineering, 

University of Thessaly, Greece


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A major obstacle in the path towards exascale computing is the necessity to improve the energy efficiency of systems by two orders of magnitude. Embedded computing also faces similar challenges, in an era when traditional techniques, such as DVFS and Vdd scaling, yield very limited additional returns.  Heterogeneous platforms are popular due to their power efficiency. They usually consist of a host processor and a number of accelerators (typically GPUs). They may also integrate multiple cores or processors with inherently different characteristics, or even just configured differently. Additional energy gains can be achieved for certain classes of applications by approximating computations, or in a more aggressive setting even tolerating errors. These opportunities, however, have to be exploited in a careful, educated manner, otherwise they may introduce significant development overhead and may also result to catastrophic failures or uncontrolled degradation of the quality of results. Introducing and tolerating approximations and errors in a disciplined and effective way requires rethinking, redesigning and re-engineering all layers of the system stack, from programming models down to hardware.  We will present our experiences from this endeavor in the context of two research projects: Centaurus (co-funded by GR an EU) and SCoRPiO (EU FET-Open). We will also discuss our perspective on the main obstacles preventing the wider adoption of approximate and error-aware computing and the necessary steps to be taken to that end.

Bio: Christos D. Antonopoulos, is Assistant Professor at the Department of Electrical and Computer Engineering of the University of Thessaly in Volos, Greece. He earned his PhD (2004), MSc (2001) and Diploma (1998) from the Department of Computer Engineering and Informatics of the University of Patras, Greece. His research interests span the areas of system and applications software for high performance computing, emphasizing on monitoring and adaptivity with performance and power/performance/quality criteria. He is the author of more than 50 refereed technical papers, and has been awarded two best-paper awards. He has been actively involved in several research projects both in the EU and in USA.




 CRTC Seminar Series on Mesh Generation


When: April 24, 2015, 10:30AM


Where:  E & CS Auditorium, First Floor


What: Image-Based Mesh Generation and Volumetric Spline Modeling for Isogeometric Analysis


Who: Professor Yongjie Jessica Zhang


Associate Professor in Mechanical Engineering & Courtesy Appointment in Biomedical Engineering

Carnegie Mellon University


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With finite element methods and scanning technologies seeing increased use in many research areas, there is an emerging need for high-fidelity geometric modeling and mesh generation of spatially realistic domains.  In this talk, I will highlight our research in three areas: image-based mesh generation for complicated domains, trivariate spline modeling for isogeometric analysis, as well as biomedical, material sciences and engineering applications. I will first present advances and challenges in image-based geometric modeling and meshing along with a comprehensive computational framework, which integrates image processing, geometric modeling, mesh generation and quality improvement with multi-scale analysis at molecular, cellular, tissue and organ scales. Different from other existing methods, the presented framework supports five unique features: high-fidelity meshing for heterogeneous domains with topology ambiguity resolved; multiscale geometric modeling for biomolecular complexes; automatic all-hexahedral mesh generation with sharp feature preservation; robust quality improvement for non-manifold meshes; and guaranteed-quality meshing. These unique capabilities enable accurate, stable, and efficient mechanics calculation for many biomedicine, materials science and engineering applications.

In the second part of this talk, I will show our latest research on volumetric spline parameterization, which contributes directly to the integration of design and analysis, the root idea of isogeometric analysis. For arbitrary topology objects, we first build a polycube whose topology is equivalent to the input geometry and it serves as the parametric domain for the following trivariate T-spline construction. Boolean operations and geometry skeleton can also be used to preserve surface features. A parametric mapping is then used to build a one-to-one correspondence between the input geometry and the polycube boundary. After that, we choose the deformed octree subdivision of the polycube as the initial T-mesh, and make it valid through pillowing, quality improvement, and applying templates or truncation mechanism couple with subdivision to handle extraordinary nodes. The parametric mapping method has been further extended to conformal solid T-spline construction with the input surface parameterization preserved and trimming curves handled.

