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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 NTRS1987

Optical communication with semiconductor laser diodes

A 25 megabit/sec direct detection optical communication system that used Q=4 PPM signalling was constructed and its performance measured under laboratory conditions. The system used a single-mode AlGaAs laser diode transmitter and low noise silicon avalanche photodiode (APD) photodetector. Comparison of measured performance with the theoretical revealed that modeling the APD output as a Gaussian process under conditions of negligible background radiation and low (less than 10 to the -12 power A) APD bulk leakage currents leads to substantial underestimates of optimal APD gain to use and overestimates of system bit error probability. A procedure is given to numerically compute system performance which uses the more accurate Webb's Approximation of the exact Conradi distribution for the APD ouput signal that does not require excessive amounts of computer time (a few minutes of VAX 8600 CPU time per system operating point). Examples are given which illustrate the breakdown of the Gaussian approximation in assessing system performance. This system achieved a bit error probability of 10 to the -6 power at a received signal energy corresponding to an average of 60 absorbed photons/bit and optimal APD gain of 700.

Davidson, F.↗

NASA NTRS1998

Parallelization of NAS Benchmarks for Shared Memory Multiprocessors

This paper presents our experiences of parallelizing the sequential implementation of NAS benchmarks using compiler directives on SGI Origin2000 distributed shared memory (DSM) system. Porting existing applications to new high performance parallel and distributed computing platforms is a challenging task. Ideally, a user develops a sequential version of the application, leaving the task of porting to new generations of high performance computing systems to parallelization tools and compilers. Due to the simplicity of programming shared-memory multiprocessors, compiler developers have provided various facilities to allow the users to exploit parallelism. Native compilers on SGI Origin2000 support multiprocessing directives to allow users to exploit loop-level parallelism in their programs. Additionally, supporting tools can accomplish this process automatically and present the results of parallelization to the users. We experimented with these compiler directives and supporting tools by parallelizing sequential implementation of NAS benchmarks. Results reported in this paper indicate that with minimal effort, the performance gain is comparable with the hand-parallelized, carefully optimized, message-passing implementations of the same benchmarks.

Waheed, Abdul↗

NASA NTRSDate not supplied

Implicit Thermochemical Nonequilibrium Flow Simulations on Unstructured Grids using GPUs

Thermochemical nonequilibrium flow simulation capabilities have been previously implemented, verified, and validated for central processing unit (CPU) systems in NASA’s unstructured-grid computational fluid dynamics solver FUN3D. Many exascale-class high-performance computing systems will rely on graphics processing unit (GPU) architectures for high throughput and energy efficiency; thus, CPU-based scientific computing software unable to effectively utilize these systems must be updated. In this work, we present a CUDA C++ implementation of FUN3D’s thermochemical nonequilibrium flow simulation capabilities targeting NVIDIA Tesla GPUs. An overview of the porting and optimization strategy is described and performance comparisons with other recent architectures are presented. Scaling to thousands of GPUs is demonstrated, yielding computational performance equivalent to that of several million CPU cores. The implementation enables efficient, high-fidelity, scale-resolving simulations of thermochemical nonequilibrium flows for many applications including atmospheric entry, hypersonics, and combustion.

GPU↗

DOE OSTI2024

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

azure↗

DOE OSTI2026

A Scaling Study for Incompressible Multispecies Solver in Vertex-CFD

Multispecies incompressible flows occur widely in engineering and environmental applications, such as chemical reactors, fuel cells, ocean mixing, and biomedical systems. However, accurately resolving the complex transport and mixing phenomena associated with multiple interacting species remains computationally challenging, especially for large-scale problems. In this study, we present a robust, high-performance computing--enabled multispecies incompressible Navier–Stokes solver integrated within the Vertex-CFD framework. Our solver employs a fully coupled, implicit, finite element--based formulation that accurately captures the advection, diffusion, and interaction of multiple species in incompressible flows by leveraging the Kokkos library for parallel computing to achieve high computational efficiency. For pressure coupling, the entropically damped artificial compressibility method is utilized. We validated the solver against canonical test cases, including multispecies advection, diffusion, and Bateman systems; the results demonstrate second- and third-order spatial accuracy and consistent convergence. Additionally, we demonstrated the strong and weak scaling study results obtained on the leadership-class high-performance computing system, Frontier at Oak Ridge National Laboratory.

