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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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NASA NTRS1984

Application of supercomputers to computational aerodynamics

Computers are playing an increasingly important role in the field of aerodynamics such that they now serve as a major complement to wind tunnels in aerospace research and development. Factors pacing advances in computational aerodynamics are identified, including the amount of computational power required to take the next major step in the discipline. Example results obtained from the successively refined forms of the governing equations are discussed, both in the context of levels of computer power required and the degree to which they either further the frontiers of research or apply to problems of practical importance. Finally, the Numerical Aerodynamic Simulation (NAS) Program - with its 1988 target of achieving a sustained computational rate of 1 billion floating point operations per second and operating with a memory of 240 million words - is discussed in terms of its goals and its projected effect on the future of computational aerodynamics.

Peterson, V. L.↗

NASA NTRS1991

Numerical Aerodynamic Simulation Program

Report describes developments that occurred at National Aerodynamics Simulation (NAS) facility at Ames Research Center during years 1987 and 1988. Begins with description of NAS processing network, which is large network of computers. Followed by summary of early achievements of program and advanced features of network, including installation of supercomputers, installation of standard operating system and communication software on all processors, accessibility to users at remote facilities across United States, and emphasis on development of graphics workstations to display results of numerical simulation.

Bailey, F. R.↗

DOE OSTI2024

Streaming Large-Scale Microscopy Data to a Supercomputing Facility

Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers via conventional file-based methods is becoming increasingly impractical. The 4D Camera at the National Center for Electron Microscopy generates data at a nominal rate of 480 Gbit s -1 (87,000 frames s -1 ⁠), producing a 700 GB dataset in 15 s. To address the challenges associated with storing and processing such quantities of data, we developed a streaming workflow that utilizes a high-speed network to connect the 4D Camera’s data acquisition system to supercomputing nodes at the National Energy Research Scientific Computing Center, bypassing intermediate file storage entirely. In this work, we demonstrate the effectiveness of our streaming pipeline in a production setting through an hour-long experiment that generated over 10 TB of raw data, yielding high-quality datasets suitable for advanced analyses. Additionally, we compare the efficacy of this streaming workflow against the conventional file-transfer workflow by conducting a postmortem analysis on historical data from experiments performed by real users. Our findings show that the streaming workflow significantly improves data turnaround time, enables real-time decision-making, and minimizes the potential for human error by eliminating manual user interactions.

4D-STEM↗

DOE OSTI2022

Research Software Engineering at Oak Ridge National Laboratory

Research software engineers (RSE) play a vital role in scientific discoveries worldwide. They lead the core development of the applications, libraries, and tools that enable today’s supercomputers to process the vast volumes of data generated from the world’s most extensive and complicated scientific instruments and facilities. This article describes the mission, culture, and practices of RSE teams at Oak Ridge National Laboratory (ORNL), including their team dynamics and composition, work ethics, standard practices, and ever-evolving skill sets vital to pursuing scientific innovations and implementing novel ideas. We describe the lessons learned from specific activities that contribute to shaping the identity and growth of RSE roles at ORNL. Lastly, we provide our view for the near future on effective strategies for establishing, leading, and nurturing RSE teams and building a thriving community in collaboration with science stakeholders.

42 ENGINEERING↗

DOE OSTI2019

The Origins of Matter on Near-Exascale Supercomputing

This LDRD addressed one of the central questions in physics today: the lack of antimatter relative to matter in the universe. If antimatter and matter existed in equal amounts they would have annihilated into radiation and we would not exist today. DOE is funding experiments to investigate processes that could lead to lepton number violation and the resulting neutrino-less double beta decay (0nbb) signal that may be observed (lepton number is a property of elementary particles similar to electric charge and lepton number violation would explain the matter-antimatter imbalance). However, even if the 0nbb decay is detected in these experiments, the physics mechanism that violates lepton number would not be known, as there are several candidates. Determining the appropriate mechanism from the experimental data requires theoretical calculations. Theoretical effort in the field has focused on long-range 0nbb decay mechanisms associated with the exchange of light neutrinos between two nucleons. An equally important set of mechanisms are associated with the exchange of heavy particles and short-range physics, including the exchange of massive Majorana neutrinos. Calculating the event rate for 0nbb decays for candidate theories involving heavy particle exchange requires large-scale Lattice simulations of the underlying fundamental theory of Quantum Chromodynamics (QCD). We have performed these simulations on the LLNL supercomputers and have calculated the necessary matrix elements of short-range operators that arise from the exchange of heavy mediators that contribute to 0nbb decay via the leading pion exchange diagrams. Our published results can now be used as input to effective field theory calculations to calculate the 0nbb decay rate for the nuclei involved in the various experimental detectors. In the process of this work we entered the 2018 Gordon Bell Prize competition (the highest prize in scientific supercomputing) with our innovative and highly optimized code and methods and were selected as one of the six international finalists. During this effort we helped with the bring-up of the new LLNL Sierra and Lassen supercomputers by identifying hardware and software problems. Aiming towards the next step of this research, involving the sub-leading nucleon-nucleon direct vertex, we have developed algorithms and codes that will play a significant role in future Lattice QCD calculations involving nucleon-nucleon interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1989

