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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Real-time moving platform management system

Systems and methods are disclosed including a moving platform system suitable for mounting and use on a moving platform for communicating in real-time, comprising: a position system monitoring location of the moving platform and generating a sequence of time-based position data; a non-line of sight communication system; a high-speed line of sight communication system; and a computer system monitoring an availability of the non-line of sight communication system and the high-speed line of sight communication system and initiating connections when the non-line of sight communication system and the high-speed line of sight communication system are available, and receiving the sequence of time-based position data and transmitting the sequence of time-based position data via the at least one of the currently available non-line of sight communication system and the high-speed line of sight communication system.

Giuffrida, Frank D.↗
DOE OSTI2024

Guided cold atom inertial sensors with membrane integrated photonics on atom trap integrated platforms

A guided cold-atom inertial sensor system comprises an atom trap integrated platform, a laser system, a magnetic field system, a control system, and a computing system. The laser system and magnetic field system are adapted to form a magneto-optical trap (MOT) about a suspended waveguide of the atom trap integrated platform made of membrane integrated photonics. After loading cold atoms from a MOT, the photonic atom trap integrated platform generates one-dimensional guided atoms with an evanescent field optical dipole trap (EF-ODT) along the optical waveguide to create guided atomic accelerometers/gyroscopes. Motion of atomic wavepackets in a superposition state is created along the guided atom geometry by way of state-dependent momentum kicks. The light-pulse sequence of guided atom interferometry splits, redirects, and recombines atomic wavepackets, which allows measurement of atom interference fringes sensitive to inertial forces via a probe laser.

Lee, Jongmin↗
DOE OSTI2025

HPDR: High-Performance Portable Scientific Data Reduction Framework

The rapid growth in scientific data generation is outpacing advancements in computing systems necessary for efficient storage, transfer, and analysis, particularly in the context of exascale computing. With the deployment of first-generation exascale computing systems and next-generation experimental facilities, this gap is widening and necessitates effective data reduction techniques to manage enormous data volumes. Over the past decade, various data reduction methods, including lossless compression, error-controlled lossy compression, and data refactoring, have been developed to accelerate I/O in scientific workflows. Despite significant reductions in data volume, these methods introduce considerable computational overhead, which can become the new bottleneck in data processing. To mitigate this, GPU-accelerated data reduction algorithms have been introduced. However, challenges remain in their integration into exascale workflows, including limited portability across different GPU architectures, substantial memory transfer overhead, and reduced scalability on dense multi-GPU systems. To address these challenges, we propose HPDR, a high-performance and portable data reduction framework. HPDR is designed to enable the execution of state-of-the-art reduction algorithms across diverse processor architectures while reducing memory transfer overhead to 2.3 % of the original, resulting in up to 3.5× faster throughput compared to existing solutions. It also achieves up to 96% of the theoretical speedup in multi-GPU settings. In addition, evaluations on accelerating I/O operations at scale up to 1,024 nodes of the Frontier supercomputer demonstrate that HPDR can achieve up to 103 TB/s reduction throughput, providing up to 4× acceleration in parallel I/O performance compared to existing data reduction routines. This work highlights the potential of HPDR to significantly enhance data reduction efficiency in exascale computing environments.

Chen, Jieyang [University of Oregon]↗
DOE OSTI2021

Malicious activity detection in a memory

A method and apparatus for monitoring a volatile memory in a computer system. Samples of compressed data from locations in the volatile memory in the computer system are read. Data in the volatile memory is reconstructed using the samples of compressed data. The data is an image of the volatile memory. The image enables determining whether an undesired process is present in the volatile memory.

Wheeler, Jason W.↗
DOE OSTI2021

FY 2021 High Performance Computing Overall Systems Availability

INL HPC capabilities were utilized by individuals at universities, industry, and government laboratories for a wide range of research and engineering activities between October 1, 2020 and September 30, 2021. The HPC systems themselves experienced minimal downtime over the course of the fiscal year. Most downtime was planned to apply critical security patches to system software. The most serious of the unplanned downtime events occurred due to maintenance on the Kohler backup generator in July. Users were kept notified of all events, both planned and unplanned, via 36 total email notifications in FY-21. The INL HPC systems continue to provide high availability for collaboration and innovation in nuclear energy systems research.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Opportunities for nonvolatile memory systems in extreme-scale high-performance computing

