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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Constructing Memory Through Artistic Practices - 18197

I have been investigating radioactive waste sites internationally since 1994, analyzing how this archaeological stratum of the 21. century can be read in the landscape. Over more than twenty years of work this research has led me to visit several sites around the world. My focus has become the identification of the disposal sites in the landscape, as well as finding ways to pass on memory. Reports on Disposal Sites and Exhibitions: - Dessel, Belgium - exhibition at De Markten, Brussels; - Sacavem, Portugal - participation to the World Exhibition in Lisbon; - El Cabril, Spain - workshop at the University of Bilbao; - Angra dos Reis, Brazil - exhibition at Centre cultural Puc, Rio de Janeiro; - Rokkasho Mura, Japan - exhibition at gallery Gen, Tokyo; - Soulaines D'Huys, France - exhibition at art gallery Cours Carree, Paris; - CSM, Beaumont-Hague, France - exhibition at the House of Culture in Tournai, Belgium; - Fortsmark, Sweden - exhibition at 340 Muzeum, Brussels; - Cnesten Maamora, Morocco - exhibition at Villa des Arts, Casablanca; - Bhabha Atomic Research, Trombay, India - I was allowed to visit it but it was forbidden to make photographs or drawings. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Information processing systems, reasoning modules, and reasoning system design methods

Information processing systems, reasoning modules, and reasoning system design methods are described. According to one aspect, an information processing system includes working memory comprising a semantic graph which comprises a plurality of abstractions, wherein the abstractions individually include an individual which is defined according to an ontology and a reasoning system comprising a plurality of reasoning modules which are configured to process different abstractions of the semantic graph, wherein a first of the reasoning modules is configured to process a plurality of abstractions which include individuals of a first classification type of the ontology and a second of the reasoning modules is configured to process a plurality of abstractions which include individuals of a second classification type of the ontology, wherein the first and second classification types are different.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Nuclear, Land marker for a Waste Isolation Site: International Architecture Competition - 18240

The design and construction of a nuclear waste marker must include many architectural considerations. Very little research has been conducted by architects to address this issue to date. Historically, the task of designating a nuclear waste site has been a discussion predominantly contained within the scientific and engineering communities. In an effort to engage architects within this dialogue, arch out loud hosted the NUCLEAR competition as an international, architectural investigation into the design of a nuclear waste site marker. The NUCLEAR competition asks participants to design a marker to designate the site of the Waste Isolation Pilot Plant (WIPP) located near Carlsbad, New Mexico. The marker will be meant to be a means of passive institutional controls (PICs) to deter inadvertent human intrusion upon the site and should last 10,000 years. The NUCLEAR competition defined the purpose of the nuclear waste site marker as a means to communicate the danger of inadvertent intrusion from future generations. The competition requires that entries must be both legible in communication and durable in their construction. The competition brief challenged participants to consider how customs and languages will evolve over time and to predict what motivations future generations might have for digging at the site. Other background information was provided about the site such as how waste was stored and how the unique geology of the site seals the waste. The 1993 Sandia National Laboratories report titled Expert Judgment on Markers to Deter Inadvertent Human Intrusion into the Waste Isolation Pilot Plant [1] was referenced along with the 1992 WIPP Land Withdrawal Act [2], interviews with WIPP scientists [3] involved with the WIPP PICs program and the Nuclear Energy Agency Records Knowledge and Memory working group. Competition participants were given digital 3-D Computer-Aided Design models for reference that included the underground storage portion of the site, existing buildings and the 16-square-mile site boundary identified in the 1992 WIPP Land Withdrawal Act [2]. This paper will: - Provide a detailed description of the submitted proposals including graphic analysis of the visualizations, diagrams, technical drawings, jury comments and statements. - Catalogue and identify the consistent themes within all submissions with possible categories including: 1) overall architectural form and language, 2) integration of written language and symbols within architecture, 3) use of technology and robotics, 4) construction methods and materials. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2012