Integrated aerodynamic-structural design of a forward-swept transport wing

The introduction of composite materials is having a profound effect on aircraft design. Since these materials permit the designer to tailor material properties to improve structural, aerodynamic and acoustic performance, they require an integrated multidisciplinary design process. Futhermore, because of the complexity of the design process, numerical optimization methods are required. The utilization of integrated multidisciplinary design procedures for improving aircraft design is not currently feasible because of software coordination problems and the enormous computational burden. Even with the expected rapid growth of supercomputers and parallel architectures, these tasks will not be practical without the development of efficient methods for cross-disciplinary sensitivities and efficient optimization procedures. The present research is part of an on-going effort which is focused on the processes of simultaneous aerodynamic and structural wing design as a prototype for design integration. A sequence of integrated wing design procedures has been developed in order to investigate various aspects of the design process.

Haftka, Raphael T.↗

DOE OSTI2024

Toward Automated Detection of Portability Bugs in Kokkos Parallel Programs

Performance-portable programming frameworks provide abstractions for parallel execution to allow easily porting an application to multiple backend programming models, such as CUDA, HIP, and OpenMP. However, programs may still have portability bugs that manifest only on specific backends. Traditional testing is ineffective in discovering these bugs, as it would require concrete execution on all supported hardware configurations for a potentially infinite set of inputs. To mitigate this issue, we focused on a specific programming framework, Kokkos, and identified several categories of common portability bugs. We then developed Klokkos, a static analysis approach based on symbolic execution that can run on commodity hardware, before execution on supercomputers. As a proof-of-concept, we ran Klokkos on examples encoding the identified bugs. Our results show that Klokkos is effective, efficient, and precise: it detected all the considered bugs, quickly, and without any false positives. Although preliminary, our results motivate further research and development in this direction.

Kale, Vivek↗

DOE OSTI2021

Translational research in the MPICH project

The MPICH project is an example of translational research in computer science before that term was well known or even coined. The project began in 1992 as an effort to develop a portable, high-performance implementation of the emerging Message-Passing Interface (MPI) Standard. It has enabled the widespread adoption of MPI as a way to write scalable parallel applications on systems of all sizes including upcoming exascale supercomputers. In this paper, we describe how the translational research process was used in MPICH, how that led to its success, the challenges encountered and lessons learned, and how the process could be applied to other similar projects.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

ExaFEL: extreme-scale real-time data processing for X-ray free electron laser science

ExaFEL is an HPC-capable X-ray Free Electron Laser (XFEL) data analysis software suite for both Serial Femtosecond Crystallography (SFX) and Single Particle Imaging (SPI) developed in collaboration with the Linac Coherent Lightsource (LCLS), Lawrence Berkeley National Laboratory (LBNL) and Los Alamos National Laboratory. ExaFEL supports real-time data analysis via a cross-facility workflow spanning LCLS and HPC centers such as NERSC and OLCF. Our work therefore constitutes initial path-finding for the US Department of Energy's (DOE) Integrated Research Infrastructure (IRI) program. We present the ExaFEL team's 7 years of experience in developing real-time XFEL data analysis software for the DOE's exascale supercomputers. We present our experiences and lessons learned with the Perlmutter and Frontier supercomputers. Furthermore we outline essential data center services (and the implications for institutional policy) required for real-time data analysis. Finally we summarize our software and performance engineering approaches and our experiences with NERSC's Perlmutter and OLCF's Frontier systems. This work is intended to be a practical blueprint for similar efforts in integrating exascale compute resources into other cross-facility workflows.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Outer rim simulation: Predicting matter distribution in a universe with billions of galaxies

