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DOE OSTI2016

A Hartree-Fock Application Using UPC++ and the New DArray Library

The Hartree-Fock (HF) method is the fundamental first step for incorporating quantum mechanics into many-electron simulations of atoms and molecules, and it is an important component of computational chemistry toolkits like NWChem. The GTFock code is an HF implementation that, while it does not have all the features in NWChem, represents crucial algorithmic advances that reduce communication and improve load balance by doing an up-front static partitioning of tasks, followed by work stealing whenever necessary. To enable innovations in algorithms and exploit next generation exascale systems, it is crucial to support quantum chemistry codes using expressive and convenient programming models and runtime systems that are also efficient and scalable. Here, this paper presents an HF implementation similar to GTFock using UPC++, a partitioned global address space model that includes flexible communication, asynchronous remote computation, and a powerful multidimensional array library. UPC++ offers runtime features that are useful for HF such as active messages, a rich calculus for array operations, hardware-supported fetch-and-add, and functions for ensuring asynchronous runtime progress. We present a new distributed array abstraction, DArray, that is convenient for the kinds of random-access array updates and linear algebra operations on block-distributed arrays with irregular data ownership. Finally, we analyze the performance of atomic fetch-and-add operations (relevant for load balancing) and runtime attentiveness, then compare various techniques and optimizations for each. Our optimized implementation of HF using UPC++ and the DArrays library shows up to 20% improvement over GTFock with Global Arrays at scales up to 24,000 cores.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Quantum/AI Topology-Aware Latency-Adaptive HPC Workflow Scheduling Optimization

The growing demand for more powerful high-performance computing (HPC) systems has led to a steady rise in energy consumption by supercomputing worldwide. This study is focused on comparing our Application-Topology Mapper (ATMapper) to the popular Simple Linux Utility for Resource Management (SLURM) for the purpose of exploring methods that can further optimize job-scheduling within HPC systems. ATMapper is an Artificial-Intelligence based approach to job-scheduling that is currently being enhanced with quantum annealing (QA) to generate optimal schedules faster. We are applying QA to speedup our ATMapper process to achieve higher computing efficiency, thereby reducing HPC energy consumption. Here, we examine how four job-scheduling approaches perform in processor node assignment when using an example network architecture of 4 interconnected nodes. Using a specialized script, we are assessing the schedule of a computation flow with 11 interdependent tasks. The data movements among nodes were tracked to count for the number of interactions (network hops) between nodes needed to complete the tasks. The total number of hops and the job completion time were then used to quantify the efficiency of the different mapping approaches. In addition to SLURM, we also compare our ATMapper to the QA-enabled LBNL TIGER and the D-Wave Distributed Computing processor assignment approaches. The preliminary results showed that our topology-aware, latency-adaptive ATMapper is significantly more efficient when compared to the other scheduling approaches due to its load-imbalance network allocation. The scheduler displayed a computing efficiency of 53% by performing significantly fewer network hops than its alternatives. By reducing the number of hops, ATMapper was able to perform all 11 tasks by using only 3 nodes out of given 4. This research indicates the potential to use QA/AI for HPC job-scheduling. Later, we will test a SLURM simulator program to draw further comparisons on the effectiveness of ATMapper's scheduling approach. The results of this comparison will serve as a baseline for later improving SLURM's performance using a QA-enhanced ATMapper approach.

Caraveo, Braulio [University of Huston - Clear Lak↗

DOE OSTI2016

Application Characterization at Scale: Lessons learned from developing a distributed Open Community Runtime system for High Performance Computing

Since 2012, the U.S. Department of Energy’s X-Stack program has been developing solutions including runtime systems, programming models, languages, compilers, and tools for the Exascale system software to address crucial performance and power requirements. Fine grain programming models and runtime systems show a great potential to efficiently utilize the underlying hardware. Thus, they are essential to many X-Stack efforts. An abundant amount of small tasks can better utilize the vast parallelism available on current and future machines. Moreover, finer tasks can recover faster and adapt better, due to a decrease in state and control. Nevertheless, current applications have been written to exploit old paradigms (such as Communicating Sequential Processor and Bulk Synchronous Parallel processing). To fully utilize the advantages of these new systems, applications need to be adapted to these new paradigms. As part of the applications’ porting process, in-depth characterization studies, focused on both application characteristics and runtime features, need to take place to fully understand the application performance bottlenecks and how to resolve them. This paper presents a characterization study for a novel high performance runtime system, called the Open Community Runtime, using key HPC kernels as its vehicle. This study has the following contributions: one of the first high performance, fine grain, distributed memory runtime system implementing the OCR standard (version 0.99a); and a characterization study of key HPC kernels in terms of runtime primitives running on both intra and inter node environments. Running on a general purpose cluster, we have found up to 1635x relative speed-up for a parallel tiled Cholesky Kernels on 128 nodes with 16 cores each and a 1864x relative speed-up for a parallel tiled Smith-Waterman kernel on 128 nodes with 30 cores.