Lunar Reconnaissance Orbiter (LRO) Command and Data Handling Flight Electronics Subsystem

A document describes a high-performance, modular, and state-of-the-art Command and Data Handling (C&DH) system developed for use on the Lunar Reconnaissance Orbiter (LRO) mission. This system implements a complete hardware C&DH subsystem in a single chassis enclosure that includes a processor card, 48 Gbytes of solid-state recorder memory, data buses including MIL-STD-1553B, custom RS-422, SpaceWire, analog collection, switched power services, and interfaces to the Ka-Band and S-Band RF communications systems. The C&DH team capitalized on extensive experience with hardware and software with PCI bus design, SpaceWire networking, Actel FPGA design, digital flight design techniques, and the use of VxWorks for the real-time operating system. The resulting hardware architecture was implemented to meet the LRO mission requirements. The C&DH comprises an enclosure, a backplane, a low-voltage power converter, a single-board computer, a communications interface board, four data storage boards, a housekeeping and digital input/output board, and an analog data acquisition board. The interfaces between the C&DH and the instruments and avionics are connected through a SpaceWire network, a MIL-STD-1553 bus, and a combination of synchronous and asynchronous serial data transfers over RS-422 and LVDS (low-voltage differential-signaling) electrical interfaces. The C&DH acts as the spacecraft data system with an instrument data manager providing all software and internal bus scheduling, ingestion of science data, distribution of commands, and performing science operations in real time.

Nguyen, Quang↗
DOE OSTI2017

Exascale Programming Approaches for Accelerated Climate Modeling for Energy

The Accelerated Climate Modeling for Energy (ACME) program is a leading-edge climate and Earth system model designed to address the U.S. Department of Energy (DOE) mission needs. The ACME project involves collaboration between seven National Laboratories, the National Center for Atmospheric Research, four academic institutions, and one private-sector company. The ACME project funds ongoing efforts to ensure the model continues to make efficient use of DOE Leadership Computing Facilities (LCFs) in order to best address the three driving grand challenge science questions:Water cycle: How will more realistic portrayals of features important to the water cycle (resolution, clouds, aerosols, snowpack, river routing, land use) affect river flow and associated freshwater supplies at the watershed scale?Cryosphere systems: Could a dynamical instability in the Antarctic ice sheet be triggered within the next 40 years?Biogeochemistry: What are the contributions and feedbacks from natural and managed systems to current greenhouse gas fluxes, and how will those factors and associated fluxes evolve in the future?

Norman, Matthew↗
NASA NTRS2023

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As the space economy continues to expand through increasingly easy access to advanced and inexpensive technology, space missions themselves have become more ambitious with exploration targets growing ever distant while simultaneously requiring larger guidance and communication budgets. These conflicting desires of distance and control drive the need for advanced on-board intelligent decision making to reduce communication and control limitations by automating as many mission functions as possible in-situ. While the amount of research on such Artificial Intelligence and Machine Learning (AI/ML) software modules has grown exponentially, the capacity to experimentally validate such software modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available bleeding-edge computational platforms via what is programmatically referred to as the BrainStack on the TechEdSat (TES-n) flight series. This on-orbit computational platform provides an evaluation laboratory where advanced software experiments are pre-loaded into memory prior to launch, then executed as payloads during mission operations with results reported back and program tweaks or new training sets uploaded as needed. Processors selected as part of the BrainStack are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and, more recently, neuromorphic processors, in LEO operations. Neuromorphic processors are of particular interest due to their superior power efficiency over GPUs in intelligent automation applications. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on TES-13, January 13, 2022, and continues to operate in orbit despite no significant modifications to harden the processor against the space environment. The Intel Loihi Gen-1 on TES-13 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. The processor is packaged in the Kapoho Bay USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by an Intel Pentium single-board computer to handle scheduling of the software application payloads and communications with the satellite’s primary computer. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the continually evolving BrainStack in the upcoming three TES-n/NOW flights. The Kapoho Point unit will incorporate eight Loihi-2 processors, enabling neural networks of up to one million neurons and one billion synapsis. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space automation applications may be initially tested.