Anticipating the completion of the Large Synoptic Survey Telescope (LSST) in 2021 in Chile, Argonne scientists have created one of the largest simulations ever produced, the Outer Rim simulation. As it follows the evolution of matter distribution in the universe and the influence of dark energy, the Outer Rim simulation helps researchers make predictions on what they should expect to see when pointing a next generation telescope like the LSST in its direction. Argonne is helping to develop advanced supercomputing and data analysis tools in support of the LSST.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1995

CFD Research, Parallel Computation and Aerodynamic Optimization

During the last five years, CFD has matured substantially. Pure CFD research remains to be done, but much of the focus has shifted to integration of CFD into the design process. The work under these cooperative agreements reflects this trend. The recent work, and work which is planned, is designed to enhance the competitiveness of the US aerospace industry. CFD and optimization approaches are being developed and tested, so that the industry can better choose which methods to adopt in their design processes. The range of computer architectures has been dramatically broadened, as the assumption that only huge vector supercomputers could be useful has faded. Today, researchers and industry can trade off time, cost, and availability, choosing vector supercomputers, scalable parallel architectures, networked workstations, or heterogenous combinations of these to complete required computations efficiently.

Ryan, James S.↗

DOE OSTI2017

Introducing Argonne’s Theta Supercomputer

Theta, the Argonne Leadership Computing Facility’s (ALCF) new Intel-Cray supercomputer, is officially open to the research community. Theta’s massively parallel, many-core architecture puts the ALCF on the path to Aurora, the facility’s future Intel-Cray system. Capable of nearly 10 quadrillion calculations per second, Theta enables researchers to break new ground in scientific investigations that range from modeling the inner workings of the brain to developing new materials for renewable energy applications.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Tensoral: A system for post-processing turbulence simulation data

Many computer simulations in engineering and science -- and especially in computational fluid dynamics (CFD) -- produce huge quantities of numerical data. These data are often so large as to make even relatively simple post-processing of this data unwieldy. The data, once computed and quality-assured, is most likely analyzed by only a few people. As a result, much useful numerical data is under-utilized. Since future state-of-the-art simulations will produce even larger datasets, will use more complex flow geometries, and will be performed on more complex supercomputers, data management issues will become increasingly cumbersome. My goal is to provide software which will automate the present and future task of managing and post-processing large turbulence datasets. My research has focused on the development of these software tools -- specifically, through the development of a very high-level language called 'Tensoral'. The ultimate goal of Tensoral is to convert high-level mathematical expressions (tensor algebra, calculus, and statistics) into efficient low-level programs which numerically calculate these expressions given simulation datasets. This approach to the database and post-processing problem has several advantages. Using Tensoral the numerical and data management details of a simulation are shielded from the concerns of the end user. This shielding is carried out without sacrificing post-processor efficiency and robustness. Another advantage of Tensoral is that its very high-level nature lends itself to portability across a wide variety of computing (and supercomputing) platforms. This is especially important considering the rapidity of changes in supercomputing hardware.

Dresselhaus, Eliot↗

DOE OSTI2016

Using Supercomputers to Probe the Early Universe

For decades physicists have been trying to decipher the first moments after the Big Bang. Using very large telescopes, for example, scientists scan the skies and look at how fast galaxies move. Satellites study the relic radiation left from the Big Bang, called the cosmic microwave background radiation. And finally, particle colliders, like the Large Hadron Collider at CERN, allow researchers to smash protons together and analyze the debris left behind by such collisions. Physicists at Los Alamos National Laboratory, however, are taking a different approach: they are using computers. In collaboration with colleagues at University of California San Diego, the Los Alamos researchers developed a computer code, called BURST, that can simulate conditions during the first few minutes of cosmological evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Performance Analysis, Modeling and Scaling of HPC Applications and Tools

