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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Energy savings and usability of zero-client computing in office settings

This study provides a detailed comparison of the power consumption, usability, and applicability of virtual machines (VMs) - accessed through zero-client devices - and traditional laptop computers in office settings. The study analyzed high-level plug loads across two office spaces, one using traditional laptops, the other using zero clients. In addition, the individual power consumption of four workstations was monitored and compared. Each workstation user switched between using a laptop or zero client for one week and then using the alternate system the second week. Results of the high-level and workstation analysis show that average workstation plug loads are lower for occupants using zero clients. However, this does not include power consumed by the data center managing VMs. This study calculates the affiliated data center power draw of VMs and shows that server-related loads push total zero-client computing energy higher than that of traditional laptops. Finally, a questionnaire was administered to building occupants to determine the appropriateness of zero-client computing for various user groups, with the results indicating that VMs are most appropriate for more basic software functions. The findings of this study suggest that advances in server technology can help improve both the overall efficiency and the usability of zero-client computing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Better Buildings: Energy Savings and Usability of Zero-Client Computing in Office Settings

Plug loads account for approximately 30% of commercial whole-building energy use, and this percentage is growing. That means the United States spends about $60 billion per year on energy to keep our devices running. About 10% of this is attributed to computing resources, which includes both traditional laptop and desktop computers, as well as data centers that can host virtual machines (VMs) and enable teleworking trends. Teleworking and more flexible work environments are becoming increasingly popular options, and many business and building owners wonder whether hosting VMs on data center servers has the potential to save energy. To answer this question, researchers at the National Renewable Energy Laboratory (NREL) conducted a study comparing energy and usability of remote VMs (accessed through zero-client devices) with traditional laptop computers. The findings were published in the Journal of Sustainable Cities and Society in 2017.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Energy Savings and Usability of Zero-Client Computing in Office Settings

The U.S. Department of Energy (DOE) and the National Institute of Building Sciences (NIBS) worked with industry stakeholders to develop voluntary national guidelines to improve the quality and consistency of commercial building workforce credentials for four key energy-efficiency related jobs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Computer Health Score

The algorithm develops a single health score for office computers, today just Windows, but we plan to extend this to Apple computers. The score is derived from various parameters, including: CPU Utilization; Memory Utilization; Various Error logs; Disk Problems; and Disk write queue length. It then uses a weighting scheme to balance these parameters and provide an overall health score. By using these parameters, we are not just assessing the theoretical performance of the components of the computer, rather we are using actual performance metrics that are selected to be a more realistic representation of the experience of the person using the computer. This includes compensating for the nature of their use. If there are two identical computers and the user of one places heavy demands on their computer compared with the user of the second computer, the former will have a lower health score. This allows us to provide a 'fit for purpose' score tailored to the assigned user. This is very helpful data to inform the mangers when individual computers need to be replaced. Additionally it provides specific information that can facilitate the fixing of the computer, to extend it's useful lifetime. This presents direct financial savings, time savings for users transferring from one computer to the next, and better environmental stewardship.

Source record↗
DOE OSTI2013

Field data collection of miscellaneous electrical loads in Northern California: Initial results

This report describes efforts to measure energy use of miscellaneous electrical loads (MELs) in 880 San Francisco Bay Area homes during the summer of 2012. Ten regions were selected for metering: Antioch, Berkeley, Fremont, Livermore, Marin County (San Rafael, Novato, Fairfax, and Mill Valley), Oakland/Emeryville, Pleasanton, Richmond, San Leandro, and Union City. The project focused on three major categories of devices: entertainment (game consoles, set-top boxes, televisions and video players), home office (computers, monitors and network equipment), and kitchen plug-loads (coffee/espresso makers, microwave ovens/toaster ovens/toasters, rice/slow cookers and wine chillers). These categories were important to meter because they either dominated the estimated overall energy use of MELs, are rapidly changing, or there are very little energy consumption data published. A total of 1,176 energy meters and 143 other sensors were deployed, and 90% of these meters and sensors were retrieved. After data cleaning, we obtained 711 valid device energy use measurements, which were used to estimate, for a number of device subcategories, the average time spent in high power, low power and “off” modes, the average energy use in each mode, and the average overall energy use. Consistent with observations made in previous studies, we find on average that information technology (IT) devices (home entertainment and home office equipment) consume more energy (15.0 and 13.0 W, respectively) than non-IT devices (kitchen plug-loads; 4.9 W). Opportunities for energy savings were identified in almost every device category, based on the time spent in various modes and/or the power levels consumed in those modes. Future reports will analyze the collected data in detail by device category and compare results to those obtained from prior studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Pumping Optimization Model for Pump and Treat Systems - 15091

Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.