Artificial Intelligence↗
DOE OSTI2026

A hybrid CNN-LSTM surrogate model for hyper-resolution spatiotemporal flood forecasting in Norfolk, Virginia

Study region: Norfolk, Virginia, United States Study focus: Accurate and timely flood forecasting is essential for enhancing resilience in coastal urban areas in the context of increasing frequency and intensity of rainfall, sea level rise and urbanization. This study presents a hybrid deep learning-based surrogate model that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enable real-time spatiotemporal flood forecasting. The model leverages CNN to capture spatial features from inputs such as elevation and Topographic Wetness Index (TWI), while LSTM processes time-series inputs of rainfall and tide data to capture temporal features. New hydrologic insights for the region: The hybrid CNN-LSTM model was trained using the physics-based hydrodynamic model simulations obtained from the Two-dimensional Unsteady FLOW (TUFLOW) model for Norfolk, Virginia, and achieved high predictive accuracy across diverse flood-prone areas. The reduced computational time from four to six hours using TUFLOW to 3.2 min per event using CNN-LSTM enables rapid flood inundation mapping and early warning applications. The model effectively captured both spatial flood extents and their temporal evolution across different flooding scenarios, providing forecasts at a 2.5-m spatial resolution and 15-min temporal resolution and a one-hour-ahead prediction horizon. While challenges remain in terms of transferability to new regions and real-time data assimilation, this approach demonstrates strong potential for supporting operational flood risk management in coastal urban environments.

Coastal urban flooding↗
DOE OSTI2023

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorologically relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks to months is an area of active research and development. NASA's Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1–3-month lead times in the HMA region, including a portion of the Indian subcontinent, during the retrospective forecast period, 1981–2016. To assess forecast skill, we evaluate 2 m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to the similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from an anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system's ability to forecast HMA hydrometeorology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Seasonal Forecasting Skill for the High Mountain Asia Region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorological relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks-to-months is an area of active research and development. NASA’s 15 Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1-3 month lead times in the HMA region, including a portion of the Indian Subcontinent, during the retrospective forecast period, 1981-2016. To assess forecast skill, we evaluate 2-m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and 20 Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are 25 evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system’s ability to forecast HMA hydrometeorology.

GEOS↗
DOE OSTI2013

A Proposal for Geologic Radioactive Waste Disposal Environmental Zero-State and Subsequent Monitoring Definition - First Lessons Learned from the French Environment Observatory - 13188

Obtaining a reference state of the environment before the beginning of construction work for a geological repository is essential as it will be useful for further monitoring during operations and beyond, thus keeping a memory of the original environmental state. The area and the compartments of the biosphere to be observed and monitored as well as the choice of the markers (e.g. bio-markers, biodiversity, quality of the environment, etc.) to be followed must be carefully selected. In parallel, the choice and selection of the environmental monitoring systems (i.e. scientific and technical criteria, social requirements) will be of paramount importance for the evaluation of the perturbations that could be induced during the operational phase of the repository exploitation. This paper presents learning points of the French environment observatory located in the Meuse/Haute-Marne that has been selected for studying the feasibility of the underground disposal of high level wastes in France. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗
DOE OSTI2012

Using the Sirocco File System for high-bandwidth checkpoints.

