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Computer Science and Mathematics Division
INCITE Involvement

INCITE History

Over the past 30 years, the Department of Energy’s (DOE) supercomputing program has played an increasingly important role in scientific research by allowing scientists to create more accurate models of complex processes, simulate problems once thought to be impossible, and to analyze the increasing amount of data generated by experiments. To help the research communities fully tap into the capabilities of current and future supercomputers, Under Secretary for Science Raymond Orbach launched the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program in 2003. The INCITE program was conceived specifically to seek out computationally intensive, large-scale research projects with the potential to significantly advance key areas in science and engineering. The program encourages proposals from universities, other research institutions and industry.

Since 1974, DOE’s Office of Science, the nation’s single largest supporter of basic research in the physical sciences, has provided supercomputing resources for unclassified research through the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. During the first two years of the INCITE program, 10 percent of the resources at NERSC were allocated to INCITE awardees. However, demand for supercomputing resources far exceeded available systems and in 2003, the Office of Science identified increasing computing capability by a factor of 100 as the second priority on its Facilities of the Future list. The goal was to establish Leadership Class Computing resources to support open science. As a result of a peer-reviewed competition, the first Leadership Computing facility was established at Oak Ridge National Laboratory in 2004. A second Leadership Computing facility was established at Argonne National Laboratory in 2006. This expansion of computational resources led to a corresponding expansion of the INCITE program. In 2007, Argonne, Lawrence Berkeley, Oak Ridge and Pacific Northwest national laboratories all provided resources for the INCITE program.

Click HERE to learn more about the INCITE program.

CSM 2008 INCITE Projects

Principal Investigator: Robert Harrison

Affiliation: Oak Ridge National Laboratory

Proposal Title:
“An Integrated Approach to the Rational Design of Chemical Catalysts”

Research Summary:

Leadership-scale simulation using advanced theory in close collaboration with experiment is the only path towards the rational design of novel chemical catalysts that are crucial for many clean energy sources and for new manufacturing processes. Catalytic processes are directly involved in the synthesis of 20% of all industrial products. Within the DOE mission, catalysts feature prominently in cleaner and more efficient energy production, exemplified by the fuel cell and storage technologies required to realize the President’s goal of a hydrogen economy. Experimental tools are unable to provide data on all of the steps involved in catalytic processes especially under operating conditions. Computational modeling and simulation can fill this gap, supporting experiment by improved analysis and interpretation of data, and ultimately, in partnership with experiment, enabling the design of catalysts from first principles. Through a combination of leadership-scale computing and continued improvements in theory and algorithm, computational chemistry is about to cross a threshold that will deliver the 100-1000x increase in effective simulation power required to make significant progress with our scientific objectives of improved activity and selectivity.

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Principal Investigator: Anthony Mezzacappa

Affiliation: Oak Ridge National Laboratory

Proposal Title:
“Multidimensional Simulations of Core Collapse Supernovae”

Research Summary:

This project will perform 3-D simulations to understand how stars more than ten times the mass of our sun die in catastrophic stellar explosions known as core collapse supernovae. Core collapse supernovae are the dominant source of elements in the Universe, including all the elements between oxygen and iron and half the elements heavier than iron; life would not exist without these elements. These supernovae are complex, three-dimensional, multi-physics events, but presently there are no three-dimensional models of sufficient realism. This is a significant void in supernova theory. The simulations described here will begin to fill this void. These simulations will be the first three-dimensional simulations performed with multifrequency neutrino transport, critical to realistic modeling of the neutrino shock reheating that is believed to be central to the supernova explosion mechanism. A complete understanding of the core collapse supernova mechanism requires parallel simulations in one, two, and three spatial dimensions. The nuclei in the stellar core undergo a transition through a series of complex shapes that can only be modeled in three spatial dimensions. These modeling efforts will extend to three dimensions both the macroscopic and microscopic models of stellar core phenomena in core collapse supernovae.

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Principal Investigator: Thomas Schulthess

Affiliation: Oak Ridge National Laboratory

Proposal Title:
“Predictive and accurate Monte Carlo based simulations for Mott insulators, cuprate superconductors, and nanoscale systems.”

Research Summary:

Better electric grid technologies, high-density magnetic hard drives, and more efficient biofuel production require that we understand and optimize relevant materials. This project will perform simulations of Mott insulators, high-temperature superconductors, magnetic nanoparticles, and select biomolecular systems that are key for these goals and will accelerate development of such technologies. Applying recent advances in Monte Carlo techniques, this project will push the envelope of computational science at the petascale in order to understand, predict, design, and exploit complex behavior that emerges at the nanoscale. Initial emphasis will be to break new ground in our understanding of transition metal oxide systems, where strong electronic correlations drive emergent behavior, such as high-temperature superconductivity in the cuprates. In the longer term, our simulations will lead to breakthroughs in nanoscale systems, such as nanomagnets and biomolecular systems with complex interactions, subject to temperature driven fluctuations and entropic effects.