Baker, S.↗
DOE OSTI2015

Pumping optimization model for pump and treat systems - 15091

Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of the U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Implementing Software Resiliency in HPX for Extreme Scale Computing

The DOE Office of Science Exascale Computing Project (ECP) outlines the next milestones in the supercomputing domain. The target computing systems under the project will deliver 10x performance while keeping the power budget under 30 megawatts. With such large machines, the need to make applications resilient has become paramount. The benefits of adding resiliency to mission critical and scientific applications, includes the reduced cost of restarting the failed simulation both in terms of time and power. Most of the current implementation of resiliency at the software level makes use of a Coordinated Checkpoint and Restart (C/R). This technique of resiliency generates a consistent global snapshot, also called a checkpoint. Generating snapshots involves global communication and coordination and is achieved by synchronizing all running processes. The generated checkpoint is then stored in some form of persistent storage. On failure detection, the runtime initiates a global rollback to the most recent previously saved checkpoint. This involves aborting all running processes, rolling them back to the previous state and restarting them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

ASCR@40: Highlights and Impacts of ASCR’s Programs

A report compiled by the ASCAC Subcommittee on the 40-year history of ASCR for the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. The Office of Advanced Scientific Computing Research (ASCR) sits within the Office of Science in the Department of Energy (DOE). Per their web pages, “the mission of the ASCR program is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to the DOE.” This succinct statement encompasses a wide range of responsibilities for computing and networking facilities; for procuring, deploying, and operating high performance computing, networking, and storage resources; for basic research in mathematics and computer science; for developing and sustaining a large body of software; and for partnering with organizations across the Office of Science and beyond. While its mission statement may seem very contemporary, the roots of ASCR are quite deep—long predating the creation of DOE. Applied mathematics and advanced computing were both elements of the Theoretical Division of the Manhattan Project. In the early 1950s, the Manhattan Project scientist and mathematician John von Neumann, then a commissioner for the AEC (Atomic Energy Commission), advocated for the creation of a Mathematics program to support the continued development and applications of digital computing. Los Alamos National Laboratory (LANL) scientist John Pasta created such a program to fund researchers at universities and AEC laboratories. Under several organizational name changes, this program has persisted ever since, and would eventually grow to become ASCR.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

US Department of Energy, Office of Science, High-Performance Computing Facility 2024 Operational Assessment Oak Ridge Leadership Computing Facility

The Oak Ridge Leadership Computing Facility (OLCF) was established to accelerate scientific discovery by providing world-leading computational performance and advanced data infrastructure to the US Department of Energy (DOE) computing community. As a DOE Office of Science user facility, the OLCF has managed the successful deployment and operation of a succession of leadership-class resources dedicated to open science. In addition to these resources, the OLCF staff continually strive to develop innovative processes and technologies, improve security, and empower users through effective allocation management and comprehensive user support and training. These efforts support the advancement of science by the OLCF users and benefit high-performance computing (HPC) facilities around the world.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enterprise Risks for Scientific Software in the Post Exascale Era

The Department of Energy’s Office of Science’s Advanced Scientific Computing Research (ASCR) Office hosts three high performance computing Facilities and one high performance networking Facility. ASCR’s Facilities Division and these four Facilities established a joint working group to address the most severe threats to the software capabilities that can prevent the Facilities from supporting a diverse array of mission critical scientific research carried out by thousands of researchers from national labs, academia, and industry. This report outlines the risk categories, threat matrix calculations, and number of risks in each of the categories along with the threat levels. Two categories—programming environment/tools and system software—account for 13 out of the 20 risks encountered in the risk register. A significant risk to ASCR’s software ecosystem also arises from the possible loss of personnel and expertise past the end of the exascale computing project. The working group recommends that the software enterprise risks are reevaluated regularly, and are considered in future decision making regarding system acquisition, knowledge sharing, partnership development, and strategic planning

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Advanced Simulation Capability for Environmental Management (ASCEM) Phase II Demonstration

In 2009, the National Academies of Science (NAS) reviewed and validated the U.S. Department of Energy Office of Environmental Management (EM) Technology Program in its publication, Advice on the Department of Energy’s Cleanup Technology Roadmap: Gaps and Bridges. The NAS report outlined prioritization needs for the Groundwater and Soil Remediation Roadmap, concluded that contaminant behavior in the subsurface is poorly understood, and recommended further research in this area as a high priority. To address this NAS concern, the EM Office of Site Restoration began supporting the development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific approach that uses an integration of toolsets for understanding and predicting contaminant fate and transport in natural and engineered systems. The ASCEM modeling toolset is modular and open source. It is divided into three thrust areas: Multi-Process High Performance Computing (HPC), Platform and Integrated Toolsets, and Site Applications. The ASCEM toolsets will facilitate integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Project Final Report: HPC-Colony II

This report recounts the HPC Colony II Project which was a computer science effort funded by DOE's Advanced Scientific Computing Research office. The project included researchers from ORNL, IBM, and the University of Illinois at Urbana-Champaign. The topic of the effort was adaptive system software for extreme scale parallel machines. A description of findings is included.

Adaptive Software↗
DOE OSTI2014

Large Scale Computing and Storage Requirements for Fusion Energy Sciences: Target 2017

The National Energy Research Scientific Computing Center (NERSC) is the primary computing center for the DOE Office of Science, serving approximately 4,500 users working on some 650 projects that involve nearly 600 codes in a wide variety of scientific disciplines. In March 2013, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR) and DOE's Office of Fusion Energy Sciences (FES) held a review to characterize High Performance Computing (HPC) and storage requirements for FES research through 2017. This report is the result.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