For extreme-scale high-performance computing systems, system-wide power consumption has been identified as one of the key constraints moving forward, where DRAM main memory systems account for about 30 to 50 percent of a node's overall power consumption. As the benefits of device scaling for DRAM memory slow, it will become increasingly difficult to keep memory capacities balanced with increasing computational rates offered by next-generation processors. However, several emerging memory technologies related to nonvolatile memory (NVM) devices are being investigated as an alternative for DRAM. Moving forward, NVM devices could offer solutions for HPC architectures. Researchers are investigating how to integrate these emerging technologies into future extreme-scale HPC systems and how to expose these capabilities in the software stack and applications. In addition, current results show several of these strategies could offer high-bandwidth I/O, larger main memory capacities, persistent data structures, and new approaches for application resilience and output postprocessing, such as transaction-based incremental checkpointing and in situ visualization, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

rvGAHP: push-based job submission using reverse SSH connections. In: WORKS '17 Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science, Article No. 3

Computational science researchers running large-scale scientific workflow applications often want to run their workflows on the largest available compute systems to improve time to solution. Workflow tools used in distributed, heterogeneous, high performance computing environments typically rely on either a push-based or a pull-based approach for resource provisioning from these compute systems. However, many large clusters have moved to two-factor authentication for job submission, making traditional automated push-based job submission impossible. On the other hand, pull-based approaches such as pilot jobs may lead to increased complexity and a reduction in node-hour efficiency. In this paper, we describe a new, efficient approach based on HTCondor-G called reverse GAHP (rvGAHP) that allows us to push jobs using reverse SSH submissions with better efficiency than pull-based methods. We successfully used this approach to perform a large probabilistic seismic hazard analysis study using SCEC's CyberShake workflow in March 2017 on the Titan Cray XK7 hybrid system at Oak Ridge National Laboratory.

Callaghan, Scott↗
DOE OSTI2016

Reproduction of the Yucca Mountain Project TSPA-LA Uncertainty and Sensitivity Analyses and Preliminary Upgrade of Models

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014) and Hadgu et al. (2015). The TSPA computing hardware (CL2014) and storage system described in Hadgu et al. (2015) were used for the current analysis. One floating license of GoldSim with Versions 9.60.300, 10.5 and 11.1.6 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA-type analysis on the server cluster. The current tasks included verification of the TSPA-LA uncertainty and sensitivity analyses, and preliminary upgrade of the TSPA-LA from Version 9.60.300 to the latest version 11.1. All the TSPA-LA uncertainty and sensitivity analyses modeling cases were successfully tested and verified for the model reproducibility on the upgraded 2014 server cluster (CL2014). The uncertainty and sensitivity analyses used TSPA-LA modeling cases output generated in FY15 based on GoldSim Version 9.60.300 documented in Hadgu et al. (2015). The model upgrade task successfully converted the Nominal Modeling case to GoldSim Version 11.1. Upgrade of the remaining of the modeling cases and distributed processing tasks will continue. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Holistic Measurement Driven Resilience: Combining Operational Fault and Failure Measurements and Fault Injection for Quantifying Fault Detection, Propagation and Impact. Final report

For HPC systems to date, application resilience to faults and failures has been accomplished by the brute- force method of checkpoint/restart, which allows an application to make forward progress in the face of system and application faults, errors, and failures independent of root cause or end result. It has remained the primary resilience mechanism because we lack a way to identify faults and anticipate consequences early enough to take meaningful mitigating action. However, checkpoint/restart implementations put a tremendous burden on system resources and on the applications themselves and is becoming less feasible at scale. Because we have not yet operated at scales at which checkpoint/restart fails to provide forward progress, despite increasing costs, vendors have had little motivation to provide the instrumentation necessary for early identification of faults and failures. However, as we move from petascale to exascale, component mean time to failure (MTTF) will render the existing techniques ineffectual and/or too expensive. Furthermore, fault recovery mechanisms such as failover and/or error correction introduce performance inconsistency. Instrumentation allowing early indication of problems and tools to enable use of such information by systems, operating systems, and applications offer an alternative, more scalable and less costly solution. In the HMDR project, we built on our experience and expertise developed and accumulated over years of research on design, monitoring, measurement, and assessment of resilient computing systems. Analysis of field data on the current and past generations of extreme-scale systems revealed several challenges that, if not addressed in increasingly larger and more complex systems, may hinder the effectiveness of future exascale computing systems. Specifically, i) file systems and interconnects in current-generation large-scale systems already operate at the margins of resiliency, including consistent performance, and may not scale to larger deployments; ii) automated, software-based failover mechanisms are frequently inadequate and can introduce wider failures, such that failures during recovery may lead to system/application failures, including system-wide outages; and iii) silent data corruption represents a critical fault mode and will require efficient detection mechanisms if next-generation applications are to take full advantage of exascale hardware. To address the above challenges, we assembled a team of world-renowned experts in resilient extreme- scale computing from the University of Illinois (Electrical and Computer Engineering, Computer Science, and NCSA), SNL, LANL, NERSC, and Cray. Our team includes representatives from centers that house many of the largest HPC resources in the world, both today and over the coming years. The team has a unique track record of research in i) system and application failure characterization based on the analysis of field data, ii) data-driven design of fault/error detection mechanisms, and iii) experimental characterization of system/application resiliency. The team includes system owners/operators who provide continuous data collection and access and ensure installation of appropriate analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Neuromorphic computing architecture with dynamically accessible contexts