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Principal Investigator: Jeremy Smith

Affiliation: Oak Ridge National Laboratory

Proposal Title:
“Cellulosic Ethanol: Physical Basis of Recalcitrance to Hydrolysis of Lignocellulosic Biomass”

Research Summary:

Efficient production of ethanol via hydrolysis of cellulose into sugars is a major energy policy goal. This project will perform highly-parallelized multilength- scale computer simulations to help understand the physical causes of resistance of plant cell walls to hydrolysis – the major technological challenge in the development of viable cellulosic bioethanol. The solution to this challenge may be the improvement of pretreatments or the design of improved feedstock plants (or both). Plant cell wall lignocellulosic biomass is a complex material composed of crystalline cellulose microfibrils laminated with hemicellulose, pectin, and lignin polymers. The simulations performed will be part of a larger effort to integrate the power and capabilities of the neutron scattering and high-performance computering at Oak Ridge National Laboratory to derive information on lignocellulosic degradation at an unprecedented level of detail. The simulations will provide detailed knowledge of the fundamental molecular organization, interactions, mechanics and associations of bulk lignocellulosic biomass.

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Principal Investigator: Madhava Syamlal

Affiliation: National Energy Technology Laboratory

Proposal Title:
“Clean and Efficient Coal Gasifier Designs using Large-Scale Simulations”

Research Summary:

This project will use large-scale parallel computing to speed up high fidelity coal gasifier simulations, making such studies feasible for the ongoing design and optimization of advanced fossil fuel plants. Through use of MFIX, a multiphase computational fluid dynamics model, researchers will explicitly address the issue of scale-up by studying the effect of various operating conditions on the performance of a commercial scale Clean Coal Power Initiative (CCPI) transport gasifier. The calibrated gasifier model is now being used to help with the design of commercialscale systems intended for CCPI projects and tomorrow’s zero-emissions fossil fuel plants. These high fidelity simulations will provide design engineers unique and valuable information on the gas and coal flow in the gasifier, information otherwise unavailable to them since no experimental measurements or visualizations exist for the gasifier operating conditions. Furthermore, these simulations can help minimize the uncertainty in other scale-up issues like reactor length over diameter ratio, coal feed rate, solids recirculation rate, and effect of recycled gas. This is a unique and tremendous opportunity -- the results of this project will have direct impact on the design of advanced environmentally friendly power plants of the 21st century.

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Principal Investigator: Warren Washington

Affiliation: National Center for Atmospheric Research

Proposal Title:
“Climate-Science Computational End Station Development and Grand Challenge Team”

Research Summary:

The Climate Science Computational End Station (CCES) will predict future climates using scenarios of anthropogenic emissions and other changes resulting from energy policies options. CCES will also improve the scientific basis, accuracy and fidelity of climate models, delivering climate change simulations that directly inform national science policy, thereby contributing to the DOE, NSF and NASA science missions. CCES will advance climate science through both an aggressive model development activity and an extensive suite of climate simulations. Advanced computational simulation of the Earth System is built on the successful interagency collaboration of NSF and DOE in developing the Community Climate System Model (CCSM), collaboration with NASA in carbon data assimilation, and university partners with expertise in computational climate research. Of particular importance is the correct simulation of the global carbon cycle and its feedbacks to the climate system, including its variability and modulation by ocean and land ecosystems. Continuing model development and extensive testing of the CCSM system to include recent new knowledge about such processes is at the cutting edge of climate science research and is a principal focus of the CCES.

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Principal Investigator: Peter Lichtner

Affiliation: LANL

Proposal Title:
“Modeling Reactive Flows in Porous Media”

Research Summary:

The goal of the project is to capture the observed slow leaching of uranium from the Hanford sediment and model the behavior of the uranium plume over time, taking into account variations in the Columbia River stage.

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Principal Investigator: Zhengyu Liu

Affiliation: University of Wisconsin - Madison

Proposal Title:
“Assessing Global Climate Response of the NCAR-CCSM3: CO2 Sensitivity and Abrupt Climate Change”

Research Summary:

The primary goal of this project is to perform the first synchronously coupled transient ocean/atmosphere/dynamic vegetation general circulation model simulation of the past 21,000 years using the NCAR Community Climate System Model (CCSM3). This experiment will addresses two fundamental questions on future climate changes: "What is the sensitivity of the climate system to the change of greenhouse gases, notably CO2?" and "How does the climate system exhibit abrupt changes on decadal-centennial time scales?"

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Principal Investigator: Patrick H. Worley

Affiliation: Oak Ridge National Laboratory

Proposal Title:
“Performance Evaluation and Analysis Consortium End Station”

Research Summary:

To maximize the utility of Leadership Class systems, such as the Cray X1E, Cray XT3, and IBM BlueGene/L (BG/L), the performance community (performance tool developers, system and appliation performance evaluators, and performance optimization engineers) must understand how to use each system most efficiently. To further understanding of these highend systems, this proposal is focusing on four primary goals: (1) update and extend performance evaluation of all systems using suites of both standard and custom micro, kernel, and application benchmarks; (2) continue to port performance tools to the BG/L, X1E, and XT3, making these available to high-end computing users, and further develop the tools so as to take into account the scale and unique features of the Leadership Class systems; (3) validate the effectiveness of performance prediction technologies, modifying them as necessary to improve their utility for predicting resource requirements for production runs on the Leadership Class systems; (4) analyze and help optimize current or candidate Leadership Class application codes.

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