Bio:Yongjie Jessica Zhang is an Associate Professor in Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Biomedical Engineering. She received her B.Eng. in Automotive Engineering, and M.Eng. in Engineering Mechanics, all from Tsinghua University, China, and M.Eng. in Aerospace Engineering and Engineering Mechanics, and Ph.D. in Computational Engineering and Sciences from the University of Texas at Austin. Her research interests include computational geometry, mesh generation, computer graphics, visualization, finite element method, isogeometric analysis and their application in computational biomedicine, material sciences and engineering. She has co-authored over 100 publications in peer-reviewed journals and conference proceedings. She is the recipient of Presidential Early Career Award for Scientists and Engineers, NSF CAREER Award, Office of Naval Research Young Investigator Award, USACM Gallagher Young Investigator Award, Clarence H. Adamson Career Faculty Fellow in Mechanical Engineering, George Tallman Ladd Research Award, and Donald L. & Rhonda Struminger Faculty Fellow.




 CRTC Seminar Series on Mesh Generation

When: March 20, 2015, 10:30AM

Where:  E & CS Auditorium, First Floor


What: AFLR Unstructured Meshing  Research Activities at CFD Modeling and Simulation Research at the Center for Advanced Vehicular Systems

Who: Professor David Marcum , Billie J. Ball Professor and  Chief Scientist

Center for Advanced Vehicular Systems, Mechanical Engineering Department, Mississippi State University

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Visitor marcum




Mesh generation and associated geometry preparation are critical aspects of any computational field simulation (CFS) process. In particular the mesh used can have a significant impact on accuracy, effectiveness, and efficiency of the CFS solver. Further, typical users spend a considerable portion of their time for the overall effort on mesh and geometry issues. All of this is particularly critical for CFD applications.  AFLR is an unstructured mesh generator designed with a focus on addressing these issues for complex geometries. It is widely used, readily available to Government and Academic users, and has been very successful with relevant problems. AFLR volume and surface meshing is also directly incorporated in several systems, including: DoD CREATE-MG Capstone, Lockheed Martin/DoD ACAD, Boeing MADCAP, MSU SolidMesh, and Altair HyperMesh. In this talk we will provide an overview of this technology, future directions, and plans for multi-tasking/parallel operation.

Bio: Dr. Marcum is Professor of Mechanical Engineering at Mississippi State University (MSU) and Chief Scientist for CFD within the Center for Advanced Vehicular Systems (CAVS). He has 30 years of experience in development of CFD and unstructured grid technology. Before joining MSU in 1991, Dr. Marcum was a Scientist and Senior Engineer at McDonnell Douglas Research Laboratories and Boeing Commercial Airplane Company. He received his Ph.D. from Purdue University in 1985. Prior to that he was a Senior Engineer from 1978 through 1983 at TRW Ross Gear Division. At MSU, Dr. Marcum served as Thrust Leader and Director of the NSF ERC for Computational Field Simulation. As Director, he led the transition from graduated NSF ERC to its current form as the High Performance Computing Collaboratory (HPC²). Dr. Marcum also served as Deputy Director and Director of the SimCenter (an HPC² member center and currently merged within CAVS). He is currently Chief Scientist for CFD within CAVS (also an HPC² member center). As Chief Scientist for CFD, he is directly involved in the research activities of a team of multi-disciplinary researchers working on CFD related projects for DoD, DoE, NASA, NSF, and industry. Computational tools produced by these projects at MSU within the ERC, SimCenter and CAVS, and in particular Dr. Marcum’s AFLR unstructured mesh generator, are in use throughout aerospace, automotive and DoD organizations. Dr. Marcum is widely recognized for his contributions to unstructured grid technology and is currently Honorary Professor at University of Wales, Swansea, UK and a previous Invited Professor at INRIA, Paris-Rocquencourt, France.




CRTC Seminar Series on Mesh Generation


When: January 23, 2015, 10:30AM

Where:  E & CS Auditorium, First Floor


What: Riemannian Optimization for Elastic Shape Analysis


Who: Professor Kyle Gallivan

Professor Mathematics Department

Florida State University


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 Visitor Gallivan



 In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotation and reparameterization and important problems (such as computing the distance and geodesic between two curves, the mean of a set of curves, and other statistical analyses) require finding a best rotation and re-parameterization between two curves. In this talk, I focus on this key subproblem and study different tools for optimizations on the joint group of rotations and re-parameterizations. I will give a brief account of a novel Riemannian optimization approach and evaluate its use in computing the distance between two curves and classification using two public data sets. Experiments show significant advantages in computational time and reliability in performance compared to the current state-of-the-art method.