Application characterization↗

DOE OSTI2015

Fuel Thermo-physical Characterization Project. Fiscal Year 2014 Final Report

The Office of Material Management and Minimization (M3) Reactor Conversion Fuel Thermo-Physical Characterization Project at Pacific Northwest National Laboratory (PNNL) was tasked with using PNNL facilities and processes to receive irradiated low enriched uranium–molybdenum (LEU-Mo) fuel plate samples and perform analysis in support of the M3 Reactor Conversion Program. This work is in support of the M3 Reactor Conversion Fuel Development Pillar that is managed by Idaho National Laboratory. The primary research scope was to determine the thermo-physical properties as a function of temperature and burnup. Work conducted in Fiscal Year (FY) 2014 complemented measurements performed in FY 2013 on four additional irradiated LEU-Mo fuel plate samples. Specifically, the work in FY 2014 investigated the influence of different processing methods on thermal property behavior, the absence of aluminum alloy cladding on thermal property behavior for additional model validation, and the influence of higher operating surface heat flux / more aggressive irradiation conditions on thermal property behavior. The model developed in FY 2013 and refined in FY 2014 to extract thermal properties of the U-Mo alloy from the measurements conducted on an integral fuel plate sample (i.e., U-Mo alloy with a thin Zr coating and clad in AA6061) continues to perform very well. Measurements conducted in FY 2014 on samples irradiated under similar conditions compare well to measurements performed in FY 2013. In general, there is no gross influence of fabrication method on thermal property behavior, although the difference in LEU-Mo foil microstructure does have a noticeable influence on recrystallization of grains during irradiation. Samples irradiated under more aggressive irradiation conditions, e.g., higher surface heat flux, revealed lower thermal conductivity when compared to samples irradiated at moderate surface heat fluxes, with the exception of one sample. This report documents thermal property measurements conducted in FY 2014 and compares results to values obtained from literature and measurements performed in FY 2013, where applicable, along with appropriate discussion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Fusion Materials Research at Oak Ridge National Laboratory in Fiscal Year 2017

Achieving fusion energy presents a formidable challenge to the field of materials science, to provide a suite of suitable materials in close integration to the plasma physics and other applied technologies. The technological challenge presented by the planned fusion power systems is the inability of current materials and components to withstand the harsh fusion nuclear environment. The overarching goal of the ORNL fusion materials program is to provide the applied materials science support and materials understanding to underpin the ongoing DOE Office of Science fusion energy program in parallel with developing materials for fusion power systems. In this effort the program continues to be integrated both with the larger U.S. and international fusion materials communities and with the international fusion design and technology communities. This long-running ORNL program continues to pursue development of low activation structural materials such as the Reduced Activation Ferritic/Martensitic Steels, higher strength/higher creep resistant/coolant compatible/radiation tolerant advanced steels, and Silicon Carbide Composites. Focus tasks within the steels portfolio are development of Castable Nanostructured Alloys, exploratory work on Bainitic steels and liquid metal compatibility evaluations. Parallel to this is the increased emphasis on radiation effects, high heat flux testing and the development of refractory metals. This includes the use of an ORNL Plasma Arc Lamp facility adapted for the thermal testing of irradiated materials, the development and evaluation of new tungsten materials, and the study and understanding of the irradiation performance of tungsten. In each case the materials are being developed in a design-informed fashion where properties improvements are led by fusion-relevant design studies and directed at advancing the Technology Readiness Level of the material systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Examining United States Nuclear Weapon Educational Initiatives: A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community [Slides]