The Sirocco File System, a file system for exascale under active development, is designed to allow the storage software to maximize quality of service through increased flexibility and local decision-making. By allowing the storage system to manage a range of storage targets that have varying speeds and capacities, the system can increase the speed and surety of storage to the application. We instrument CTH to use a group of RAM-based Sirocco storage servers allocated within the job as a high-performance storage tier to accept checkpoints, allowing computation to potentially continue asynchronously of checkpoint migration to slower, more permanent storage. The result is a 10-60x speedup in constructing and moving checkpoint data from the compute nodes. This demonstration of early Sirocco functionality shows a significant benefit for a real I/O workload, checkpointing, in a real application, CTH. By running Sirocco storage servers within a job as RAM-only stores, CTH was able to store checkpoints 10-60x faster than storing to PanFS, allowing the job to continue computing sooner. While this prototype did not include automatic data migration, the checkpoint was available to be pushed or pulled to disk-based storage as needed after the compute nodes continued computing. Future developments include the ability to dynamically spawn Sirocco nodes to absorb checkpoints, expanding this mechanism to other fast tiers of storage like flash memory, and sharing of dynamic Sirocco nodes between multiple jobs as needed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗
NASA NTRS2006

Valve Health Monitoring System Utilizing Smart Instrumentation

The valve monitoring system is a stand alone unit with network capabilities for integration into a higher level health management system. The system is designed for aiding in failure predictions of high-geared ball valves and linearly actuated valves. It performs data tracking and archiving for identifying degraded performance. The data collection types are cryogenic cycles, total cycles, inlet temperature, body temperature torsional strain, linear bonnet strain, preload position, total travel and total directional changes. Events are recorded and time stamped in accordance with the IRIG B True Time. The monitoring system is designed for use in a Class 1 Division II explosive environment. The basic configuration consists of several instrumentation sensor units and a base station. The sensor units are self contained microprocessor controlled and remotely mountable in three by three by two inches. Each unit is potted in a fire retardant substance without any cavities and limited to low operating power for maintaining safe operation in a hydrogen environment. The units are temperature monitored to safeguard against operation outside temperature limitations. Each contains 902-928 MHz band digital transmitters which meet Federal Communication Commission's requirements and are limited to a 35 foot transmission radius for preserving data security. The base-station controller correlates data from the sensor units and generates data event logs on a compact flash memory module for database uploading. The entries are also broadcast over an Ethernet network. Nitrogen purged National Electrical Manufactures Association (NEMA) Class 4 enclosures are used to house the base-station

Jensen, Scott L.↗
NASA NTRS2010

Different Perspectives on Asthenia in Astronauts and Cosmonauts: International Research Literature

The Behavioral Health and Performance (BHP) Element is one of the six elements within the NASA Human Research Program (HRP) and is responsible for managing four risks: a) The Risk of Performance Decrements due to inadequate Cooperation, Coordination, Communication and Psychological Adaptation within a Team (Team), b) the Risk of Performance Errors due to Sleep Loss, Circadian De-synchronization, Fatigue and Work Overload (Sleep), c) Risk of Behavioral Conditions (BMed), and d) the Risk of Psychiatric Disorders (BMed). The aim of this report is to address some of the recommendations made by the recent NASA HRP Standing Review Panel for the Behavioral Medicine Risk of Psychiatric Disorders. Such recommendations included: a) the inclusion of important national and international literature in English and non-English language materials; including journals, books, magazines, conference reports and b) an extensive literature review of certain types of psychological states to predict, detect, and assess adverse mental states that may negatively affect the psychological well being of the astronauts, specifically asthenia. This report was a collaborative international work effort focused on the evaluation and determination of the importance of continuing research on asthenia as a possible psychological problem that might affect the optimal psychological functioning among crewmembers during long-duration space flight missions. Russian medical personnel (flight surgeons and psychologist) have observed symptoms of asthenia (weakness, increased fatigue, irritability, and attention and memory disorders) in cosmonauts after four months in space (Myasnikov& Zamaleddinov1996; Grigorieve, 1996 ) and believe that asthenia is one of the greater risks that will affect crews? optimal psychological functioning.

