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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Benchmarking high performance computing architectures with CMS’ skeleton framework

Here, in 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta, Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

GridPACK™ : A Framework for Developing Power Grid Simulations on High-Performance Computing Platforms

This paper describes the GridPACK™ framework, which is designed to help power grid engineers develop modeling software capable of running on high performance computers. The framework makes extensive use of software templates to provide high level functionality while at the same time allowing developers the freedom to express whatever models and algorithms they are using. GridPACK™ contains modules for setting up distributed power grid networks, assigning buses and branches with arbitrary behaviors to the network, creating distributed matrices and vectors and using parallel linear and non-linear solvers to solve algebraic equations. It also provides mappers to create matrices and vectors based on properties of the network and functionality to support IO and to mana

Palmer, Bruce J.↗
DOE OSTI2023

Characterizing Reactor Operations from Realistic Simulated Environmental Samples: Combining High-Performance Computing and Data Analytics

Environmental sampling is a common technique employed by inspectors and facility operators in nuclear safeguards, proliferation detection, and process monitoring contexts. Interpreting measurements performed on samples or collections of samples and ensuring the information extracted is accurate and precise is difficult. To date, these analyses have relied on simulated data to enable systematic studies; however, these models are inherently limited by the fidelity of the models and the implicit spatial averaging of isotopic composition or other signatures of interest. To advance this capability, we have refined the spatial discretization and expanded the range of physics in the simulation codes we use to perform reactor simulations and depletion calculations. This allows us to generate data that are more representative of real environmental samples, especially for the length scale of the isotopic composition and associated variation. Accordingly, these new data allow a more realistic assessment of traditional and new data analytic analysis methods. Here we present motivation for developing reactor simulations using high-performance computing methods and resources, impacts of these new simulations on our assessment of data analysis and interpretation methods, and initial results of developing and systematically testing data analytic methods designed to overcome the challenges expected of real-world samples. We also quantify the performance of these analyses using defensible statistical methods.

Dayman, Ken J.↗
NASA NTRS1991

Implementation of the Lanczos eigen-solver for the CSI code on high performance computers

The focus of this research is to implement a Lanczos algorithm for the Control-Structure Integration (CSI) code which can exploit both parallel and vector capabilities provided by modern, high performance computers. A partial restoring orthogonality scheme is also developed and incorporated into the basic Lanczos algorithm. The numerical performance of the proposed parallel-vector Lanczos algorithm is demonstrated by solving for the frequencies and mode shapes of the Phase Zero CSI model. The superior performance of the Lanczos algorithm is illustrated in tabular form.

Nguyen, Duc T.↗
DOE OSTI2024

A Framework for Integrating Quantum Simulation and High Performance Computing

Scientific applications are starting to explore the viability of quantum computing. This exploration typically begins with quantum simulations that can run on existing classical platforms, albeit without the performance advantages of real quantum resources. In the context of high-performance computing (HPC), the incorporation of simulation software can often take advantage of the powerful resources to help scale-up the simulation size. The configuration, installation and operation of these quantum simulation packages on HPC resources can often be rather daunting and increases friction for experimentation by scientific application developers. We describe a framework to help streamline access to quantum simulation software running on HPC resources. This includes an interface for circuit-based quantum computing tasks, as well as the necessary resource management infrastructure to make effective use of the underlying HPC resources. The primary contributions of this work include a classification of different usage models for quantum simulation in an HPC context, a review of the software architecture for our approach and a detailed description of the prototype implementation to experiment with these ideas using two different simulators (TNQVM & NWQ-Sim). We include initial experimental results running on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) using a synthetic workload generated via the SupermarQ quantum benchmarking framework.

Shehata, Amir [ORNL] (ORCID:0000000224531426)↗
NASA NTRS1996

High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems

This is the final technical report for the project entitled: "High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems", funded at NPAC by the DAO at NASA/GSFC. First, the motivation for the project is given in the introductory section, followed by the executive summary of major accomplishments and the list of project-related publications. Detailed analysis and description of research results is given in subsequent chapters and in the Appendix.