Bio: Kyle A. Gallivan is a Professor of Mathematics at Florida State University. Gallivan received the Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1983 under the direction of C. W. Gear. He worked on special purpose signal processors in the Government Aerospace Systems Division of Harris Corporation.  He was a research computer scientist at the Center for Supercomputing Research and Development at the University of Illinois from 1985 until 1993 when he moved to the Department of Electrical and Computer Engineering. From 1997 to 2008 he was a member of the Department of Computer Science at Florida State University (FSU) and a member of the Computational Science and Engineering group becoming a full Professor in 1999. He became a Professor of Mathematics at FSU in 2008 and was selected the 2012 Pascal Professor for the Faculty of Sciences of the University of Leiden in the Netherlands. He has been a Visiting Professor at the Catholic University of Louvain in Belgium multiple times through a long-standing research collaboration with colleagues there.

Over the years Gallivan's research has included: design and analysis of high-performance numerical algorithms, pioneering work on block algorithms for numerical linear algebra, performance analysis of the experimental Cedar system, restructuring compilers, model reduction of large scale differential equations, and high-performance codes for application such as ocean circulation, circuit simulation and the codes in the Perfect Benchmark Suite.

Gallivan's current main research concerns optimization algorithms on Riemannian manifolds and their use in applications such as shape analysis, statistics, and signal/image processing.





CRTC Seminar Series on Mesh Generation


When: November 7, 2014, 10:30AM

Where:  E & CS Auditorium, First Floor


What: A parallel log barrier for mesh quality improvement and updating 

Who: Professor Suzanne M. Shontz


Department of Electrical Engineering and Computer Science

University of Kansas


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 Visitor shontz




There are numerous applications in science, engineering, and medicine which require high-quality meshes, i.e., discretizations of the geometry, for use in computational simulations.  For example, meshes have been used to enable accurate prediction of the performance, reliability, and safety of solid propellant rockets.  The movie industry in Hollywood typically employs dynamic meshes in order to animate characters in films.  Large-scale applications often require meshes with millions to billions of elements that are generated and manipulated in parallel.  The advent of supercomputers with hundreds to thousands of cores has made this possible.

The focus of my talk will be on parallel algorithms for mesh quality improvement and mesh untangling.  Such algorithms are needed, for example, when a large-scale mesh deformation is applied and tangled and/or low quality meshes are the result.  Prior efforts in these areas have focused on the development of parallel algorithms for mesh generation and local mesh quality improvement in which only one vertex is moved at a time.  In contrast, we are concerned with the development of parallel global algorithms for mesh quality improvement and untangling in which all vertices are moved simultaneously. I will present our parallel log-barrier mesh quality improvement and untangling algorithms for distributed-memory machines.  Our algorithms simultaneously move the mesh vertices in order to optimize a log-barrier objective function that was designed to improve the quality of the worst quality mesh elements. We employ an edge coloring-based algorithm for synchronizing unstructured communication among the processes executing the log-barrier mesh optimization algorithm.  The main contribution of this work is a generic scheme for global mesh optimization.  The algorithm shows greater strong scaling efficiency compared to an existing parallel mesh quality improvement technique. Portions of this talk represent joint work with Shankar Prasad Sastry, University of Utah, and Stephen Vavasis, University of Waterloo.

Short Bio:  Suzanne M. Shontz is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas. She is also affiliated with the Graduate Program in Bioengineering and the Information and Telecommunication Technology Center.  Prior to joining the University of Kansas in 2014, Suzanne was on the faculty at Mississippi State and Pennsylvania State Universities.  She was also a postdoc at the University of Minnesota and earned her Ph.D. in Applied Mathematics from Cornell University.

