International Data Corporation (IDC) today announced the fifth round of recipients of the HPC Innovation Excellence Award at the ISC'13 supercomputer industry conference in Leipzig, Germany. Prior winners were announced at the ISC'11, SC'11, ISC'12, and SC'12 supercomputing conferences.
“The winners achieved clear success in applying HPC to greatly improve business ROI, scientific advancement, and/or engineering successes. Many of the achievements also directly benefit society.”
The HPC Innovation Excellence Award recognizes noteworthy achievements by users of high performance computing (HPC) technologies. The program's main goals are to showcase return on investment (ROI) and scientific success stories involving HPC; to help other users better understand the benefits of adopting HPC and justify HPC investments, especially for small and medium-size businesses (SMBs); to demonstrate the value of HPC to funding bodies and politicians; and to expand public support for increased HPC investments.
"IDC research has shown that HPC can impact innovation cycles greatly and can potentially generate ROI. The award program aims to collect a large set of success stories across many research disciplines, industries, and application areas," said Chirag Dekate, Research Manager, High Performance Computing at IDC. "The winners achieved clear success in applying HPC to greatly improve business ROI, scientific advancement, and/or engineering successes. Many of the achievements also directly benefit society."
Winners of the first four rounds of awards, announced in 2011 and 2012, included 24 organizations from the U.S., three from the People's Republic of China, one from Canada, two from India, and one each from Australia and Spain.
The new award winners and project leaders announced at ISC'13 are as follows (contact IDC for additional details about the projects):
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Alenia Aermacchi (Italy). Engineers at Alenia Aermacchi utilized technical computing and scientific computing tools in the "Clean Sky" project to design a new generation of environmentally friendly aircraft. While seeking the most promising configuration, the engineers shaped two different wings to fulfill separately the two goals of enhancing aerodynamic performance and reducing wing weight. This was accomplished through the use of computational fluid dynamics (CFD) and other technical computing tools. The two promising configurations enhanced cruise efficiency by 2.5% and reduced the wing weigh by 4%. Lead: Enrica Marentino
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High Performance GeoComputing Laboratory at the University of California at San Diego (U.S.). The High Performance GeoComputing Laboratory, University of California at San Diego, has developed a highly scalable and efficient GPU-based finite difference code based on AWP-ODC, a community code developed and supported by the Southern California Earthquake Center for large-scale earthquake simulations. AWP-ODC-GPU achieved perfect scalability on the Oak Ridge National Laboratory's Titan supercomputer and was used to simulate realistic 0-10 Hz earthquake ground motions, the largest-ever earthquake simulation performed. This code was re-structured to enable maximized throughput, reduced time-to-solution, and scalability. The code achieved 100% parallel efficiency on 8,192 GPUs and sustained 2.33 petaflop/sec. on Titan. Moreover, this GPU-powered code has been transformed to calculate Strain Green Tensors, resulting in a 110-fold speedup in key strain tensor calculations critical to probabilistic seismic hazard analysis. This achievement makes a California state-wide hazard model a goal reachable with existing supercomputers. The performance of the code is expected to take physics-based seismic hazard analysis to a new level using petascale, heterogeneous computing resources, saving more than 500 million core-hours as required by building engineering design. Lead: Yifeng Cui
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DOD High Performance Computing Modernization Program (U.S.). This HPCMP-supported project, within the armor/anti-armor portfolio, provided direct support to the Warfighter program. The fundamental goals for using modeling and simulation in support of the armor/anti-armor development programs were to reduce time, resources, and risk while improving the quality of information available to designers, users, and decision makers. HPCMP capabilities enabled the development and testing of new armor/anti-armor capabilities in the following areas: propulsion, interior ballistics, external trajectory determination, terminal ballistics, warhead analysis, and sensors. The total upper bound ROI amounted to $935 million. Lead: Deborah Schwartz
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DOD High Performance Computing Modernization Program (U.S.). This HPC innovation comprised a suite of cutting-edge computational efficiency enhancement methodologies applied to complex missile-related, aero-propulsive problems with combustion. These methodologies were integrated into CRAFT CFD® and CRUNCH CFD®, two CFD codes in widespread use by DoD to support missile design and evaluation, and encompassed gas-phase/multi-phase combustion as well as laminar/turbulent chemistry, including tabulated/neural network approaches, reduced/adaptive chemistry, turbulent scalar fluctuation model (SFM) and GPU acceleration. By leveraging state-of-the-art HPC resources provided by DoD HPCMP, these innovative methodologies delivered higher-fidelity predictive capabilities to the analysis of missile systems/components, thereby enabling CFD to serve as a cost-effective design tool and virtual testbed for missile evaluation. Lead: John West
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ESTECO and Airworks Engineering (Italy). Airworks, a multidisciplinary company for mechanical engineering, was facing the challenge of improving efficiency in converting wind energy into electrical power by optimizing the whole assembly of a wind power unit rotor. Experts in the firm's wind power unit, specialists in CAD (computer-aided design) and CFD (computational fluid dynamics) professionals from different organizations were involved in a complex design scenario and needed to collaborate effectively. Engineers from the University of Trieste prepared the parametric CAD model and set up CFD simulations, while Airworks developed aerodynamic performance calculations of the wind rotor blade and subsequently performed the optimization analysis. The technical computing-driven solution enabled the seamless execution of inter-organizational simulation workflows. With the set up of the optimization workflow, Airworks professionals were able to explore and evaluate new parametric geometry, leading to innovative designs. The end result was a wind turbine design with an outstanding power coefficient and an annual energy production increase as high as 1.26%. Lead: Paolo Vercesi
