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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

MO-AB-204-02: IHE RAD [Health care]

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-AB-204-03: Profile Development and IHE Process

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Enabling Autonomous Electron Microscopy for Networked Computation and Steering

Advanced electron microscopy workflows require an ecosystem of microscope instruments and computing systems possibly located at different sites to conduct remotely steered and automated experiments. Current workflow executions involve manual operations for steering and measurement tasks, which are typically performed from control workstations co-located with microscopes; consequently, their operational tempo and effectiveness are limited. We propose an approach based on separate data and control channels for such an ecosystem of Scanning Transmission Electron Microscopes (STEM) and computing systems, for which no general solutions presently exist, unlike the neutron and light source instruments. We demonstrate automated measurement transfers and remote steering of Nion STEM physical instruments over site networks. We propose a Virtual Infrastructure Twin (VIT) of this ecosystem, which is used to develop and test our steering software modules without requiring access to the physical instrument infrastructure. Additionally, we develop a VIT for a multiple laboratory scenario, which illustrates the applicability of this approach to ecosystems connected over wide-area networks, for the development and testing of software modules and their later field deployment.

Al Najjar, Anees↗
DOE OSTI2016

SU-G-IeP4-14: Prostate Brachytherapy Activity Measurement and Source Localization by Using a Dual Photon Emission Computed Tomography System: A Feasibility Study

Purpose: To monitor the activity distribution and needle position during and after implantation in operating rooms. Methods: Simulation studies were conducted to assess the feasibility of measurement activity distribution and seed localization using the DuPECT system. The system consists of a LaBr3-based probe and planar detection heads, a collimation system, and a coincidence circuit. The two heads can be manipulated independently. Simplified Yb-169 brachytherapy seeds were used. A water-filled cylindrical phantom with a 40-mm diameter and 40-mm length was used to model a simplified prostate of the Asian man. Two simplified seeds were placed at a radial distance of 10 mm and tangential distance of 10 mm from the center of the phantom. The probe head was arranged perpendicular to the planar head. Results of various imaging durations were analyzed and the accuracy of the seed localization was assessed by calculating the centroid of the seed. Results: The reconstructed images indicate that the DuPECT can measure the activity distribution and locate the seeds dwelt in different positions intraoperatively. The calculated centroid on average turned out to be accurate within the pixel size of 0.5 mm. The two sources were identified when the duration is longer than 15 s. The sensitivity measured in water was merely 0.07 cps/MBq. Conclusion: Preliminary results show that the measurement of the activity distribution and seed localization are feasible using the DuPECT system intraoperatively. It indicates the DuPECT system has potential to be an approach for dose-distribution-validation. The efficacy of acvtivity distribution measurement and source localization using the DuPECT system will evaluated in more realistic phantom studies (e.g., various attenuation materials and greater number of seeds) in the future investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Iterative Importance Sampling Algorithms for Parameter Estimation

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is a challenging task. Several sampling algorithms have been proposed over the past years that take an iterative approach to constructing a proposal distribution. We investigate the applicability of such algorithms by applying them to two realistic and challenging test problems, one in subsurface flow, and one in combustion modeling. More specifically, we implement importance sampling algorithms that iterate over the mean and covariance matrix of Gaussian or multivariate t-proposal distributions. Our implementation leverages massively parallel computers, and we present strategies to initialize the iterations using “coarse” MCMC runs or Gaussian mixture models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

GPU Acceleration of Large-Scale Full-Frequency GW Calculations

Many-body perturbation theory is a powerful method to simulate electronic excitations in molecules and materials starting from the output of density functional theory calculations. By implementing the theory efficiently so as to run at scale on the latest leadership high-performance computing systems it is possible to extend the scope of GW calculations. Here, we present a GPU acceleration study of the full-frequency GW method as implemented in the WEST code. Excellent performance is achieved through the use of (i) optimized GPU libraries, e.g., cuFFT and cuBLAS, (ii) a hierarchical parallelization strategy that minimizes CPU-CPU, CPU-GPU, and GPU-GPU data transfer operations, (iii) nonblocking MPI communications that overlap with GPU computations, and (iv) mixed precision in selected portions of the code. A series of performance benchmarks has been carried out on leadership high-performance computing systems, showing a substantial speedup of the GPU-accelerated version of WEST with respect to its CPU version. Good strong and weak scaling is demonstrated using up to 25 920 GPUs. Finally, we showcase the capability of the GPU version of WEST for large-scale, full-frequency GW calculations of realistic systems, e.g., a nanostructure, an interface, and a defect, comprising up to 10 368 valence electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A fully non-linear multi-species Fokker–Planck–Landau collision operator for simulation of fusion plasma