Suzanne's research efforts focus centrally on parallel scientific computing, more specifically, the design and analysis of unstructured mesh, numerical optimization, model order reduction, and numerical linear algebra algorithms and their applications to medicine, images, electronic circuits, materials, and other applications.  In 2012, she was awarded an NSF Presidential Early CAREER Award (i.e., NSF PECASE Award) by President Obama for her research in computational- and data-enabled science and engineering.  Suzanne also received an NSF CAREER Award for her research on parallel dynamic meshing algorithms, theory, and software for simulation-assisted medical interventions in 2011 and a Summer Faculty Fellowship from the Office of Naval Research in 2009. She has chaired or co-chaired several top conferences in computational- and data-enabled science and engineering including the International Meshing Roundtable in 2010 and the NSF CyberBridges Workshop in 2012-2014 and has served on numerous program committees in the field.  Suzanne is also an Associate Editor for the Book Series in Medicine by De Gruyter Open.


CRTC Facilities

Introduction One of the most notable research programs associated with Old Dominion University is the Center for Real Time Computing (CRTC).  The purpose of the CRTC is to pioneer advancements in real-time and large-scale physics-based modeling and simulation computing utilizing quality mesh generation.  Since its inception, the CRTC has explored the use of real-time computational technology in Image Guided Therapy, storm surge and beach erosion modeling, and Computational Fluid Dynamics simulations for complex Aerospace applications.  The center and its distinguished personnel accomplish their objectives through rigorous theoretical research (which often involves the use of powerful computers) and dynamic collaboration with partners like Harvard Medical School and NASA Langley Research Center in US and Center for Computational Engineering Science (CCES) RWTH Aachen University in Germany and Neurosurgical Department of Huashan Hospital Shanghai Medical College, Fudan University in China. This research is mainly funded from government agencies like ational Science Foundation, National Institute of Health and NASA and philanthropic organizations like John Simon Guggenheim Foundation.

Nikos Office The CRTC is currently under the direction of Professor Nikos Chrisochoides, who has been the Richard T. Cheng Chair Professor at Old Dominion University since 2010.  Dr. Chrisochoides’ work in parallel mesh generation and deformable registration for image guided neurosurgery has received international recognition.  The algorithms and software tools that he and his colleagues developed are used in clinical studies around the world with more than 40,000 downloads. He has also received significant funding through the National Science Foundation for his innovative research in parallel mesh generation.  

CRTC Lab Space and Resources To further its mission of fostering research, Old Dominion University has provided the Center for Real Time Computing with lab space in its Engineering and Computational Sciences Building.  The CRTC utilizes the lab space and the Department of Computer Science’s other resources to conduct its studies.  The principal investigators (PIs) who lead research projects at the CRTC Lab have access to a Dell Precision T7500 workstation, featuring a Dual Six Core Intel Xeon Processor X5690 (total of 12 cores).  The processor has a clock speed of 3.46GHz, a cache of 12MB, and QPI speed of 6.4GT/s.  The processor also supports up to 96GB of DDR3 ECC SDRAM (6X8GB) at 1333MHz. The system is augmented by the nVIDIA Quadro 6000.  With 6 GB of memory, this device provides stunning graphic capabilities. The PIs also have command of an IBM server funded from a NSF MRI award (CNS-0521381), as well as access to the Blacklight system at the Pittsburg Supercomputing Center.

Community Outreach

In addition to research, the lab space and resources of the CRTC may be used for outreach and education activities.  Students from the local high school community have visited the lab to view its state-of-the-art equipment and discuss computer science topics with distinguished experts.  To continue its outreach to the community, the CRTC will soon make its IBM server available to high school students wishing to gain experience in high performance computing. By granting controlled access of its equipment to interested high school students, the CRTC provides them with an exceptional introduction to computer science work and research, without jeopardizing other research projects.  The CRTC also possesses a 3D visualization system, which it uses in its outreach/education programs.  This high-quality, interactive system is especially motivating and exciting to high school students stimulated by multi-media.