Sandoval, Luis↗
NASA NTRS2004

Implementation of a Message Passing Interface into a Cloud-Resolving Model for Massively Parallel Computing

The capability for massively parallel programming (MPP) using a message passing interface (MPI) has been implemented into a three-dimensional version of the Goddard Cumulus Ensemble (GCE) model. The design for the MPP with MPI uses the concept of maintaining similar code structure between the whole domain as well as the portions after decomposition. Hence the model follows the same integration for single and multiple tasks (CPUs). Also, it provides for minimal changes to the original code, so it is easily modified and/or managed by the model developers and users who have little knowledge of MPP. The entire model domain could be sliced into one- or two-dimensional decomposition with a halo regime, which is overlaid on partial domains. The halo regime requires that no data be fetched across tasks during the computational stage, but it must be updated before the next computational stage through data exchange via MPI. For reproducible purposes, transposing data among tasks is required for spectral transform (Fast Fourier Transform, FFT), which is used in the anelastic version of the model for solving the pressure equation. The performance of the MPI-implemented codes (i.e., the compressible and anelastic versions) was tested on three different computing platforms. The major results are: 1) both versions have speedups of about 99% up to 256 tasks but not for 512 tasks; 2) the anelastic version has better speedup and efficiency because it requires more computations than that of the compressible version; 3) equal or approximately-equal numbers of slices between the x- and y- directions provide the fastest integration due to fewer data exchanges; and 4) one-dimensional slices in the x-direction result in the slowest integration due to the need for more memory relocation for computation.

Juang, Hann-Ming Henry↗
DOE OSTI2017

Development of an Integrated System for the Long-term Preservation of Records, Knowledge and Memory relating to Radioactive Waste Disposal Facilities - 17099

The Nuclear Energy Agency (NEA) has co-ordinated an international initiative to develop a common approach to the preservation of records, knowledge and long-term memory (RK and M), focused on radioactive waste disposals. The work programme has run in two phases, starting in 2011, with the current phase of the project due to be completed in 2018. Preparations for final reporting are now underway. The detailed implementation of an approach to RK and M preservation for any disposal facility will always remain a national decision. However, the NEA project has produced a 'menu' of tools and techniques that can be accessed and adapted to suit national needs. The common source of these menu components will help to ensure that the memory of the repository is kept alive, that messages to future populations can be clearly understood, and that evidence derived from the disposal environment can be properly interpreted. This paper describes the vision for implementation of the RK and M initiative within national programmes. Practical testing of some components of the menu of tools and techniques is currently underway in France, Sweden and USA, with encouraging results. Other disposal facilities, both under development or in planning, are invited to 'road test' the products and provide feedback. Refinement and maintenance of the tools remains important, and the NEA is committed to ensuring the continued accessibility and availability of the project outputs into the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Evaluating OpenSHMEM Explicit Remote Memory Access Operations and Merged Requests

The OpenSHMEM Library Specification has evolved consid- erably since version 1.0. Recently, non-blocking implicit Remote Memory Access (RMA) operations were introduced in OpenSHMEM 1.3. These provide a way to achieve better overlap between communication and computation. However, the implicit non-blocking operations do not pro- vide a separate handle to track and complete the individual RMA opera- tions. They are guaranteed to be completed after either a shmem quiet(), shmem barrier() or a shmem barrier all() is called. These are global com- pletion and synchronization operations. Though this semantic is expected to achieve a higher message rate for the applications, the drawback is that it does not allow fine-grained control over the completion of RMA operations. In this paper, first, we introduce non-blocking RMA operations with requests, where each operation has an explicit request to track and com- plete the operation. Second, we introduce interfaces to merge multiple requests into a single request handle. The merged request tracks multiple user-selected RMA operations, which provides the flexibility of tracking related communication operations with one request handle. Lastly, we explore the implications in terms of performance, productivity, usability and the possibility of defining different patterns of communication via merging of requests. Our experimental results show that a well designed and implemented OpenSHMEM stack can hide the overhead of allocating and managing the requests. The latency of RMA operations with requests is similar to blocking and implicit non-blocking RMA operations. We test our implementation with the Scalable Synthetic Compact Applications (SSCA #1) benchmark and observe that using RMA operations with requests and merging of these requests outperform the implementation using blocking RMA operations and implicit non-blocking operations by 49% and 74% respectively.

Boehm, Swen↗