Makivic, Miloje S.↗
DOE OSTI2025

Job Scheduler-Driven Power Gateway for High Performance Computing

Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including the large load-follow requirements observed in multi-user HPC systems. The microgrid’s flexibility to operate in either grid forming or grid following mode and to actively switch between these modes enables baseline power from multiple non-baseline DER while maintaining high power quality metrics for the HPC system. But this enormous flexibility in demand response and time of use shifting is generally programmed independently of any integration with an HPC job scheduler which can better inform the load shaping by the microgrid. While there are many existing approaches where the HPC job scheduler takes in information from the grid to make queue scheduling decisions, this work takes the opposite view and explores a scheduler where the jobs in the queue can directly impact the settings of the grid. Several HPC scheduler strategies are tested where the jobs in the queue directly impact the settings of a microgrid designed for HPC operation which is driving a datacenter with three classes of HPC architectures. The scheduler operation is shown using a microgrid with 64 kW of solar capacity and 320 kWh of battery over a period of 21 days operating with significant low-follow swings, a throttled grid, cloudy conditions, switching between grid following and grid forming modes, and a wide range of battery states-of-charge all while maintaining high quality power metrics. The scheduler provides a mechanism for the job queue to directly impact a power gateway like a microgrid and to improve HPC power outcomes such as maximizing renewable energy usage

microgrid↗
DOE OSTI2019

Energy Performance Evaluation of Aquila's Aquarius Fixed Cold Plate Cooling System at NREL's High Performance Computing Center

In the first half of 2018, as part of a partnership with Sandia National Laboratories, Aquila installed its fixed cold plate, liquid-cooled Aquarius rack solution for high-performance computing (HPC) clustering at the National Renewable Energy Laboratory's (NREL's) Energy Systems Integration Facility (ESIF). This new fixed cold plate, warm-water cooling technology together with a manifold design provides easy access to service nodes and eliminates the need for server auxiliary fans altogether. Aquila and Sandia National Laboratories chose NREL's HPC Data Center for the initial installation and evaluation because the data center is configured for liquid cooling and has the required instrumentation to measure flow and temperature differences to facilitate testing. This paper gives an overview of the Aquarius fixed cold plate cooling technology and provides results from early energy performance evaluation testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Comparative Implementation of High Performance Computing for Power System Dynamic Simulations

Dynamic simulation for transient stability assessment is one of the most important, but intensive, computations for power system planning and operation. Present commercial software is mainly designed for sequential computation to run a single simulation, which is very time consuming with a single processer. The application of High Performance Computing (HPC) to dynamic simulations is very promising in accelerating the computing process by parallelizing its kernel algorithms while maintaining the same level of computation accuracy. This paper describes the comparative implementation of four parallel dynamic simulation schemes in two state-of-the-art HPC environments: Message Passing Interface (MPI) and Open Multi-Processing (OpenMP). These implementations serve to match the application with dedicated multi-processor computing hardware and maximize the utilization and benefits of HPC during the development process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗
DOE OSTI2020

High-performance computing in water resources hydrodynamics

In this work, we present a vision of future water resources hydrodynamics codes that can fully utilize the strengths of modern high-performance computing. The advances to computing power, formerly driven by the improvement of central processing unit processors, now focus on parallel computing and, in particular, the use of graphics processing units (GPUs). However, this shift to a parallel framework requires refactoring the code to make efficient use of the data as well as changing even the nature of the algorithm that solves the system of equations. These concepts along with other features such as the precision for the computations, dry regions management, and input/output data are analyzed in this paper. A 2D multi-GPU flood code applied to a large-scale test case is used to corroborate our statements and ascertain the new challenges for the next-generation parallel water resources codes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage (CRADA Report)