E cient use of supercomputers at DOE centers is vital for maximizing system throughput, mini- mizing energy costs and enabling science breakthroughs faster. This requires complementary e orts along several directions to optimize the performance of scienti c simulation codes and the under- lying runtimes and software stacks. This in turn requires providing scalable performance analysis tools and modeling techniques that can provide feedback to physicists and computer scientists developing the simulation codes and runtimes respectively. The PAMS project is using time allocations on supercomputers at ALCF, NERSC and OLCF to further the goals described above by performing research along the following fronts: 1. Scaling Study of HPC applications; 2. Evaluation of Programming Models; 3. Hardening of Performance Tools; 4. Performance Modeling of Irregular Codes; and 5. Statistical Analysis of Historical Performance Data. We are a team of computer and computational scientists funded by both DOE/NNSA and DOE/ ASCR programs such as ECRP, XStack (Traleika Glacier, PIPER), ExaOSR (ARGO), SDMAV II (MONA) and PSAAP II (XPACC). This allocation will enable us to study big data issues when analyzing performance on leadership computing class systems and to assist the HPC community in making the most e ective use of these resources.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Revolutionizing Investigation of Unsteady Flow with Pressure-Sensitive Paint

NASA and its Stakeholders are developing increasingly advanced aerospace vehicles. Performing a ground test is a standard method to quantify the loads a vehicle will experience during flight. In order to efficiently design these new advanced aerospace vehicles, more advanced tools are required. A new state-of-the-art technique to measure unsteady aerodynamics is currently being developed using pressure-sensitive paint (PSP), high-speed cameras, and advanced image processing methods. This new technique is capable of acquiring fluctuating pressures up to 20 kHz with continuous spatial resolution which enables direct calculation of unsteady loads. To successfully develop a new capability, a systems perspective must be taken. Recently, a connection was established between the Unitary Plan Wind Tunnel and the NASA Advanced Supercomputer, both located at NASA Ames Research Center. The rapid transfer, processing, and display of high-speed PSP data from the wind tunnel demonstrated the ability to make real-time decisions in order to decrease design cycle time.

PSP↗

DOE OSTI2016

Virtual Special Issue on Catalysis at the U.S. Department of Energy’s National Laboratories

Catalysis research at the U.S. Department of Energy's (DOE's) National Laboratories covers a wide range of research topics in heterogeneous catalysis, homogeneous/molecular catalysis, biocatalysis, electrocatalysis, and surface science. Since much of the work at National Laboratories is funded by DOE, the research is largely focused on addressing DOE's mission to ensure America's security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. The catalysis research carried out at the DOE National Laboratories ranges from very fundamental catalysis science, funded by DOE's Office of Basic Energy Sciences (BES), to applied research and development (R&D) in areas such as biomass conversion to fuels and chemicals, fuel cells, and vehicle emission control with primary funding from DOE's Office of Energy Efficiency and Renewable Energy.

09 BIOMASS FUELS↗

DOE OSTI2023

Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute

At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes are best suited for the types of models we see in neuroscience. In 2015, a Frontiers Research Topic “Python in neuroscience” by Muller et al. triggered and documented a revolution in the neuroscience community, namely in the usage of the scripting language Python as a common language for interfacing with simulation codes and connecting between applications. The review by Einevoll et al. documented that simulation tools have since further matured and become reliable research instruments used by many scientific groups for their respective questions. Open source and community standard simulators today allow research groups to focus on their scientific questions and leave the details of the computational work to the community of simulator developers. A parallel development has occurred, which has been barely visible in neuroscientific circles beyond the community of simulator developers: Supercomputers used for large and complex scientific calculations have increased their performance from ~10 TeraFLOPS (10 13 floating point operations per second) in the early 2000s to above 1 ExaFLOPS (10 18 floating point operations per second) in the year 2022. This represents a 100,000-fold increase in our computational capabilities, or almost 17 doublings of computational capability in 22 years. Moore's law (the observation that it is economically viable to double the number of transistors in an integrated circuit every other 18–24 months) explains a part of this; our ability and willingness to build and operate physically larger computers, explains another part. It should be clear, however, that such a technological advancement requires software adaptations and under the hood, simulators had to reinvent themselves and change substantially to embrace this technological opportunity. It actually is quite remarkable that—apart from the change in semantics for the parallelization—this has mostly happened without the users knowing. The current Research Topic was motivated by the wish to assemble an update on the state of neuroscientific software (mostly simulators) in 2022, to assess whether we can see more clearly which scientific questions can (or cannot) be asked due to our increased capability of simulation, and also to anticipate whether and for how long we can expect this increase of computational capabilities to continue.

biophysically detailed models↗