Various technologies pertaining to allocating computing resources of a neuromorphic computing system are described herein. Subgraphs of a neural algorithm graph to be executed by the neuromorphic computing system are identified. The subgraphs are each executed by a group of neuron circuits serially. Output data generated by execution of the subgraphs are provided to the same or a second group of neuron circuits at a same time or with associated timing data indicative of a time at which the output data was generated. The same or second group of neuron circuits performs one or more processing operations based upon the output data.

Aimone, James Bradley↗
DOE OSTI2019

Hyperdimensional visualization tool

A method and apparatus for displaying data. Independent data in the data is displayed by a computer system in a two-dimensional graph in a graphical user interface on a display system. Dimensions of dependent data in the data that are dependent on the independent data are displayed by the computer system in the two-dimensional graph using graphical indicators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Automatic Code Generation for High-Performance Graph Algorithms

Graph problems are common across fields of scientific computing and social sciences. However, despite their importance, implementing graph algorithms effectively on modern computing systems is a challenging task that requires significant programming effort and generally results in customized implementations. Current computing and memory hierarchies are not architected for irregular computations resulting in challenges for graph algorithms to achieve high performance on those architectures. In this paper, we present GraphX, a novel compiler framework and DSL designed to simplify the development of efficient graph algorithms and achieve high performance on modern computing systems. GraphX consists of a DSL for efficient implementation of graph algorithms, various optimizations, such as support for sparse linear algebra and workspace transformations, optimized graph primitives, including semiring and masking, and a high-performance code generation engine. Using GraphX, users can implement graph algorithms using a semantically-rich language with graph-oriented operators. GraphX uses these semantics to automatically generate efficient code for target architectures, increasing performance and portability across architectures. The composable nature of GraphX makes it possible to extend the set of optimizations and architectures without modifying the source code. We demonstrate GraphX outperforms state-of-the-art graph libraries, such as LAGraph, up to $3.7 speedup in semiring operations, $2.19 speedup in an important sparse computational kernel, and $9.05 speedup in graph processing algorithms.

compiler, graph algorithms, semiring, masking, wor↗
DOE OSTI2015

Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable

Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS based technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Turbulent Flow Simulation at the Exascale: Opportunities and Challenges Workshop: August 4-5, 2015, Washington, D.C.

This report details the impact exascale will bring to turbulent-flow simulations in applied science and technology. The need for accurate simulation of turbulent flows is evident across the DOE applied-science and engineering portfolios, including combustion, plasma physics, nuclear-reactor physics, wind energy, and atmospheric science. The workshop brought together experts in turbulent-flow simulation, computational mathematics, and high-performance computing. Building upon previous ASCR workshops on exascale computing, participants defined a research agenda and path forward that will enable scientists and engineers to continually leverage, engage, and direct advances in computational systems on the path to exascale computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Asynchronous cache flushing

Proactive flush logic in a computing system is configured to perform a proactive flush operation to flush data from a first memory in a first computing device to a second memory in response to execution of a non-blocking flush instruction. Reactive flush logic in the computing system is configured to, in response to a memory request issued prior to completion of the proactive flush operation, interrupt the proactive flush operation and perform a reactive flush operation to flush requested data from the first memory to the second memory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Enhancing obfuscation of digital content through use of linear error correction codes

Technologies related to enhancing security of digital content are described. Linear error correction codes (LECCs) are employed for dual purposes: 1) to obfuscate digital content; and 2) to verify integrity of the digital content. A transmitter computing system obfuscates digital content based upon an obfuscation protocol, wherein the obfuscated digital content includes an LECC. A receiver computing system deobfuscates the digital content by performing the inverse of the obfuscation protocol.

Corral, Celestino A.↗
DOE OSTI2016

Non-harmful insertion of data mimicking computer network attacks

Non-harmful data mimicking computer network attacks may be inserted in a computer network. Anomalous real network connections may be generated between a plurality of computing systems in the network. Data mimicking an attack may also be generated. The generated data may be transmitted between the plurality of computing systems using the real network connections and measured to determine whether an attack is detected.

97 MATHEMATICS AND COMPUTING↗