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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

FPGA-based HPC accelerators: An evaluation on performance and energy efficiency

Hardware specialization is a promising direction for the future of digital computing. Reconfigurable technologies enable hardware specialization with modest non-recurring engineering cost, but their performance and energy efficiency compared to state-of-the-art processor architectures remain an open question. In this article, we use FPGAs to evaluate the benefits of building specialized hardware for numerical kernels found in scientific applications. In order to properly evaluate performance, we not only compare Intel Arria 10 and Xilinx U280 performance against Intel Xeon, Intel Xeon Phi, and NVIDIA V100 GPUs, but we also extend the Empirical Roofline Toolkit (ERT) to FPGAs in order to assess our results in terms of the Roofline model. We show design optimization and tuning techniques for peak FPGA performance at reasonable hardware usage and power consumption. As FPGA peak performance is known to be far less than that of a GPU, we also benchmark the energy efficiency of each platform for the scientific kernels comparing against microbenchmark and technological limits. Results show that while FPGAs struggle to compete in absolute terms with GPUs on memory- and compute-intensive kernels, they require far less power and can deliver nearly the same energy efficiency.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Derived virtual devices: a secure distributed file system mechanism

This paper presents the design of derived virtual devices (DVDs). DVDs are the mechanism used by the Netstation Project to provide secure shared access to network-attached peripherals distributed in an untrusted network environment. DVDs improve Input/Output efficiency by allowing user processes to perform I/O operations directly from devices without intermediate transfer through the controlling operating system kernel. The security enforced at the device through the DVD mechanism includes resource boundary checking, user authentication, and restricted operations, e.g., read-only access. To illustrate the application of DVDs, we present the interactions between a network-attached disk and a file system designed to exploit the DVD abstraction. We further discuss third-party transfer as a mechanism intended to provide for efficient data transfer in a typical NAP environment. We show how DVDs facilitate third-party transfer, and provide the security required in a more open network environment.

VanMeter, Rodney↗
DOE OSTI2023

Using Numba for GPU acceleration of Neutron Beamline Digital Twins

Digital twins of neutron instruments using Monte Carlo ray tracing have proven to be useful in neutron data analysis and verifying instrument and sample designs. However, these simulations can become quite complex and computationally demanding with tens of billions of neutrons. In this paper, we present a GPU accelerated version of MCViNE using Python and Numba to balance user extensibility with performance. Numba is an open-source just-in-time (JIT) compiler for Python using LLVM to generate efficient machine code for CPUs and GPUs with NVIDIA CUDA. The JIT nature of Numba allowed complex instrument kernels to be generated easily. Initial simulations have shown a speedup between 200-1000x over the original CPU implementation. The performance gain with Numba enables more sophisticated data analysis and impacts neutron scattering science and instrument design.

Kendrick, Coleman↗
DOE OSTI2022

Scalable Gaussian Processes, GPyTorch Application Benchmarking, and Targeted Adaptive Design (TAD) on ThetaGPU

We aim at showcasing the scalability of Gaussian Process (GP). The naive GP implementation scales cubically with data size, which can be prohibitive, so GP has not heretofore been considered suitable for very large-scale problem settings. We take advantage of GPyTorch, a library for scalable GPs built on top of PyTorch that incorporates GPU acceleration. With GPyTorch, one can achieve nearly linear scaling with structured kernel interpolation (SKI) and constant-time predictive covariances computation with LanczOs Variance Estimates (LOVE) while preserving accuracy. We also take advantage of the computational power of ThetaGPU, a supercomputer of Argonne Leadership Computing Facility (ALCF). In addition, we implement a scalable, GPU-ready version of Targeted Adaptive Design (TAD), a GP-based data-driven algorithm that efficiently searches the control space of an advanced manufacturing experiment for settings capable of producing a required design within a specified tolerance, despite the poorly known mapping from control settings to design. We finally show our benchmarking for GPyTorch and TAD performance on CPU vs. ThetaGPU and discuss the results and implications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