Oz, Furkan [ORNL] (ORCID:0000000265831724)↗

DOE OSTI2024

Computing with a Chemical Reservoir

Contemporary computation is expensive, with large language models and artificial intelligence becoming more common in daily life. However, high-performance computing is reaching the limits in speed and energy expenditure, and domain science requires ever-increasing computational capacity, with simulations and data analysis pipelines ever-growing in complexity. As we progress towards post-exascale computation, with the associated high energy costs, new methods of energy-conscious computation are required. Novel analog and hybrid digital-analog systems can overcome these challenges, and chemical reactions offer a promising avenue. Computers based on chemistry can provide compact desktop devices with immense computational power. These devices are readily scalable by considering greater reaction systems or vessels, meeting the high-performance requirements for scientific workflows. In this article, we present ChemComp, a compilation pipeline for the conversion of ordinary differential equations into implementable chemical reactions. We then demonstrate the solving capabilities of ChemComp by emulating a potential chemical reservoir device. We leverage the multi-layer intermediate representation (MLIR) compiler framework to implement an expressive chemical reaction abstraction and propose a path for chemical reaction networks (CRNs) to represent mathematical problems effectively. Combined, we demonstrate a potential workflow that can harness chemistry’s computing power to create energy-efficient, high-performance computation systems for contemporary computing needs.

artificial intelligence↗

NASA NTRS2006

User-Defined Data Distributions in High-Level Programming Languages

One of the characteristic features of today s high performance computing systems is a physically distributed memory. Efficient management of locality is essential for meeting key performance requirements for these architectures. The standard technique for dealing with this issue has involved the extension of traditional sequential programming languages with explicit message passing, in the context of a processor-centric view of parallel computation. This has resulted in complex and error-prone assembly-style codes in which algorithms and communication are inextricably interwoven. This paper presents a high-level approach to the design and implementation of data distributions. Our work is motivated by the need to improve the current parallel programming methodology by introducing a paradigm supporting the development of efficient and reusable parallel code. This approach is currently being implemented in the context of a new programming language called Chapel, which is designed in the HPCS project Cascade.

physically distributed memory↗

NASA NTRS1994

Applications of massively parallel computers in telemetry processing

Telemetry processing refers to the reconstruction of full resolution raw instrumentation data with artifacts, of space and ground recording and transmission, removed. Being the first processing phase of satellite data, this process is also referred to as level-zero processing. This study is aimed at investigating the use of massively parallel computing technology in providing level-zero processing to spaceflights that adhere to the recommendations of the Consultative Committee on Space Data Systems (CCSDS). The workload characteristics, of level-zero processing, are used to identify processing requirements in high-performance computing systems. An example of level-zero functions on a SIMD MPP, such as the MasPar, is discussed. The requirements in this paper are based in part on the Earth Observing System (EOS) Data and Operation System (EDOS).

El-Ghazawi, Tarek A.↗

DOE OSTI2026

panhandle

A project to provide user activity monitoring for High Performance Computing systems and clusters. The goal is to provide effective user activity monitoring with minimal performance impact on the host running this service.

McGee, David [@LANL @USMC @DoD]↗

NASA NTRS2001

Performance of the Wavelet Decomposition on Massively Parallel Architectures

Traditionally, Fourier Transforms have been utilized for performing signal analysis and representation. But although it is straightforward to reconstruct a signal from its Fourier transform, no local description of the signal is included in its Fourier representation. To alleviate this problem, Windowed Fourier transforms and then wavelet transforms have been introduced, and it has been proven that wavelets give a better localization than traditional Fourier transforms, as well as a better division of the time- or space-frequency plane than Windowed Fourier transforms. Because of these properties and after the development of several fast algorithms for computing the wavelet representation of any signal, in particular the Multi-Resolution Analysis (MRA) developed by Mallat, wavelet transforms have increasingly been applied to signal analysis problems, especially real-life problems, in which speed is critical. In this paper we present and compare efficient wavelet decomposition algorithms on different parallel architectures. We report and analyze experimental measurements, using NASA remotely sensed images. Results show that our algorithms achieve significant performance gains on current high performance parallel systems, and meet scientific applications and multimedia requirements. The extensive performance measurements collected over a number of high-performance computer systems have revealed important architectural characteristics of these systems, in relation to the processing demands of the wavelet decomposition of digital images.

