MarFS - Scalable POSIX on Object File System [Slides]
Abstract not provided.
97 MATHEMATICS AND COMPUTING↗
SEARCH · Engineering Papers
Results for “Scalable”
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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Scalable Heuristics for Planning, Placement and Sizing of Flexible AC Transmission System Devices
Aiming to relieve transmission grid congestion and improve or extend feasibility domain of the operations, we build optimization heuristics, generalizing standard AC Optimal Power Flow (OPF), for placement and sizing of Flexible Alternating Current Transmission System (FACTS) devices of the Series Compensation (SC) and Static VAR Compensation (SVC) type. One use of these devices is in resolving the case when the AC OPF solution does not exist because of congestion. Another application is developing a long-term investment strategy for placement and sizing of the SC and SVC devices to reduce operational cost and improve power system operation. SC and SVC devices are represented by modification of the transmission line inductances and reactive power nodal corrections respectively. We find one placement and sizing of FACTs devices for multiple scenarios and optimal settings for each scenario simultaneously. Our solution of the nonlinear and nonconvex generalized AC-OPF consists of building a convergent sequence of convex optimizations containing only linear constraints and shows good computational scaling to larger systems. The approach is illustrated on single- and multi-scenario examples of the Matpower case-30 model.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Synthetic Graph Generation for Data-Intensive HPC Benchmarking: Scalability, Analysis and Real-World Application
The benchmarking effort within the Extreme Scale Systems Center at Oak Ridge National Laboratory seeks to provide High Performance Computing benchmarks and test suites of interest to the DoD sponsor. The work described in this report is a part of the effort focusing on graph generation. A previously developed benchmark, SystemBurn, allows the emulation of a broad spectrum of application behavior profiles within a single framework. To complement this effort, similar capabilities are desired for graph-centric problems. This report described the in-depth analysis of the generated synthetic graphs' properties at a variety of scales using different generator implementations and examines their applicability to replicating real world datasets.
97 MATHEMATICS AND COMPUTING↗
Performance Verification of Production-Scalable Energy-Efficient Solutions: Winchester/Camberley Homes Mixed-Humid Climate
Winchester/Camberley Homes collaborated with the Building America team Partnership for Home Innovation to develop a new set of high performance home designs that could be applicable on a production scale. The new home designs are to be constructed in the mixed humid climate zone and could eventually apply to all of the builder's home designs to meet or exceed future energy codes or performance-based programs. However, the builder recognized that the combination of new wall framing designs and materials, higher levels of insulation in the wall cavity, and more detailed air sealing to achieve lower infiltration rates changes the moisture characteristics of the wall system. In order to ensure long term durability and repeatable successful implementation with few call-backs, the project team demonstrated through measured data that the wall system functions as a dynamic system, responding to changing interior and outdoor environmental conditions within recognized limits of the materials that make up the wall system. A similar investigation was made with respect to the complete redesign of the HVAC systems to significantly improve efficiency while maintaining indoor comfort. Recognizing the need to demonstrate the benefits of these efficiency features, the builder offered a new house model to serve as a test case to develop framing designs, evaluate material selections and installation requirements, changes to work scopes and contractor learning curves, as well as to compare theoretical performance characteristics with measured results.
2x6 walls↗
Scalable Codesign Performance Prediction for Computational Physics - Mid-Term- Appraisal: Overview Talk
No abstract provided.