An EVACS simulation with nested transactions

Documented here is the recent effort of the MISSION Kernel Team on an Extra-Vehicular Activity Control System (EVACS) simulation with nested transactions. The team has implemented the EVACS simulation along with a design for nested transactions. The EVACS simulation is a project wide aid to exploring Mission and Safety Critical (MASC) applications and their support software. For this effort it served as a trial scenario for demonstrating nested transactions and exercising the transaction support design. The EVACS simulation is a simulation of some aspects of the Extra-Vehicular Activity Control System, in particular, just the selection of communication frequencies. Its current definition is quite narrow, serving only as a starting point for prototyping purposes. (EVACS itself may be supplanted in a larger scenario of a lunar outpost with astronauts and a lunar rover.) Initially the simulation of frequency selection was written without consideration of nested transactions. This scenario was then modified to embed its processing in nested transactions. To simplify the prototyping effort, only two aspects of the general design for transaction support have been implemented: the basic architecture and state recovery. The simulation has been implemented in the programming language Smalltalk. It consists of three components: (1) a simulation support code which provides the framework for initiating, interacting and tracing the system; (2) the EVACS application code itself, including its calls upon nested transaction support; and (3) a transaction support code which implements the logic necessary for nested transactions. Each of these components deserves further description, but for now only the transaction support is discussed.

Auty, David↗
DOE OSTI2022

MICCO: An Enhanced Multi-GPU Scheduling Framework for Many-Body Correlation Functions

Calculation of many-body correlation functions is one of the critical kernels utilized in many scientific computing areas, especially in Lattice Quantum Chromodynamics (Lattice QCD). It is formalized as a sum of a large number of contraction terms each of which can be represented by a graph consisting of vertices describing quarks inside a hadron node and edges designating quark propagations at specific time intervals. Due to its computation- and memory-intensive nature, real-world physics systems (e.g., multi-meson or multi-baryon systems) explored by Lattice QCD prefer to leverage multi-GPUs. Different from general graph processing, many-body correlation function calculations show two specific features: a large number of computation-/data-intensive kernels and frequently repeated appearances of original and intermediate data. The former results in expensive memory operations such as tensor movements and evictions. The latter offers data reuse opportunities to mitigate the data-intensive nature of many-body correlation function calculations. However, existing graph-based multi-GPU schedulers cannot capture these data-centric features, thus resulting in a sub-optimal performance for many-body correlation function calculations. To address this issue, this paper presents a multi-GPU scheduling framework, MICCO, to accelerate contractions for correlation functions particularly by taking the data dimension (e.g., data reuse and data eviction) into account. This work first performs a comprehensive study on the interplay of data reuse and load balance, and designs two new concepts: local reuse pattern and reuse bound to study the opportunity of achieving the optimal trade-off between them. Based on this study, MICCO proposes a heuristic scheduling algorithm and a machine-learning-based regression model to generate the optimal setting of reuse bounds. Specifically, MICCO is integrated into a real-world Lattice QCD system, Redstar, for the first time running on multiple GPUs. The evaluation demonstrates MICCO outperforms other state-of-art works, achieving up to 2.25× speedup in synthesized datasets, and 1.49× speedup in real-world correlation functions.

Wang, Qihan↗
NASA NTRS1997

Advanced Free Flight Planner and Dispatcher's Workstation: Preliminary Design Specification

The National Aeronautics and Space Administration (NASA) has implemented the Advanced Air Transportation Technology (AATT) program to investigate future improvements to the national and international air traffic management systems. This research, as part of the AATT program, developed preliminary design requirements for an advanced Airline Operations Control (AOC) dispatcher's workstation, with emphasis on flight planning. This design will support the implementation of an experimental workstation in NASA laboratories that would emulate AOC dispatch operations. The work developed an airline flight plan data base and specified requirements for: a computer tool for generation and evaluation of free flight, user preferred trajectories (UPT); the kernel of an advanced flight planning system to be incorporated into the UPT-generation tool; and an AOC workstation to house the UPT-generation tool and to provide a real-time testing environment. A prototype for the advanced flight plan optimization kernel was developed and demonstrated. The flight planner uses dynamic programming to search a four-dimensional wind and temperature grid to identify the optimal route, altitude and speed for successive segments of a flight. An iterative process is employed in which a series of trajectories are successively refined until the LTPT is identified. The flight planner is designed to function in the current operational environment as well as in free flight. The free flight environment would enable greater flexibility in UPT selection based on alleviation of current procedural constraints. The prototype also takes advantage of advanced computer processing capabilities to implement more powerful optimization routines than would be possible with older computer systems.