El-Ghazawi, Tarek A.↗

NASA NTRS1991

Enhancing aeropropulsion research with high-speed interactive computing

NASA-Lewis has committed to a long range goal of creating a numerical test cell for aeropropulsion research and development. Efforts are underway to develop a first generation Numerical Propulsion System Simulation (NPSS). The NPSS will provide a unique capability to numerically simulate advanced propulsion systems from nose to tail. Two essential ingredients to the NPSS are: (1) experimentally validated Computational Fluid Dynamics (CFD) codes; and (2) high performing computing systems (hardware and software) that will permit those codes to be used efficiently. To this end, NASA-Lewis is using high speed, interactive computing as a means for achieving Integrated CFD and Experiments (ICE). The development is described of a prototype ICE system for multistage compressor flow physics research.

Szuch, John R.↗

NASA NTRS1991

Enhancing aeropropulsion research with high-speed interactive computing

Szuch, John R.↗

NASA NTRS1981

RAMP - A fault tolerant distributed microcomputer structure for aircraft navigation and control

Design methodologies for realizing future high authority autoflight control systems are being investigated, taking into account also the study of distributed microcomputer architectures. Attention is given to the redundant asynchronous microprocessor (RAMP) structure. RAMP comprises a connected network of microcomputers which has as input command and sensor information, and which generates servo information to drive actuators, and thrust linkages. Tolerance to hardware failures is achieved by static redundancy. Results of a failed microcomputer are simply rejected. This is done in lieu of dynamic redundancy wherein the distributed computer system performs real time fault detection and reconfiguration of the system. Attention is given to the RAMP network structure and operation, flight control with parallel asynchronous computers, and intermittent fault tolerance.

Dunn, W. R.↗

NASA NTRS1995

Experimental Evaluation and Workload Characterization for High-Performance Computer Architectures

This research is conducted in the context of the Joint NSF/NASA Initiative on Evaluation (JNNIE). JNNIE is an inter-agency research program that goes beyond typical.bencbking to provide and in-depth evaluations and understanding of the factors that limit the scalability of high-performance computing systems. Many NSF and NASA centers have participated in the effort. Our research effort was an integral part of implementing JNNIE in the NASA ESS grand challenge applications context. Our research work under this program was composed of three distinct, but related activities. They include the evaluation of NASA ESS high- performance computing testbeds using the wavelet decomposition application; evaluation of NASA ESS testbeds using astrophysical simulation applications; and developing an experimental model for workload characterization for understanding workload requirements. In this report, we provide a summary of findings that covers all three parts, a list of the publications that resulted from this effort, and three appendices with the details of each of the studies using a key publication developed under the respective work.

El-Ghazawi, Tarek A.↗

NASA NTRS2021

Characterization Study of TestBed Infrastructure Performance in a Distributed Simulation Environment: Baseline Analysis

Characterization of the performance of Air Traffic Management Exploration (ATM-X) TestBed integration environment has been investigated and documented for one system configuration for progressively increasing traffic. Several statistical parameters were used to assess the performance of the TestBed distributed system such as mean, standard deviation, skewness, and kurtosis of latency, and update rate for aircraft state messages that are transmitted through the simulated system under investigation. It is necessary to assess the performance characteristics of distributed systems in terms of the indicated statistical parameters mentioned above. It is critical to verify the system performance with respect to a researcher’s required system performance. Computer host specifications are documented in terms of Central Processing Unit (CPU) clock speed and core count. Transmission Control Protocol/ Internet Protocol (TCP/IP) message protocol was used for data transmission. The system network topology also contributes to the latency and update rate variations from the one imposed by the data source. The motivation for selecting the TestBed infrastructure as the focus of this study can be attributed to the number of services and capabilities it provides that help simplify the process of preparing and conducting a simulation. These capabilities include an easy to use GUI for simulation configuration, access to TestBed library by the end-user of other simulation software components, a modular adapter paradigm that allows simple connectivity of external software to TestBed, connectivity with other simulation laboratories, and a Software Development Kit (SDK) for quicker development. Two types of traffic generators, Air Traffic Generator (ATG) and Multi Aircraft Control System (MACS) were used to generate messages that were injected into the TestBed distributed environment. Eight different air traffic scenarios with progressively increasing loads were generated for each air traffic simulator. The corresponding air traffic loads between the two simulators had an identical number of aircraft per scenario, but different flight plans. It was observed that the performance of MACS degraded for air traffic scenarios containing more than 200 aircraft (37.5 KB/s nominal throughput). However, ATG performed adequately under all tested air traffic loads up to 1200 aircraft (225. KB/s nominal throughput). The tests show that MACS exhibits better latency performance with smaller aircraft loads when compared to ATG. The tests also show that the TestBed infrastructure successfully transmits 1200 aircraft without significant degradation of its performance. From the latency trends for both MACS and ATG, it is clear that as aircraft load increases, the latency in the system increases as well as its standard deviation. Likewise, the trends for the update data rate for both MACS and ATG show that as the aircraft load increases, so does the standard deviation and mean of the update rates which can be attributed to the performance of MACS and ATG applications. The analysis of the results of this study have proven that the overall system performance is dependent on the individual performance of each system component that is connected to TestBed, which subsequently propagates into the system. All TestBed characterization tests were conducted in SimLabs at NASA Ames Research Center in November 2019. This study addresses the need for a baseline TestBed characterization, and the results will serve as a reference for more complex simulation systems.