Information Technology Services (ITS) at Old Dominion University maintains a robust, broadband, high-speed communications network and High Performance Computing (HPC) infrastructure.  The facility utilizes 3200 square feet of conditioned space to accommodate server, core networking, storage, and computational resources. The data center has 100+ racks deployed in alternating hot and cold aisle configuration. The data center facility is on raised flooring with minimized obstruction to help facilitate optimized air flow.  Some of the monitoring software’s being utilized in the operations center are Solarwinds ORION network performance software and Nagios Infrastructure monitoring application. IT Operations center monitors the stability and availability of about 400 production servers (physical and virtual), close to 400 network infrastructure switching and routing devices, enterprise storage, and high performance computing resources.

The network is currently comprised of a meshed Ten Gigabit Ethernet backbone supporting voice, data and video with switched 10Gbps connections to the servers and 1Gbps connections to the desktops. Inter-building network connectivity consists of redundant fiber optic data channels yielding high-speed Gigabit connectivity, with Ten-Gigabit connectivity for key building on campus. Ongoing upgrades to Inter-building networks will result in data speeds of 10Gbps for the entire campus. ITS currently provides a variety of Internet services, including 1Gbps connection to Cox communication, 2Gbps connection to Cogent. Connections to Internet2 and Cogent are over a private DWDM regional optical network infrastructure, with redundant 10Gbps links to MARIA aggregation nodes in Ashburn, Virginia and Atlanta, Georgia. The DWDM infrastructure project named ELITE (Eastern Lightwave Internetworking Technology Enterprise) provides access not only to the commodity Internet but gateways to other national networks to include the Energy Science Network and Internet2. 

HPC Turing Cluster The University supports research computing with parallel computing using MPI and OpenMP protocols on compute cluster architectures with shared memory and symmetric multiprocessing compute nodes. Old Dominion University has recently introduced a new higher performance computing cluster named Turing. This cluster is based on Intel’s ivy-bridge architecture and each node has 20 cores and 128GB of memory. After the recent upgrade to the Turing cluster 2700 cores are available to researchers for computational needs. As part of the expansion of Turing Cluster, researchers have access to high memory nodes and nodes with Xeon Phi co-processors. FDR based infiniband infrastructure provides the communication path for the cluster inter communication. Mass storage is integrated in this cluster at 20Gbps and scratch space is accessible over FDR based infiniband infrastructure. Turing cluster has redundant head nodes and login nodes for increased reliability. Turing cluster is primarily used by faculty members who are conducting research using software such as Ansys, Comsol, R, Mathematics, and Matlab among other software’s. Integrated in Turing cluster is a number of GPU nodes with NVidia Tesla M2090 GPU’s, to help facilitate computation that requires graphic processors. 

 Hardware1  Hardware1  Hardware1  Hardware1

Data Storage EMC’s Isilon storage is the primary storage platform for high performance computing environment. The storage environment provides home and mass storage for the HPC environment with a total capacity of 736TBytes. The storage platform provides scale out NAS storage that delivers increased performance for file based data applications and workflows. In addition EMC’s VNX storage platform is the primary storage environment on campus for virtualized server environments as well as campus data enterprise shares. EMC’s VNX platform is a tiered, scalable storage environment for file, block and object storage. This storage solution is deployed in the enterprise data center with the associated controller, disk, network and power redundancy.

Data Center HVAC Solution consist of has three (3) 30 Ton HVAC units deployed in an N+1 redundancy deployment. Racks of server and computational hardware are arranged in alternating hot and cold aisle configuration. The HVAC units are deployed on a raised floor arrangement with perforated tiles in the cold aisles which allows for superior environmental controls and maintaining the data center at the desired and optimal temperature levels. Optimized performance of chillers in data center is critical for environment control and for this reason the main data center has a 45 Ton chiller installed to facilitate ventilation and air conditioning. In addition ITS has an additional fourteen (14) above the rack cooling units complement the main HVAC units. These above the rack cooling units do not take any additional rack space in the data center. These units are designed to draw hot air from the computational equipment racks and hot aisles and then dissipate conditioned cold air down the cold aisle. This solution provides for an energy efficient cooling solution with zero floor space requirements.