Wilson, J.↗
DOE OSTI2023

BitGNN: Unlocking the Performance Potential of Binary Graph Neural Networks on GPUs

Graph Neural Networks (GNNs) have shown compelling results in many graph-based learning tasks. They are, however, time-consuming. Recent work has shown a promising direction in improving GNN speed and shrinking the size — network binarization, which binarizes network values and operations. Prior work, however, mainly focused on algorithm designs, leaving it open on how to fully materialize the performance potential. This work fills the gap by proposing techniques to best map binary GNNs and their computations to fit the nature of bit manipulations, optimizations and algorithms to maximize BSpMM kernel efficiency, and solutions to other factors influencing the end-to-end time on GPUs. Results on real-world graphs show that the proposed techniques outperform state of-the-art binary GNN implementations by 21-67× with little accuracy loss.

Chen, Jou-An↗
DOE OSTI2022

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

"Source Term Modeling for Advanced Gas Micro-Reactors"

Maintaining the safety of the public, environment, and operating personnel is the most important factor in designing, operating, maintaining, and decommissioning nuclear reactors. In recent years, there has been a growing interest in the development of micro-reactors employing TRi-structural ISOtropic (TRISO)-coated particle fuel. In gas reactors, TRISO fuel plays an important role in the safety case for high temperature reactors because of the fission product retention properties of the fuel. This ability enables the use of a functional containment strategy for the reactor where multiple barriers are used to prevent fission product release to the environment. Part of the safety analysis of these advanced reactors is the assessment of radionuclide releases under normal and accident conditions through the multiple credited safety barriers. Using conservative assumptions, a mechanistic analysis can be performed to quantify these releases that combines the probabilistic assessment of failure with analytic solutions to radionuclide transport equations. Source term modeling for TRISO fuel has been performed for previous reactor designs; however, these models are outdated, in many cases proprietary, and need updates to be applied to the current state of TRISO fuel technology and alternative gas reactor core configurations [1]. Currently, the only publicly available source term assessment for gas reactors is an expert-based Monte Carlo simulation based on the effectiveness of the fuel kernel, coating layers, and graphite block in a modular high temperature gas reactor [2]. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that could be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. The release is calculated by the diffusion of the key safety important fission products through the kernel, silicon carbide (SiC), graphite for both intact and defective TRISO particles based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system to remove fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. The model then can calculate the fission product release for any transient temperature profile and fission product releases can then be used to assess radiological dose to the workers and the public using conventional dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy (DOE) Advanced Gas Reactor (AGR) TRISO fuel development program. The model is coded in python with inputs and outputs in excel spreadsheets, as well as python plotting utilities to aid in the interpretation of the results. References: [1] INL, NGNP Mechanistic Source Term White Paper, INL-10-17997, July 2010. [2] David A. Petti, Richard R. Hobbins, Peter Lowry, Hans Gougar, “Representative Source Terms and The Influence of Reactor Attributes on Functional Containment in Modular High Temperature Gas-cooled Reactors,” Nuclear Technology, Vol. 184, p. 181-197, Nov. 2013.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone ADCD-504-28)

