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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 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Reduced Hardware NOrec: A Safe and Scalable Hybrid Transactional Memory

Because of hardware TM limitations, software fallbacks are the only way to make TM algorithms guarantee progress. Nevertheless, all known software fallbacks to date, from simple locks to sophisticated versions of the NOrec Hybrid TM algorithm, have either limited scalability or weakened semantics. We propose a novel reduced-hardware (RH) version of the NOrec HyTM algorithm. Instead of an all-software slow path, in our RH NOrec the slow-path is a "mix" of hardware and software: one short hardware transaction executes a maximal amount of initial reads in the hardware, and the second executes all of the writes. Furthermore, this novel combination of the RH approach and the NOrec algorithm delivers the first Hybrid TM that scales while fully preserving the hardware's original semantics of opacity and privatization. Our GCC implementation of RH NOrec is promising in that it shows improved performance relative to all prior methods, at the concurrency levels we could test today.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

The SprayList: a scalable relaxed priority queue

High-performance concurrent priority queues are essential for applications such as task scheduling and discrete event simulation. Unfortunately, even the best performing implementations do not scale past a number of threads in the single digits. This is because of the sequential bottleneck in accessing the elements at the head of the queue in order to perform a DeleteMin operation. In this paper, we present the SprayList, a scalable priority queue with relaxed ordering semantics. Starting from a non-blocking SkipList, the main innovation behind our design is that the DeleteMin operations avoid a sequential bottleneck by ``spraying'' themselves onto the head of the SkipList list in a coordinated fashion. The spraying is implemented using a carefully designed random walk, so that DeleteMin returns an element among the first O(p log^3 p) in the list, with high probability, where p is the number of threads. We prove that the running time of a DeleteMin operation is O(log^3 p), with high probability, independent of the size of the list. Our experiments show that the relaxed semantics allow the data structure to scale for high thread counts, comparable to a classic unordered SkipList. As a result, we observe that, for reasonably parallel workloads, the scalability benefits of relaxation considerably outweigh the additional work due to out-of-order execution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Shepherding Metadata Through the Building Lifecycle

Many different digital representations of a building are produced over the course of its lifecycle. These representations contain the metadata required to support different stages of the building, from initial planning and design, to construction and commissioning, through operations, audits, retrofits and maintenance. However, because of differences in the semantics, structure and syntax of these representations, the metadata they contain is not interoperable. We present a novel method for leveraging these representations to create a unified, authoritative Brick metadata model for a building that can be continually maintained over the course of the building lifecycle. A simple synchronization protocol relays inferred Brick metadata from existing metadata sources such as gbXML, BuildingSync, Project Haystack and Modelica to a central integration server, which merges the metadata into a valid Brick model.

Fierro, Gabe↗

DOE OSTI2020

Interactive Metadata Integration with Brick

Many different digital representations of a building are produced over the course of its lifecycle. While these representations individually contain metadata required to support different stages of the building's lifecycle, they are largely not interoperable due to differences in structure, syntax and semantics. This impedes the development and deployment of data-driven applications providing fault detection and diagnosis, virtual metering or optimal control. [4] introduces a new platform for the continuous curation of a unified, Brick [1]-based metadata model that can be maintained throughout the building lifecycle. In this demonstration, we present a live proof-of-concept implementation of the platform with support for several metadata representations in the context of a simulated building lifecycle.

Fierro, Gabe↗

DOE OSTI2022

Giallar: push-button verification for the qiskit Quantum compiler

This paper presents Giallar, a fully-automated verification toolkit for quantum compilers. Giallar requires no manual specifications, invariants, or proofs, and can automatically verify that a compiler pass preserves the semantics of quantum circuits. To deal with unbounded loops in quantum compilers, Giallar abstracts three loop templates, whose loop invariants can be automatically inferred. To efficiently check the equivalence of arbitrary input and output circuits that have complicated matrix semantics representation, Giallar introduces a symbolic representation for quantum circuits and a set of rewrite rules for showing the equivalence of symbolic quantum circuits. With Giallar, we implemented and verified 44 (out of 56) compiler passes in 13 versions of the Qiskit compiler, the open-source quantum compiler standard, during which three bugs were detected in and confirmed by Qiskit. Furthermore, our evaluation shows that most of Qiskit compiler passes can be automatically verified in seconds and verification imposes only a modest overhead to compilation performance.