This study focused on United States nuclear weapons educational programs exploring six classroom environment factors that may or may not influence Satisfaction in a virtual/live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization, controlling for Gender, Age, and Education. This study added to the nuclear weapons community by researching factors that may aid academic instructors and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Using Python For 3D Visualizations of MCNP output

MCNP is ubiquitously used within industries, universities and national laboratories as a tool for accurately modeling radiation. With so much focus on the details of transport, attention is seldom given to the visualizations of these meticulously constructed outputs. Python is a programing language designed to promote code readability and has steadily grown in popularity since the 1990's. Python is also a heavily crowd-sourced programing language which generally means that the problems that you are trying to solve with computer codes are already solved; The user is often left with the now-simplified task of cobbling together a good and useful compilation of these tools and adapting them to solve the problem at hand. I have taken advantage of this situation and constructed some visualization tools in python that can be used to duplicate some of the 2D radiation fields that MCNP produces and also produce a meaningful 3D representation of a radiation field. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

Reaching bandwidth saturation using transparent injection parallelization

Although logically available, applications may not exploit enough instantaneous communication concurrency to maximize network utilization on HPC systems. This is exacerbated in hybrid programming models that combine single program multiple data with OpenMP or CUDA. We present the design of a “multi-threaded” runtime able to transparently increase the instantaneous network concurrency and to provide near saturation bandwidth, independent of the application configuration and dynamic behavior. The runtime offloads communication requests from application level tasks to multiple communication servers. The servers use system specific performance models to attain network saturation. Our techniques alleviate the need for spatial and temporal application level message concurrency optimizations. Experimental results show improved message throughput and bandwidth by as much as 150% for 4 KB messages on InfiniBand and by as much as 120% for 4 KB messages on Cray Aries. For more complex operations such as all-to-all collectives, we observe as much as 30% speedup. This translates into 23% speedup on 12,288 cores for a NAS FT implemented using FFTW. We observe as much as 76% speedup on 1500 cores for an already optimized UPC+OpenMP geometric multigrid application using hybrid parallelism. For the geometric multigrid GPU implementation, we observe as much as 44% speedup on 512 GPUs.

Chaimov, Nicholas↗

DOE OSTI2020

SUSTAINING NUCLEAR SECURITY REGIMES THROUGH CONTINUOUS LEARNING EXPERIENCES

As Member States plan, implement, and ultimately sustain their nuclear security regimes, human resource development supporting these regimes are paramount. Human resource development broadly includes programs addressing education, training, and knowledge management. The International Atomic Energy Agency’s Implementing Guide, Sustaining a Nuclear Security Regime, highlights the importance of national-level support for assigning resources that help ensure States are able to develop and retain sufficient human resources in the short, medium, and long term. Determining the resources needed to support education, training, and knowledge management is not an easy task, and knowledge management is a practice often overlooked when States plan for and allocate human resources for a nuclear security regime. The paper highlights the importance of implementing knowledge management practices as part of sustaining a nuclear security regime. Given the availability of secure web-based knowledge management tools, a nuclear security human resource development program should not depend solely on direct human interactions. To that end, the paper will offer an approach for planning and implementing a knowledge management system by using the U.S. Department of Energy/National Nuclear Security Administration’s Nuclear Smuggling Detection and Deterrence Knowledge Management Website as a case study. This example offers useful lessons learned for States considering or actively developing their own nuclear security knowledge management efforts and human resource development.

Tremonte, Matthew M.↗

DOE OSTI2020

A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

Science & Technology - Other Topics↗

DOE OSTI2023

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

DOE OSTI2018

A Comparison of Cargo X-Ray Attenuation as Measured by Top-Down versus Side-View Imaging Systems

Because millions of cargo containers enter the United States each year, there are millions of opportunities for terrorists to smuggle in dangerous radiological or special nuclear materials. The Department of Homeland Security (DHS) has been tasked to ensure that the United States remains safe from the illicit transportation, development, or procurement of a radiological/ nuclear (R/N) device or materials. The Nuclear and Radiological Imaging Platform (NRIP) program within DHS/CWMD aims to develop and characterize the performance of an integrated R/N detection platform and to determine if it performs better than previous screening systems. The cargo scanner developed by Passport features several technologies that have never been fielded, including the subsystem that my project involved. I concentrated on the high-energy Xray transmission imaging subsystem for producing 2D (top-down view) attenuation images. This subsystem was created to help identify highly-attenuating potential threats, but I focused on a smaller, more specific topic for my project. I worked on converting attenuations in the top-down X-ray transmission images into equivalent steel thickness. For example, a slab of material with a given attenuation would be converted into an equivalent thickness of steel that would have the same attenuation. Equivalent steel thickness provides a consistent way to compare data acquired by different inspection systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