The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications and their role in the overall ECP ecosystem. Our FY22 March/April milestone (ADCD- 504-28) proposed to: Assess the fidelity of proxy applications compared to their respective parents in terms of kernel and I/O behavior, and predictability. Similarity techniques will be applied for quantitative comparison of proxy/parent kernel behavior. MACSio evaluation will continue and support for OpenPMD backends will be explored. The execution time predictability of proxy apps with respect to their parents will be explored through a carefully designed scaling study and code comparisons. Note that in this FY, we also have quantitative assessment milestones that are due in September and are, therefore, not included in the description above or in this report. Another report on these deliverables will be generated and submitted upon completion of these milestones. To satisfy this milestone, the following specific tasks were completed: Study the ability of MACSio to represent I/O workloads of adaptive mesh codes. Re-define the performance counter groups for contemporary Intel and IBM platforms to better match specific hardware components and to better align across platforms (make cross-platform comparison more accurate). Perform cosine similarity study based on the new performance counter groups on the Intel and IBM P9 platforms. Perform detailed analysis of performance counter data to accurately average and align the data to maintain phases across all executions and develop methods to reduce the set of collected performance counters used in cosine similarity analysis. Apply a quantitative similarity comparison between proxy and parent CPU kernels. Perform scaling studies to understand the accuracy of predictability of the parent performance using its respective proxy application. This report presents highlights of these efforts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Antiterrorist Software

In light of the escalation of terrorism, the Department of Defense spearheaded the development of new antiterrorist software for all Government agencies by issuing a Broad Agency Announcement to solicit proposals. This Government-wide competition resulted in a team that includes NASA Lewis Research Center's Computer Services Division, who will develop the graphical user interface (GUI) and test it in their usability lab. The team launched a program entitled Joint Sphere of Security (JSOS), crafted a design architecture (see the following figure), and is testing the interface. This software system has a state-ofthe- art, object-oriented architecture, with a main kernel composed of the Dynamic Information Architecture System (DIAS) developed by Argonne National Laboratory. DIAS will be used as the software "breadboard" for assembling the components of explosions, such as blast and collapse simulations.

Clark, David A.↗
DOE OSTI2024

Monte–Carlo ray-tracing studies of multiplexed prismatic graphite analyzers for the cold-neutron triple-axis spectrometer at the High Flux Isotope Reactor

A modern cold triple-axis spectrometer to study quantum condensed matter systems is planned for the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. Here, we describe the conceptual principles and design of a secondary spectrometer using a multiplexed, prismatic analyzer system relying on graphite crystals and inspired by the successful implementation of the Continuous Angle Multiple Energy Analysis (CAMEA) spectrometers at the Paul Scherrer Institute. This project is currently known as MANTA for Multi-Analyzer Neutron Triple-Axis. Here, we report Monte-Carlo ray-tracing simulations on a simple but realistic sample scattering kernel to further illustrate the prismatic analyzer concept’s workings, calibration, and performance. Then, we introduce a new statistical analysis approach based on the prismatic analyzer concept to improve the number of final energies measured on the spectrometer. We also study possible evolutions in the CAMEA design relevant for MANTA.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Postirradiation examination from separate effects irradiation testing of uranium nitride kernels and coated particles

An overview of postirradiation examination results for uranium nitride kernels and uranium nitride coated particles irradiated in the High Flux Isotope Reactor are presented. This is the first postirradiation examination of the MiniFuel irradiation vehicle that was recently developed to rapidly accumulate burnup during separate effects irradiation testing. In general, the burnup and fuel temperatures measured postirradiation were consistent with the design calculations. The burnup measured by mass spectrometry ranged from 5.9 to 10 MWd/kgU and was achieved after only 68 effective full-power days of irradiation. The dilatometric evaluation of passive silicon carbide thermometry indicated that the fuel was irradiated at temperatures ranging from 410 to 460 °C. Because the irradiation temperatures and burnup were low, the UN kernels showed minimal fission gas release that was within the range of the expected recoil (athermal) release. While it is possible to measure fuel swelling using x-ray computed tomography, the observed swelling was too small to quantify in this case. Extensive microstructural characterization of the irradiated fuel was performed in this study, and no significant irradiation induced changes were observed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SHADOW4: the popular ray tracing revived for evolving synchrotron sources in fourth-generation storage rings

We present SHADOW4, a new version of the popular ray tracing code. The SHADOW kernel has been completely rewritten in Python applying modern concepts of software engineering. A new user interface is available in the OASYS ecosystem. The new tool has been designed and implemented preparing the future needs both in computing (cloud computing, AI integration) and in the transit to fourth generation sources and beyond.