97 MATHEMATICS AND COMPUTING↗
Scalable, Economical Fabrication Processes for Ultra-Compact Warm-White LEDs
Conventional warm-white LED component fabrication consists of a large number of sequential steps which are required to incorporate electrical, mechanical, and optical functionality into the component. Each of these steps presents cost and yield challenges which multiply throughout the entire process. Although there has been significant progress in LED fabrication over the last decade, significant advances are needed to enable further reductions in cost per lumen while not sacrificing efficacy or color quality. Cree conducted a focused 18-month program to develop a new low-cost, high-efficiency light emitting diode (LED) architecture enabled by novel large-area parallel processing technologies, reduced number of fabrication steps, and minimized raw materials use. This new scheme is expected to enable ultra-compact LED components exhibiting simultaneously high efficacy and high color quality. By the end of the program, Cree fabricated warm-white LEDs with a room-temperature “instant on” efficacy of >135 lm/W at ~3500K and 90 CRI (when driven at the DOE baseline current density of 35 A/cm2). Cree modified the conventional LED fabrication process flow in a manner that is expected to translate into simultaneously high throughput and yield for ultra-compact packages. Building on its deep expertise in LED wafer fabrication, Cree developed these ultra-compact LEDs to have no compromises in color quality or efficacy compared to their conventional counterparts. Despite their very small size, the LEDs will also be robustly electrically integrated into luminaire systems with the same attach yield as conventional packages. The versatility of the prototype high-efficacy LED architecture will likely benefit solid-state lighting (SSL) luminaire platforms ranging from bulbs to troffers. We anticipate that the prototype LEDs will particularly benefit luminaires with large numbers of distributed compact packages, such as linear and area luminaires (e.g. troffers). The fraction of total SSL luminaire cost made up by the LEDs themselves has steadily fallen over the past several years, but can still make up 30% or more of the bill of materials; the new LED design will radically lower this proportion. Ultra-compact, highly efficient LEDs with optimal distribution in the system will further benefit luminaire materials and assembly costs by reducing the complexity and volume of thermal management and optical subsystems.
42 ENGINEERING↗
Flexible and Scalable Data Fusion using Proactive Schemaless Information Services
Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once- read-never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are made known. Lastly, we embrace found data heterogeneity by coupling multi-indexing to backing stores with appropriate semantics (as opposed to a single store or schema).
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
Flexible and Scalable Data Fusion using Proactive, Schemaless Information Services
Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once-read- never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are made known. Lastly, we embrace found data heterogeneity by coupling multi-indexing to backing stores with appropriate semantics (as opposed to a single store or schema).
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Enabling Secure, Scalable Microgrids with High Penetration Renewables
In the first section, ac and dc technologies are compared highlighting their advantages and disadvantages. Since ac and dc systems have both evolved significantly since their introduction in the mid and latter parts of the 19th century, many of the early advantages of ac systems no longer exist or are of less importance today. Consequently, it is useful to provide a brief historical perspective on the evolution of both ac and dc power systems. As in the dc case, there are many potential modes of operation and control strategies for the given system. In ac systems, the situation is more complex since it is necessary to regulate both the amplitude and the frequency of the ac voltage. In the third section, the techniques of controlling and analyzing the stability of ac systems is reviewed.
30 DIRECT ENERGY CONVERSION↗
MarFS: A Scalable Near-POSIX Name Space over Cloud Objects – New Features
No abstract provided.
97 MATHEMATICS AND COMPUTING↗
Scalability of the LEU-Modified Cintichem Process: 3-MeV Van de Graaff and 35-MeV Electron Linear Accelerator Studies
Molybdenum-99, the mother of Tc-99m, can be produced from fission of U-235 in nuclear reactors and purified from fission products by the Cintichem process, later modified for low-enriched uranium (LEU) targets. The key step in this process is the precipitation of Mo with α-benzoin oxime (ABO). The stability of this complex to radiation has been examined. Molybdenum-ABO was irradiated with 3 MeV electrons produced by a Van de Graaff generator and 35 MeV electrons produced by a 50 MeV/25 kW electron linear accelerator. Dose equivalents of 1.7–31.2 kCi of Mo-99 were administered to freshly prepared Mo-ABO. Irradiated samples of Mo-ABO were processed according to the LEU Modified-Cintichem process. The Van de Graaff data indicated good radiation stability of the Mo-ABO complex up to ~15 kCi dose equivalents of Mo-99 and nearly complete destruction at doses >24 kCi Mo-99. The linear accelerator data indicate that even at 6.2 kCi of Mo-99 equivalence of dose, the sample lost ~20% of Mo-99. The 20% loss of Mo-99 at this low dose may be attributed to thermal decomposition of the product from the heat deposited in the sample during irradiation.
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
Scalable Track Detection in SAR CCD Images
Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.