Air Traffic Management simulations↗

DOE OSTI2026

A scalable framework for efficient coupling of thermal and microstructural simulations in additive manufacturing

Predicting microstructure evolution in metal additive manufacturing (AM) is important for process optimization, but spatiotemporal scale disparities between thermal transport and microstructure evolution create significant challenges for efficient data transfer between simulation codes. To address this, we present Stork, a scalable framework for coupling thermal and microstructural simulations. Stork uses a sparse data representation to identify and store active solidification sub-volumes, enabling highly parallel quad-linear interpolation from coarse thermal grids to fine microstructure grids without large intermediate storage. We demonstrate the framework by coupling the semi-analytic heat transfer code 3DThesis with the time-parallel cellular automata code Toucan. This approach achieves over two orders of magnitude reduction in data generation time and file size compared to prior workflows. Numerical studies show that quad-linear interpolation preserves grain morphology and crystallographic texture in laser powder bed fusion (LPBF) simulations for coarsening ratios up to 16. Overall, Stork provides a scalable pathway for high-throughput, component-scale AM simulations on modern high-performance computing systems.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Power-Capping Metric Evaluation for Improving Energy Efficiency in HPC Applications

With high-performance computing systems now running at exascale, optimizing power-scaling management and resource utilization has become more critical than ever. This paper explores runtime power-capping optimizations that leverage integrated CPU-GPU power management on architectures like the NVIDIA GH200 superchip. We evaluate energy-performance metrics that account for simultaneous CPU and GPU power-capping effects by using two complementary approaches: speedup-energy-delay and a Euclidean distance-based multi-objective optimization method. By targeting a mostly compute-bound exascale science application, the Locally Self-Consistent Multiple Scattering (LSMS), we explore challenging scenarios to identify potential opportunities for energy savings in exascale applications, and we recognize that even modest reductions in energy consumption can have significant overall impacts. Our results highlight how GPU task-specific dynamic power-cap adjustments combined with integrated CPU-GPU power steering can improve the energy utilization of certain GPU tasks, thereby laying the groundwork for future adaptive optimization strategies.

Patrou, Maria [ORNL] (ORCID:0000000339754638)↗

NASA NTRS2016

Overview of the NASA Glenn Flux Reconstruction Based High-Order Unstructured Grid Code

A computational fluid dynamics code based on the flux reconstruction (FR) method is currently being developed at NASA Glenn Research Center to ultimately provide a large- eddy simulation capability that is both accurate and efficient for complex aeropropulsion flows. The FR approach offers a simple and efficient method that is easy to implement and accurate to an arbitrary order on common grid cell geometries. The governing compressible Navier-Stokes equations are discretized in time using various explicit Runge-Kutta schemes, with the default being the 3-stage/3rd-order strong stability preserving scheme. The code is written in modern Fortran (i.e., Fortran 2008) and parallelization is attained through MPI for execution on distributed-memory high-performance computing systems. An h- refinement study of the isentropic Euler vortex problem is able to empirically demonstrate the capability of the FR method to achieve super-accuracy for inviscid flows. Additionally, the code is applied to the Taylor-Green vortex problem, performing numerous implicit large-eddy simulations across a range of grid resolutions and solution orders. The solution found by a pseudo-spectral code is commonly used as a reference solution to this problem, and the FR code is able to reproduce this solution using approximately the same grid resolution. Finally, an examination of the code's performance demonstrates good parallel scaling, as well as an implementation of the FR method with a computational cost/degree- of-freedom/time-step that is essentially independent of the solution order of accuracy for structured geometries.

High-Order Methods↗