Sanchez del Rio, Manuel↗
DOE OSTI2026

Triso Analysis Tool For Predictive Source Terms

Source term modeling for TRi-structural ISOtropic (TRISO) fuel has been performed for previous reactor designs, but few are available in the open literature. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that can be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. To meet this need, the TRISO Analysis Tool for Predictive Source terms (TRISO-ATOPS) was developed. This model calculates the release of the key safety-important fission products by diffusion through the kernel, silicon carbide and graphite based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system for removing fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. From this initial condition, the model calculates the fission product release for any transient temperature profile, and the fission product releases can then be used to assess radiological dose to the workers and the public using conventional radiological dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy Advanced Gas Reactor TRISO fuel development program. The example cases in this work demonstrate the flexibility of the model

Stoyer, Benjamin [Idaho National Laboratory (INL),↗
NASA NTRS1992

The Chimera II Real-Time Operating System for advanced sensor-based control applications

Attention is given to the Chimera II Real-Time Operating System, which has been developed for advanced sensor-based control applications. The Chimera II provides a high-performance real-time kernel and a variety of IPC features. The hardware platform required to run Chimera II consists of commercially available hardware, and allows custom hardware to be easily integrated. The design allows it to be used with almost any type of VMEbus-based processors and devices. It allows radially differing hardware to be programmed using a common system, thus providing a first and necessary step towards the standardization of reconfigurable systems that results in a reduction of development time and cost.

Stewart, David B.↗
DOE OSTI2024

Efficient Parallelization of Irregular Applications on GPU Architectures

With the enlarging computation capacity of general Graphics Processing Units (GPUs), leveraging GPUs to accelerate parallel applications has become a critical topic in academia and industry. However, a wide range of irregular applications with the computation-/memory-intensive nature cannot easily achieve high GPU utilization. The challenges mainly involve the following aspects: first, data dependence leads to coarse-grained kernel and inefficient parallelism; second, heavy GPU memory usage may cause frequent memory evictions and extra overhead of I/O; third, specific computation patterns produce memory redundancies; last, workload balance and data reusability conjunctly benefit the overall performance, but there may exist a dynamic trade-off between them. Targeting these challenges, this dissertation proposes multiple optimizations to accelerate two real-world applications: many-body correlation functions to simulate nuclear physics in a large-scale scientific system; the other is the eALS-based matrix factorization recommendation system. To accelerate the calculations of many-body correlation functions, this dissertation presents three frameworks in GPU memory management and multi-GPU scheduling. Firstly, an optimized systematic GPU memory management framework, MemHC, utilizes a series of new memory reduction designs in GPU memory allocation, CPU/GPU communications, and GPU memory oversubscription. Secondly, an enhanced multi-GPU scheduling framework, MICCO, particularly by taking both data dimension (e.g., data reuse and data eviction) and computation dimension into account. MICCO designs a heuristic scheduling algorithm and a machine learning-based regression model to generate the optimal settings of a proposed new concept to manage the trade-off. Thirdly, a locality-aware multi-GPU scheduling framework. This scheduler leverages pipeline batch generation with a looking-ahead strategy by building local dependency graphs for memory transfer reduction and better data reuse, achieving up to 79.92% memory cost reduction and 1.67x speedup. To parallelize the eALS-based recommendation system, this dissertation proposes an efficient CPU/GPU heterogeneous recommendation system, HEALS. HEALS employs newly designed architecture-adaptive data formats to achieve load balance and good data locality on CPU and GPU. To mitigate the data dependence, HEALS presents a CPU/GPU collaboration model for both task parallelism and data parallelism with multiple kernel computation optimizations. In summary, this dissertation efficiently accelerates two typical irregular applications on GPUs by building four frameworks, including CPU/GPU collaboration, GPU memory management, and multi-GPU scheduling.

Wang, Qihan↗