automated verification↗

DOE OSTI2015

Single Sided Messaging v. 0.6.6

Single-Sided Messaging (SSM) is a portable, multitransport networking library that enables applications to leverage potential one-sided capabilities of underlying network transports. It also provides desirable semantics that services for highperformance, massively parallel computers can leverage, such as an explicit cancel operation for pending transmissions, as well as enhanced matching semantics favoring large numbers of buffers attached to a single match entry. This release supports TCP/IP, shared memory, and Infiniband.

Curry, MatthewLeon↗

DOE OSTI2017

Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI)

In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with what they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).

Roberts, LarryW.↗

DOE OSTI2019

Ompparser

ompparser is a standalone and unified OpenMP parser, which is motivated by the facts that: 1) The differences in terms of syntax and semantics of OpenMP constructs between C/C++ and Fortran are minor. 2) Current OpenMP compilers often develop their own parsers, which represent redundant work. The features of ompparser include: 1) ompparser can be used standalone for static source code analysis, e.g. tools for semantics checking or similarity analysis between C/C++ and Fortran programs 2) omppaser can be integrated into an OpenMP compiler implementation can reduce the development efforts, and there is no need to create and maintain two separate parsers for C/C++ and Fortran. 3) ompparser provides a complete reference OpenMP grammar in the Backus-Naur Form that formally describes all the latest OpenMP language constructs. This will help users understand the rules and restriction of the OpenMP standard, which no longer contains a reference grammar in its recent versions.

Wang, Anjia↗

DOE OSTI2024

SaS4D Home Team UI (SaS4D-HT-UI) v1.0

The SaS4D Home Team UI (python) is a software to view and interact with different layers of 3D geometries and generate usable MCNP-style input file. It is used by the remote Home Team in providing guidance and building models of environments they have never seen in order to investigate threat object discovered at the Working Point. The UI visualizes a colorized mesh, a semantic labelled mesh, and a semantic labelled probability mesh of the scanned environment as well as individual water-tight material-labeled objects. It allows for manipulation and re-processing of these objects. The UI also contains measurement tools to facilitate better MCNP input file generation in the manipulation workflow. The software is a key component in ensuring the Home Team has prompt awareness of the Working Point.

Chen, Xin↗

DOE OSTI2014

Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of nonKEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗

DOE OSTI2022

Towards a Stronger Foundation: Digitizing Commercial Buildings with Brick to Enable Portable Advanced Applications

Most large commercial buildings have digital controls for their heating, ventilation, and air-conditioning (HVAC) and lighting systems with the potential to implement advanced control strategies and data analytics. However, advanced control strategies and data analytics are rarely deployed at scale due to non-standard naming conventions and heterogenous building configurations. Semantic metadata standards, like Brick, show promise to proliferate these applications across many buildings, but they have not been widely adopted by industry due to barriers such as perceived risk and unfamiliarity with the technology. This paper describes the workflow we established and evaluated while using it to develop over ten Brick models of existing buildings. Through this process, we observed that digitizing existing commercial buildings is a cost and labor-intensive effort in which understanding the buildings’ data streams is the major bottleneck. Yet, we conclude this investment is worthwhile since various use case applications such as fault detection and diagnostics, thermal comfort analysis, and HVAC control optimization can utilize the same Brick model. The paper also explores the challenges and lessons learned we encountered while creating these data models, such as: 1) difficulties in finding metadata descriptions and relationships for existing buildings; 2) handling missing concepts in the schema needed to model a building; 3) lack of guidance on how to structure the data model or how much detail to include; 4) unfamiliarity with technologies, which makes the learning curve steep for applications developers. Finally, we also describe future directions for semantic metadata research and development to make such transformative technologies more accessible to practitioners.