Fusion edge plasmas can be far from thermal equilibrium and require the use of a non-linear collision operator for accurate numerical simulations. In this article, the non-linear single-species Fokker–Planck–Landau collision operator developed by Yoon and Chang (2014) [9] is generalized to include multiple particle species. The finite volume discretization used in this work naturally yields exact conservation of mass, momentum, and energy. The implementation of this new non-linear Fokker–Planck–Landau operator in the gyrokinetic particle-in-cell codes XGC1 and XGCa is described and results of a verification study are discussed. Finally, the numerical techniques that make our non-linear collision operator viable on high-performance computing systems are described, including specialized load balancing algorithms and nested OpenMP parallelization. The collision operator's good weak and strong scaling behavior are shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Fuzzy cyber detection pattern matching

Mechanisms for identifying a pattern of computing resource activity of interest, in activity data characterizing activities of computer system elements, are provided. A temporal graph of the activity data is generated and a filter is applied to the temporal graph to generate one or more first vector representations, each characterizing nodes and edges within a moving window defined by the filter. The filter is applied to a pattern graph representing a pattern of entities and events indicative of the pattern of interest, to generate a second vector representation. The second vector representation is compared to the one or more first vector representations to identify one or more nearby vectors, and one or more corresponding subgraph instances are output to an intelligence console computing system as inexact matches of the temporal graph.

Shu, Xiaokui↗
DOE OSTI2019

Use cases of lossy compression for floating-point data in scientific data sets

Architectural and technological trends of systems used for scientific computing call for a significant reduction of scientific data sets that are composed mainly of floating-point data. Here, this article surveys and presents experimental results of currently identified use cases of generic lossy compression to address the different limitations of scientific computing systems. The article shows from a collection of experiments run on parallel systems of a leadership facility that lossy data compression not only can reduce the footprint of scientific data sets on storage but also can reduce I/O and checkpoint/restart times, accelerate computation, and even allow significantly larger problems to be run than without lossy compression. In conclusion, these results suggest that lossy compression will become an important technology in many aspects of high performance scientific computing. Because the constraints for each use case are different and often conflicting, this collection of results also indicates the need for more specialization of the compression pipelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Method to Compute CT System MTF

The modulation transfer function (MTF) is the normalized spatial frequency representation of the point spread function (PSF) of the system. Point objects are hard to come by, so typically the PSF is determined by taking the numerical derivative of the system's response to an edge. This is the method we use, and we typically use it with cylindrical objects. Given a cylindrical object, we first put an active contour around it, as shown in Figure 1(a). The active contour lets us know where the boundary of the test object is. We next set a threshold (Figure 1(b)) and determine the center of mass of the above threshold voxels. For the purposes of determining the center of mass, each voxel is weighted identically (not by voxel value).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Reducing the stochasticity of crystal nucleation to enable subnanosecond memory writing

Operation speed is a key challenge in phase-change random-access memory (PCRAM) technology, especially for achieving subnanosecond high-speed cache memory. Commercialized PCRAM products are limited by the tens of nanoseconds writing speed, originating from the stochastic crystal nucleation during the crystallization of amorphous germanium antimony telluride (Ge 2 Sb 2 Te 5 ). Here, we demonstrate an alloying strategy to speed up the crystallization kinetics. The scandium antimony telluride (Sc 0.2 Sb 2 Te 3 ) compound that we designed allows a writing speed of only 700 picoseconds without preprogramming in a large conventional PCRAM device. This ultrafast crystallization stems from the reduced stochasticity of nucleation through geometrically matched and robust scandium telluride (ScTe) chemical bonds that stabilize crystal precursors in the amorphous state. Controlling nucleation through alloy design paves the way for the development of cache-type PCRAM technology to boost the working efficiency of computing systems.