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University College London and NAG HECTOR dCSE (UK). HPC experts from Numerical Algorithms Group (NAG), working under NAG's Computational Science and Engineering (CSE) support service for HECToR, the UK's national academic supercomputing facility, have optimized a Quantum Monte-Carlo application for multicore architectures, resulting in a performance increase of a factor of four. The objectives of this dCSE project were to enable the CASINO Quantum Monte Carlo code to effectively use the multicore processors of HECToR's Cray XT supercomputer and thus model more complex physical systems with greater efficiency. Shared memory techniques were introduced to allow larger models to be computed with greater efficiency by enabling multiple MPI processes on a single node to share a common data set, thus reducing the number of nodes needed for a given simulation. Further work including hierarchical parallelism with OpenMP and I/O optimizations improved the scalability of the code, enabling CASINO to run 60-80% faster for simulations using more than 10,000 cores. Following NAG's work, the scientists were able to run on 40,000 cores of the Jaguar petascale supercomputer at Oak Ridge National Laboratory. It is estimated that this dCSE work saved 12 million AUs (allocation units) for a one year research project on HECToR, equivalent to savings of as much as £760,000 and the potential for future savings of up to several million pounds. Lead: HECToR dCSE
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University of Warwick and NAG HECTOR dCSE (UK). HPC experts from NAG, working under NAG's Computational Science and Engineering (CSE) support service for HECToR, the UK's national academic supercomputing facility, have improved the scalability and performance of DL_POLY_3, a widely used software package for studying molecular dynamics. The 20-fold improvement in performance achieved by this project enabled a study of egg-shell formation that was infeasible with previous performance. DL_POLY_3 is a general-purpose package for classical molecular dynamics (MD) simulations from STFC Daresbury Laboratory. University of Warwick researchers Mark Rodger and David Quigley, in collaboration with colleagues at the University of Sheffield, used DL_POLY_3 and the HECToR supercomputers to study the role of a protein called ovocleidin-17 (OC-17) in chicken eggshell formation. Significant performance improvements were needed to make the modeling possible in feasible timescales using the HECToR supercomputers, especially in terms of parallel I/O. Lead: HECToR dCSE
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Bottero S.p.A. (Italy). Bottero has recently introduced the EMOC, a completely new family of Mold Opening and Closing (MOC) mechanisms for the hollow glass industry. This complex project combined the innovation, in terms of mold movement (speed and precision), cooling system, maintenance facility ("top mounted"), and maintaining compatibility with previous standards. This multidimensional aspect led to hard space constraints, requiring complex 3D kinematic schema, and required advanced CFD simulation and design tools. A high performance level was required for this mechanism, particularly regarding clamping forces in closed positions, force available at the beginning of the molds stroke, reduced closing time, absence of vibrations during movement, and robustness with respect to irregularities in air supply. CFD tools and simulation techniques were utilized to improve the design in EMOC. Lead: Alberto Marino
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Polestar Racing (Sweden). The Polestar Racing vehicle model had to be modified without considering the chassis design parameters, which were previously the core of the optimization analysis. Design simulation acquired an even greater importance as the best combination of the front-to-rear weight, aerodynamics, and brake distribution had to be executed in three days. Polestar Racing utilized a suite of simulation tools from MSC Software, the Lap Time Simulation (LTS) in-house code, and modeFRONTIER to devise a technical computing-driven approach to improve performance. The resulting improvements in weight, aerodynamics, and brake distribution led to lap time reductions ranging from 0.19 to 0.50 seconds. Lead: Per Blomberg
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RENCI (U.S.). Scientists and researchers at the Renaissance Computing Institute (RENCI) developed a comprehensive informatics framework called NCGENES, enabling medical decision support by systemizing genomic analysis and high performance computing to mine genomic data for clinical and research use. The framework tackles one of the biggest challenges in genomic medicine - the need for automated sorting of the millions of variants generated by genome-scale sequencing to identify the very few with actual clinical relevance. The innovative framework also provides a proof of principle for how genomic medicine can be carried out in a practical manner. NCGENES breaks new ground by guiding and defining best practices for the use of whole genome sequencing as a diagnostic tool to aid patients and clinicians in making sense of medical informatics. Lead: Phil Owen
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RENCI - ADCIRC Surge Guidance System (U.S.). This system uses the coupled coastal circulation, storm surge, and wind wave model ADCIRC+SWAN to produce high-resolution forecasts of storm surge, near shore waves, and water inundation when tropical or extra-tropical storms threaten the U.S. Atlantic or Gulf Coasts. The complete system, the ADCIRC Surge Guidance System (ASGS), includes an advanced web-based display (NC-Coastal Emergency and Risk Assessment). During an active storm, ASGS is run 2-4 times each day on a 150-node Dell PowerEdge M610/cluster (2 x 2.8Ghz Intel Nehalem-EP 5560, quad core) at the Renaissance Computing Institute (RENCI). The outputs from these runs are incorporated into guidance and forecasting efforts by the National Weather Service, the National Hurricane Center, and agencies such as the U.S. Coast Guard, the U.S. Army Corps of Engineers, FEMA, and local and regional emergency management personnel. The resulting forecasts are used for evacuation decisions, to position supplies and response personnel, for search and rescue, and for other event-based decision support as needed. Lead: Rick Luettich, Brian Blanton
"The Council on Competitiveness would like to congratulate all the winners of the HPC Innovation Excellence Award and thank all of those who submitted entries. The significance of HPC to the private sector will only be fully appreciated when examples such as these are recognized for their economic value," said Dr. Cynthia McIntyre, Senior Vice President for the HPC Initiative at the Council on Competitiveness.
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