NREL and Element 16 collaborated on sulfur thermal energy storage modeling using NREL’s high performance computing (HPC) resources to assist its application in industrial processes. Industrial process heat (IPH) accounts for ~70% of US manufacturing energy use and is primarily produced by fossil fuel combustion. Approximately, 1500 TWht (~60% Terawatt hour thermal) of IPH demand is in the temperature range of 100-300°C. Industrial applications in this temperature range include drying, hydrothermal processing, thermal enhanced oil recovery, food and beverage, bioethanol production, etc. Cost-effective thermal energy storage (TES) that increases the utilization of waste and renewable heat (solar, geothermal, etc.) could provide significant energy savings and reliable heat sources, decrease emissions, and increase US manufacturing competitiveness through reductions in fuel consumption. This HPC4EI project facilitated Element 16’s development of low-cost and high-impact molten sulfur TES for dispatchable IPH. The development of a high-fidelity model validated by experimental data and HPC simulations enabled the successful resolution of the complex interplay between fluid dynamics and heat transfer processes during transient operation of sulfur TES, overcoming the numerical challenges posed by the non-linear temperature-dependent physical properties of sulfur. The project helped accelerate Element 16’s molten sulfur TES product design and support its broad applications.

25 ENERGY STORAGE↗
DOE OSTI2018

High-Performance Computing and Analysis-Led Development of High Efficiency Dilute Opposed Piston Gasoline Engine

Pinnacle is developing a multicylinder 1.2 L gasoline engine for automotive applications using high-performance computing (HPC) and analysis methods. Pinnacle and Oak Ridge National Laboratory executed large-scale multidimensional combustion analyses at the Oak Ridge Leadership Computing Facility to thoroughly explore the design space. These HPC-led investigations show high fuel efficiency (~46% gross indicated efficiency) may be achieved by operating with extremely high charge dilution levels of exhaust gas recirculation (EGR) at a light load key drive cycle condition (2000 RPM, 3 bar brake mean effective pressure (BMEP)), while simultaneously attaining high levels of fuel conversion efficiency and low NO x emissions. In this extremely dilute environment, the flame propagation event is supported by turbulence and bulk in-cylinder charge motion brought about by modulation of inlet port flow. This arrangement produces a load and speed adjustable amalgamation of swirl and counter-rotating tumble which provides the turbulence required to support stable low-temperature combustion. At higher load conditions, the engine may operate at more traditional combustion modes to generate competitive power. In this work, the numerical results from these HPC simulations are presented. Finally, further HPC simulations and test validations are underway and will be reported in future publications.

42 ENGINEERING↗
DOE OSTI2022

DUNE Software and High Performance Computing

DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by modern high-performance computing facilities. In order to efficiently exploit these new architectures, particularly those with high CPU core counts and GPU accelerators, our existing software execution models require adaptation. In addition, the large size of individual units of raw data from the far detector modules pose an additional challenge somewhat unique to DUNE. Here we describe some of these problems and how we begin to solve them today with existing software frameworks and toolkits. We also describe ways we may leverage these existing software architectures to attack remaining problems going forward. This whitepaper is a contribution to the Computational Frontier of Snowmass21.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Application of High Performance Computing for Simulating Cycle-to-Cycle Variation in Dual-Fuel Combustion Engines