Science & Technology - Other Topics↗
DOE OSTI2025

LUNA: LUT-Based Neural Architecture for Fast and Low-Cost Qubit Readout

Qubit readout is a critical operation in quantum computing systems, which maps the analog response of qubits into discrete classical states. Deep neural networks (DNNs) have recently emerged as a promising solution to improve readout accuracy . Prior hardware implementations of DNN-based readout are resource-intensive and suffer from high inference latency, limiting their practical use in low-latency decoding and quantum error correction (QEC) loops. This paper proposes LUNA, a fast and efficient superconducting qubit readout accelerator that combines low-cost integrator-based preprocessing with Look-Up Table (LUT) based neural networks for classification. The architecture uses simple integrators for dimensionality reduction with minimal hardware overhead, and employs LogicNets (DNNs synthesized into LUT logic) to drastically reduce resource usage while enabling ultra-low-latency inference. We integrate this with a differential evolution based exploration and optimization framework to identify high-quality design points. Our results show up to a 10.95x reduction in area and 30% lower latency with little to no loss in fidelity compared to the state-of-the-art. LUNA enables scalable, low-footprint, and high-speed qubit readout, supporting the development of larger and more reliable quantum computing systems.

Farooq, M. A. [Arizona State U., Tempe]↗
DOE OSTI2017

The Einstein@Home gamma-ray pulsar survey. I. Search methods, sensitivity, and discovery of new young gamma-ray pulsars

We report on the results of a recent blind search survey for gamma-ray pulsars in Fermi Large Area Telescope (LAT) data being carried out on the distributed volunteer computing system, Einstein@Home. The survey has searched for pulsations in 118 unidentified pulsar-like sources, requiring about 10,000 years of CPU core time. In total, this survey has resulted in the discovery of 17 new gamma-ray pulsars, of which 13 are newly reported in this work, and an accompanying paper. These pulsars are all young, isolated pulsars with characteristic ages between 12 kyr and 2 Myr, and spin-down powers between 10{sup 34} and 4 × 10{sup 36} erg s{sup −1}. Two of these are the slowest spinning gamma-ray pulsars yet known. One pulsar experienced a very large glitch Δf/f≈3.5×10{sup −6} during the Fermi mission. In this, the first of two associated papers, we describe the search scheme used in this survey, and estimate the sensitivity of our search to pulsations in unidentified Fermi-LAT sources. One such estimate results in an upper limit of 57% for the fraction of pulsed emission from the gamma-ray source associated with the Cas A supernova remnant, constraining the pulsed gamma-ray photon flux that can be produced by the neutron star at its center. We also present the results of precise timing analyses for each of the newly detected pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

To Exascale and Beyond—The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), a Performance Portable Global Atmosphere Model for Cloud-Resolving Scales

The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional “high–resolution” simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real-world climate via a set of four 40 day simulations covering all 4 seasons of the year.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

THE BRAKING INDEX OF A RADIO-QUIET GAMMA-RAY PULSAR

We report the discovery and timing measurements of PSR J1208−6238, a young and highly magnetized gamma-ray pulsar, with a spin period of 440 ms. The pulsar was discovered in gamma-ray photon data from the Fermi Large Area Telescope (LAT) during a blind-search survey of unidentified LAT sources, running on the distributed volunteer computing system Einstein@Home . No radio pulsations were detected in dedicated follow-up searches with the Parkes radio telescope, with a flux density upper limit at 1369 MHz of 30 μ Jy. By timing this pulsar’s gamma-ray pulsations, we measure its braking index over five years of LAT observations to be n = 2.598 ± 0.001 ± 0.1, where the first uncertainty is statistical and the second estimates the bias due to timing noise. Assuming its braking index has been similar since birth, the pulsar has an estimated age of around 2700 years, making it the youngest pulsar to be found in a blind search of gamma-ray data and the youngest known radio-quiet gamma-ray pulsar. Despite its young age, the pulsar is not associated with any known supernova remnant or pulsar wind nebula. The pulsar’s inferred dipolar surface magnetic field strength is 3.8 × 10{sup 13} G, almost 90% of the quantum-critical level. We investigate some potential physical causes of the braking index deviating from the simple dipole model but find that LAT data covering a longer time interval will be necessary to distinguish between these.

79 ASTRONOMY AND ASTROPHYSICS↗