CEED-MS34: Improve performance and capabilities of CEED-enabled ECP applications on Summit/Sierra. Exascale Computing Project Milestone Report

The main goal of this milestone was to help CEED-enabled ECP applications, including ExaSMR, MARBL, ExaWind and ExaAM, to improve their performance and capabilities on GPU systems like Summit and Lassen/Sierra. In addition, the CEED team also worked to: add and improve support for additional hardware and programming models in the CEED software components; release the next version of the CEED software stack, CEED-3.0; and demonstrate performance of libParanumal kernels in libCEED, Nek and MFEM. These additional tasks contributed directly to the main CEED-MS34 goal and will also play an important role in CEED’s future milestones.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Accelerator-driven Medical Sterilization to Replace Co-60 Sources

This report documents the results of a study prepared at the request of the Office of Radiological Security of the National Nuclear Security Administration (NNSA), as part of the Domestic Protect and Reduce mission by the Illinois Accelerator Research Center (IARC) of Fermi National Accelerator Laboratory. The study included a literature survey of over 80 relevant documents and articles including industry standards, regulatory documents, technical papers, a court case, previous task force reports and industry white papers. The team also conducted interviews or had conversations with over 40 individuals representing over a dozen organizations over the course of its 10-month program. This report summarizes our findings, addresses the specific questions posed to us by NNSA, and concludes with a list of actionable recommendations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Fighting Flicker

Thanks in part to the rapid emergence of LED lighting, the phenomenon of flicker has been getting increased attention. All conventional light sources modulate luminous flux and intensity to some degree, usually as a consequence of drawing power from AC mains sources. But whereas conventional light sources have somewhat delayed responses to changes in electrical current – which serves to “cushion” them to some degree against flickering – the LED and its driver respond instantly to such changes, which can result in stark fluctuations in light output. And while these fluctuations may not be noticeable to everyone, they can still result in health and task performance problems. Understanding and countering flicker is essential to the success of high-efficiency lighting technology. That’s why the U.S. Department of Energy (DOE) Solid-State Lighting Program conducts flicker research and is supporting a number of industry committees (CIE 1-83: Visual Aspects of Time-Modulated Lighting Systems; CIE 2-89: Measurement of Temporal Light Modulation of Light Sources and Lighting Systems; and the IES Testing Procedures Committee) that are developing flicker standards for measurement, acceptability, and metrics. A wide variety of technical resources on flicker can be found at https://www.energy.gov/eere/ssl/flicker.

lighting, flicker, flicker meters, Flicker metrics↗

DOE OSTI2022

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks: Preprint

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous–enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

DOE OSTI2020

3-D Radiological Data Acquisition, Visualization and Modeling - 20211

The U.S. Army Corps of Engineers (USACE) was tasked to investigate and remediate low activity radiological contamination from research and production of the nation's first nuclear weapons at the former DuPont Chambers Works Formerly Utilized Sites Remedial Action Program (FUSRAP) site (DuPont). The DuPont site had several buildings used for the Manhattan project that were demolished in the 1940's and 1950's apparently using heavy earthmoving equipment. Some of the contaminated rubble from the demolition appears to have been spread out by this equipment resulting in somewhat random scattering of radiologically contaminated soil and debris along with aqueous spills. Traditional investigative methods such as soil borings, test pits and 2-dimensional gamma walkovers were only partially successful in delineating the radiological contamination at the site. It was feared that even 'chasing' the contamination during remediation would miss contamination if the demolition resulted in discontinuous trails of radiologically contaminated soils. In evaluating the data generated over the interceding decades, the USACE determined that a better method to collect and process the remedial action radiological data was needed to enable the project team to optimize predictive planning and meet documentation expectations. The purpose of this paper is to provide an overview of the effort and progress to combine and organize radiological survey methods into a highly flexible sampling, modeling, and decision analysis approach that emphasizes the quality of decision-making during remediation. This innovative system blends multiple tools to develop a methodology that can extend MARRSIM [1] into the subsurface and provide tools that can be applied to other sites. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