Network Communication Infrastructure

Old Dominion University network communication infrastructure is designed using the state of the art networking and switching hardware platforms. The campus infrastructure backbone is fully redundant and capable of 10Gbps data rates between all distribution modules. The data center infrastructure is designed to operate at 40Gbps data rates between the server and storage platforms.  

 Hardware1  Hardware1  Hardware1  Hardware1

DWDM E-LITE Infrastructure Old Dominion University manages the Eastern Lightwave Integrated Technology Enterprise (E-LITE) infrastructure, which provides 10Gbps connectivity to a number of regional institutions to include the College of William & Mary, Jefferson Lab, Old Dominion University, and the Virginia Modeling, Analysis, and Simulation Center (VMASC). E-LITE infrastructure is designed in a physical ring around the Hampton Roads area providing protected 10Gbps connectivity between the member sites and other national networks like MARIA, Energy Science Network and Internet2. E-LITE network and connectivity to MARIA is being redesigned to upgrade the local DWDM ring to be 100Gbps capable as well as establishment of 100Gbps connection to Internet2.  Old Dominion University recently completed a major upgrade on the core server distribution to integrate Nexus 7000 hardware. Nexus 7000 platforms are Cisco Systems next generation switching platforms that are designed for the data center to provide virtualized hardware, in-service upgrades, higher 10Gbps and 40Gbps density, higher performance and reliability. These platforms also provide capability to integrate 100Gbps interfaces in the data center infrastructure as needed. Cisco Nexus platforms include 7000 and 5000 series that provide a higher bandwidth and reliable backbone infrastructure for critical services using technologies such as virtual port channels.

Data Center UPS Batteries for HPC and Network infrastructure consist of a (uninterrupted power supply) UPS system rated at 375KWatts. This unit allows for considerable capacity needed for switching between commercial electrical power and dedicated building power generator. The current UPS system utilizes high performance insulated gate bipolar transistors to provide for larger power capabilities, high speed switching and lower control power consumption.

Campus Virtualized Network Infrastructure. The virtualized network infrastructure supports the unique requirements of University business operations, research, scholarly activities, and online course delivery.  Course delivery technologies include video streaming and video conferencing.  The Campus Network Virtualization is an initiative that was implemented in the campus environment  to make sure we enable our network infrastructure to provide the following features: (i) Communities of interests (Virtual Networks). This will allow us to create network based user communities that have the same functions and communication/application needs. This is being accomplished by using MPLS technology. (ii) High performance and redundant security infrastructure. Security is an important part of any network infrastructure. We have to ensure that users are able to perform all their needed tasks on the network while at the same time have the best possible security protection in place.  (iii) Flexibility to provision independent network infrastructures. This feature allows us to create smaller independent logical networks on the existing physical infrastructure. This is of great benefit in a research institution of ODU’s stature and will allow us to work with researchers to provide them the needed resources for their success.



Our software products cover enabling technologies for Biomedical Image Computing, Large and Real-Time Finite Element Analysis, Maasive Parallel Computing and STEM Education.

BioMedical Image Computing


  • Real-Time 3D Physics Based Non-Rigid Registration
  • Tetrahedral Image-to-Mesh Conversion
  • Robust Scatter Points Approximation Using FE Biomechanical Model
  • Parallel N-Dimensional Exact Signed Euclidean Distance Transform
  • Automatic Assesment of Brain MRI Image Assesment Using Robust Local Hausdorff 


  • Image-to-Mesh Conversion for Drosophila Gene Expression
  • Estimation of Lower Bounds on the Lenght of Protein Chain Segments


Parallel Mesh Generation

  • 2D Medial Axis Domain Decomposition
  • 2D Parallel Constrained Delaunay Mesh Generation
  • 3D Real-Time BCC-based Single-Tissue Image-to-Mesh Conversion


Parallel Runtime Systems

  • Data Movement and Control Substrate
  • Mobile Object Layer
  • Portable Runtime Environment for Mobile Applications
  • Multi-Layered Runtime System


STEM E-Learning Technologies 

  • STEM Video Analytics
  • STEM TBD (Matt)  Game