47 OTHER INSTRUMENTATION↗
Scalable data management, analysis and visualization (SDAV) Institute. Final Scientific/Technical Report
The purpose of the SDAV institute is to provide tools and expertise in scientific data management, analysis, and visualization to DOE’s application scientists. Our goal is to actively work with application teams to assist them in achieving breakthrough science, and to provide technical solutions in the data management, analysis, and visualization regimes that are broadly used by the computational science community. Over the last 5 years members of our institute worked directly with application scientists and DOE leadership-class facilities to assist them by applying the best tools and technologies at our disposal. We also enhanced our tools based on input from scientists on their needs. Many of the applications we have been working with are based on connections with scientists established in previous years. However, we contacted additional scientists though our outreach activities, as well as engaging application teams running on leading DOE computing systems. Our approach is to employ an evolutionary development and deployment process: first considering the application of existing tools, followed by the customization necessary for each particular application, and then the deployment in real frameworks and infrastructures. The institute is organized into three areas, each with area leaders, who keep track of progress, engagement of application scientists, and results. The areas are: (1) Data Management, (2) Data Analysis, and (3) Visualization. Kitware has been involved in the Visualization area. This report covers Kitware’s contributions over the last 5 years (February 2012 – February 2017). For details on the work performed by the SDAV institute as a whole, please see the SDAV final report.
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Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery
The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
FY17 ASC P&EM L2 Milestone 6009: Demonstrate Thread Scalability within Aria on Both Sides of Trinity
The use of next-generation platforms (NGPs), also known as advanced technology systems (ATS), that incorporate many-core and heterogeneous architectures for scientific computing represent a tectonic shift in computing hardware design that will require massive development work within the Sierra applications to harness these systems to their full potential. The completion of this milestone represents a first step towards this effort by threading many of the computational kernels within Sierra/Aria.
97 MATHEMATICS AND COMPUTING↗
Extreme-Scale Algorithms & Software Resilience (EASIR) Architecture-Aware Algorithms for Scalable Performance and Resilience on Heterogeneous Architectures
This project addresses both communication-avoiding algorithms, and reproducible floating-point computation. Communication, i.e. moving data, either between levels of memory or processors over a network, is much more expensive per operation than arithmetic (measured in time or energy), so we seek algorithms that greatly reduce communication. We developed many new algorithms for both dense and sparse, and both direct and iterative linear algebra, attaining new communication lower bounds, and getting large speedups in many cases. We also extended this work in several ways: (1) We minimize writes separately from reads, since writes may be much more expensive than reads on emerging memory technologies, like Flash, sometimes doing asymptotically fewer writes than reads. (2) We extend the lower bounds and optimal algorithms to arbitrary algorithms that may be expressed as perfectly nested loops accessing arrays, where the array subscripts may be arbitrary affine functions of the loop indices (eg A(i), B(i,j+k, k+3*m-7, …) etc.). (3) We extend our communication-avoiding approach to some machine learning algorithms, such as support vector machines. This work has won a number of awards. We also address reproducible floating-point computation. We define reproducibility to mean getting bitwise identical results from multiple runs of the same program, perhaps with different hardware resources or other changes that should ideally not change the answer. Many users depend on reproducibility for debugging or correctness. However, dynamic scheduling of parallel computing resources, combined with nonassociativity of floating point addition, makes attaining reproducibility a challenge even for simple operations like summing a vector of numbers, or more complicated operations like the Basic Linear Algebra Subprograms (BLAS). We describe an algorithm that computes a reproducible sum of floating point numbers, independent of the order of summation. The algorithm depends only on a subset of the IEEE Floating Point Standard 754-2008, uses just 6 words to represent a “reproducible accumulator,” and requires just one read-only pass over the data, or one reduction in parallel. New instructions based on this work are being considered for inclusion in the future IEEE 754-2018 floating-point standard, and new reproducible BLAS are being considered for the next version of the BLAS standard.
97 MATHEMATICS AND COMPUTING↗
Scalable Data Management, Analysis, and Visualization
This report is the entire final report for the SciDAC project authored by the whole team. OSU is part of the contributors to the report. This report is organized into sections and subsections, each covering an area of development and deployment of technologies applied to scientific applications of interest to the Department of Energy. Each sub-section includes: 1) a summary description of the research, development, and deployment carried out, the results and the extent to which the stated project objectives were met; 2) significant results, including major findings, developments, or conclusions; 3) products, such as publications and presentations, software developed, project website(s), technologies or techniques, inventions, awards, etc., and 4) conclusions of the projects and future directions for research, development, and deployment in this technology area.
97 MATHEMATICS AND COMPUTING↗
Flow Cells for Scalable Energy Conversion and Storage
This project is a response to current flow systems that are V-aqueous and not cost effective. It will hopefully enable high energy/ power density flow cells through rational materials and system design.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