Roa, Carlos Duarte↗

DOE OSTI2026

FAIRLinked: Data FAIRification Tools for Materials Data Science

FAIRLinked is a software package created to support the FAIRification of materials science data, ensuring proper alignment with FAIR principles: Findable, Accessible, Interoperable, and Reusable. It is built to be compatible with MDS-Onto, an ontology designed to capture the semantics of various types of materials data, enabling integration and sharing across different research workflows. The package is subdivided into three subpackages: InterfaceMDS, RDFTableConversion, and QBWorkflow. The first subpackage, InterfaceMDS allows users to search for terms using either string search or various filters, explore different domains and subdomains, and add terms to MDS-Onto. RDFTableConversion is used for serialization and deserialization of data from CSV into JSONLDs and vice versa in a way that captures the semantics of the data using MDS-Onto. Lastly, QBWorkflow is a serialization and deserialization workflow that incorporates RDF Data Cube vocabulary, useful for working with multidimensional datasets. By offering these packages, FAIRLinked lowers the barrier of creating FAIR, machine-actionable data for researchers in the materials science community.

FAIR↗

DOE OSTI2013

Nuclear Fuel Cycle Reasoner: PNNL FY13 Report

In Fiscal Year 2012 (FY12) PNNL implemented a formal reasoning framework and applied it to a specific challenge in nuclear nonproliferation. The Semantic Nonproliferation Analysis Platform (SNAP) was developed as a preliminary graphical user interface to demonstrate the potential power of the underlying semantic technologies to analyze and explore facts and relationships relating to the nuclear fuel cycle (NFC). In Fiscal Year 2013 (FY13) the SNAP demonstration was enhanced with respect to query and navigation usability issues.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Orchestrating Distributed Resource Ensembles for Petascale Science

Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstract API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

UPC Language and Library Specifications (Version 1.3)

UPC is an explicitly parallel extension to the ISO C 99 Standard. UPC follows the partitioned global address space programming model. This document is the formal specification for the UPC language and library syntax and semantics, and supersedes prior specification version 1.2 (LBNL-59208).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning.

Sandia has approached the analysis of big datasets with an integrated methodology that uses computer science, image processing, and human factors to exploit critical patterns and relationships in large datasets despite the variety and rapidity of information. The work is part of a three-year LDRD Grand Challenge called PANTHER (Pattern ANalytics To support High-performance Exploitation and Reasoning). To maximize data analysis capability, Sandia pursued scientific advances across three key technical domains: (1) geospatial-temporal feature extraction via image segmentation and classification; (2) geospatial-temporal analysis capabilities tailored to identify and process new signatures more efficiently; and (3) domain- relevant models of human perception and cognition informing the design of analytic systems. Our integrated results include advances in geographical information systems (GIS) in which we discover activity patterns in noisy, spatial-temporal datasets using geospatial-temporal semantic graphs. We employed computational geometry and machine learning to allow us to extract and predict spatial-temporal patterns and outliers from large aircraft and maritime trajectory datasets. We automatically extracted static and ephemeral features from real, noisy synthetic aperture radar imagery for ingestion into a geospatial-temporal semantic graph. We worked with analysts and investigated analytic workflows to (1) determine how experiential knowledge evolves and is deployed in high-demand, high-throughput visual search workflows, and (2) better understand visual search performance and attention. Through PANTHER, Sandia's fundamental rethinking of key aspects of geospatial data analysis permits the extraction of much richer information from large amounts of data. The project results enable analysts to examine mountains of historical and current data that would otherwise go untouched, while also gaining meaningful, measurable, and defensible insights into overlooked relationships and patterns. The capability is directly relevant to the nation's nonproliferation remote-sensing activities and has broad national security applications for military and intelligence- gathering organizations.

58 GEOSCIENCES↗

DOE OSTI2014

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↗