Interest in operational cost reduction is driving engine manufacturers to consider lower-cost fuel substitution in heavy-duty diesel engines. These dual-fuel (DF) engines could be operated either in diesel-only mode or operated with premixed natural gas (NG) ignited by a pilot flame of compression-ignited direct-injected diesel fuel. One promising application is that of large-bore, medium-speed engines such as those used in locomotives. With realistic natural gas substitution levels in the fleet of locomotives currently in service, such fuel substitution could result in billions of dollars of savings annually in the US alone. However, under certain conditions, dual-fuel operation can result in increased cycle-to-cycle variability (CCV) during combustion, resulting in variations in cylinder pressure and work extraction. In certain situations, the CCV of dual-fuel operation can be notably higher than that of diesel-only combustion under similar operating conditions. Excessive CCV can limit the NG substitution rate and operating range of a dual-fuel engine by increasing emissions and reducing engine stability, reliability and fuel efficiency via incomplete natural-gas combustion. Running multiple engine cycles in series to simulate CCV can be quite time consuming. Hence innovative modelling techniques and large computing resources are needed to investigate the factors affecting CCV in dual-fuel engines. This paper discusses the use of the High Performance Computing resource Titan, at the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, to investigate cycle-to-cycle combustion variability of a dual-fuel engine. The CONVERGE CFD software was used to simulate multiple, parallel single cycles of dual-fuel combustion with perturbed operating parameters and boundary conditions. These perturbations are imposed according to a sparse grids sampling of the parameter space. The sampling scheme chosen is similar to a design of experiments method but uses functions designed to minimize the number of samples required to achieve a desired degree of accuracy. The perturbed input parameters were connected to engine performance output over a large parameter space. Additionally, the same methodology was used to perform a set of diesel-only simulations at similar operating conditions to assess the numerical capability of capturing relatively low combustion variation. Lastly, this technique is expected to be useful to understand and predict combustion stability limits (knock and misfire) which are important for designing dual-fuel engines with improved operability and reliability.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

High Performance Computing Facility Operational Assessment 2015: Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security aspects associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2015 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction that ties the highest-ever mark set in CY 2014; the greatest number of core-hours delivered to research projects; the largest percentage of capability usage since the OLCF began tracking the metric in 2009; and success in delivering on the allocation of 60, 30, and 10% of core hours offered for the INCITE (Innovative and Novel Computational Impact on Theory and Experiment), ALCC (Advanced Scientific Computing Research Leadership Computing Challenge), and Director’s Discretionary programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations. The impact of all of these successes and more is reflected in the accomplishments of OLCF users, with publications this year in notable journals Nature, Nature Materials, Nature Chemistry, Nature Physics, Nature Climate Change, ACS Nano, Journal of the American Chemical Society, and Physical Review Letters, as well as many others. The achievements included in the 2015 OLCF Operational Assessment Report reflect first-ever or largest simulations in their communities; for example Titan enabled engineers in Los Angeles and the surrounding region to design and begin building improved critical infrastructure by enabling the highest-resolution Cybershake map for Southern California to date. The Titan system provides the largest extant heterogeneous architecture for computing and computational science. Usage is high, delivering on the promise of a system well-suited for capability simulations for science. This success is due in part to innovations in tracking and reporting the activity on the compute nodes, and using this information to further enable and optimize applications, extending and balancing workload across the entire node. The OLCF continues to invest in innovative processes, tools, and resources necessary to meet continuing user demand. The facility’s leadership in data analysis and workflows was featured at the Department of Energy (DOE) booth at SC15, for the second year in a row, highlighting work with researchers from the National Library of Medicine coupled with unique computational and data resources serving experimental and observational data across facilities. Effective operations of the OLCF play a key role in the scientific missions and accomplishments of its users. Building on the exemplary year of 2014, as shown by the 2014 Operational Assessment Report (OAR) review committee response in Appendix A, this OAR delineates the policies, procedures, and innovations implemented by the OLCF to continue delivering a multi-petaflop resource for cutting-edge research. This report covers CY 2015, which, unless otherwise specified, denotes January 1, 2015, through December 31, 2015.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

High Performance Computing Facility Operational Assessment 2016 - Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2016 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction for the third year in a row; the greatest number of core hours delivered to research projects; the largest number of research publications for the life of Titan; and success in delivering on the allocation of 60%, 30%, and 10% of core hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director’s Discretionary (DD) programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations.

97 MATHEMATICS AND COMPUTING↗