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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 487 records · Page 27

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Efficient Active Message RMA in GASNet Using a Target-Side Reassembly Protocol (Extended Abstract)

GASNet is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models on future exascale machines. This paper investigates strategies for efficient implementation of GASNet’s “AM Long” API that couples an RMA (Remote Memory Access) transfer with an Active Message (AM) delivery. We discuss several network-level protocols for AM Long and propose a new target-side reassembly protocol. We present a microbenchmark evaluation on the Cray XC Aries network hardware. The target-side reassembly protocol on this network improves AM Long end-to-end latency by up to 33%, and the effective bandwidth by up to 49%, while also enabling asynchronous source completion that drastically reduces injection overheads. The improved AM Long implementation for Aries is available in GASNet-EX release v2019.9.0 and later.

Hargrove, P↗

DOE OSTI2018

GASNet-EX: A High-Performance, Portable Communication Library for Exascale

Partitioned Global Address Space (PGAS) models, typified by such languages as Unified Parallel C (UPC) and Co-Array Fortran, expose one-sided communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity. GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. We describe and evaluate several features and enhancements that have been introduced to address the needs of modern client systems. Microbenchmark results demonstrate the RMA performance of GASNet-EX is competitive with several MPI-3 implementations on current HPC systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Calibration of the 2007–2017 record of Atmospheric Radiation Measurements cloud radar observations using CloudSat

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurements (ARM) facility has been at the forefront of millimeter-wavelength radar development and operations since the late 1990s. The operational performance of the ARM cloud radar network is very high; however, the calibration of the historical record is not well established. Here, a well-characterized spaceborne 94 GHz cloud profiling radar (CloudSat) is used to characterize the calibration of the ARM cloud radars. The calibration extends from 2007 to 2017 and includes both fixed and mobile deployments. Collectively, over 43 years of ARM profiling cloud radar observations are compared to CloudSat and the calibration offsets are reported as a function of time using a sliding window of 6 months. The study also provides the calibration offsets for each operating mode of the ARM cloud radars. Overall, significant calibration offsets are found that exceed the uncertainty of the technique (1–2 dB). The findings of this study are critical to past, ongoing, and planned studies of cloud and precipitation and should assist the DOE ARM to build a legacy decadal ground-based cloud radar dataset for global climate model validation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

ISIS and META projects

The ISIS project has developed a new methodology, virtual synchony, for writing robust distributed software. High performance multicast, large scale applications, and wide area networks are the focus of interest. Several interesting applications that exploit the strengths of ISIS, including an NFS-compatible replicated file system, are being developed. The META project is distributed control in a soft real-time environment incorporating feedback. This domain encompasses examples as diverse as monitoring inventory and consumption on a factory floor, and performing load-balancing on a distributed computing system. One of the first uses of META is for distributed application management: the tasks of configuring a distributed program, dynamically adapting to failures, and monitoring its performance. Recent progress and current plans are reported.

Birman, Kenneth↗

NASA NTRS1991

Space data systems: Advanced flight computers

The technical objectives are to develop high-performance, space-qualifiable, onboard computing, storage, and networking technologies. The topics are presented in viewgraph form and include the following: technology challenges; state-of-the-art assessment; program description; relationship to external programs; and cooperation and coordination effort.

Benz, Harry F.↗

NASA NTRS1991

Space data systems: Special purpose flight processors

The technical objectives are to develop high-performance, space-qualifiable, onboard computing, storage, and networking technologies. The topics are presented in viewgraph form and include the following: justification; approach; program description; state-of-the-art assessment; technology challenges; and relationship to external programs.

Henry, Mike↗

DOE OSTI2024

B-Biz: Building Business Network

The Building Business Network (B-Biz) aims to provide high-performance building technology solutions to underserved customers by collaborating with local small businesses that provide and service high-performance building technologies in communities with the lowest rates of adoption.

BTO↗

NASA NTRSDate not supplied

Open-source Wireless Sensor Network (Wi-Se Net) for Flexible Deployment

Wireless sensors, especially if battery powered, have a number of advantages over wired sensors for flexible or temporary diagnostic deployment in a field or lab setting. Recent advances in wireless technology and microprocessor boards have produced a variety of inexpensive off-the shelf chips which can communicate wirelessly with simple protocols. This paper describes the design and implementation of a highly customizable wireless sensor network (called WiSe Net) using inexpensive open-source hardware components as wireless nodes. These wireless sensor nodes can transmit data at a rate <250 Hz, can be battery powered, and have a small footprint (2x5 cm). In addition, a preliminary over-the-air programming system was developed to allow for simple wireless configuration when active. The network performance was demonstrated by taking distributed and electrically isolated temperature measurements on a high-voltage lab apparatus. Although this test case is in a laboratory setting, this network architecture could be easily repurposed for various other forms of monitoring

Wireless Sensor Network↗

NASA NTRSDate not supplied

Open-source Wireless Sensor Network (Wi-Se Net) for Flexible Deployment

Wireless Sensor Network↗

NASA NTRSDate not supplied

Open-source Wireless Sensor Network (Wi-Se Net) for Flexible Deployment

Wireless sensors, especially if battery powered, have a number of advantages over wired sensors for flexible or temporary diagnostic deployment in a field or lab setting. Recent advances in wireless technology and microprocessor boards have produced a variety of inexpensive off-the shelf chips which can communicate wirelessly with simple protocols. This paper describes the design and implementation of a highly customizable wireless sensor network (called Wi-Se Net) using inexpensive open-source hardware components as wireless nodes. These wireless sensor nodes can transmit data at a rate <250 Hz, can be battery powered, and have a small footprint (2x5 cm). In addition, a preliminary over-the-air programming system was developed to allow for simple wireless configuration when active. The network performance was demonstrated by taking distributed and electrically isolated temperature measurements on a high-voltage lab apparatus. Although this test case is in a laboratory setting, this network architecture could be easily repurposed for various other forms of monitoring.

Wireless Sensor Network↗

DOE OSTI2016

An Asynchronous Task-based Fan-Both Sparse Cholesky Solver

Systems of linear equations arise at the heart of many scientific and engineering applications. Many of these linear systems are sparse; i.e., most of the elements in the coefficient matrix are zero. Direct methods based on matrix factorizations are sometimes needed to ensure accurate solutions. For example, accurate solution of sparse linear systems is needed in shift-invert Lanczos to compute interior eigenvalues. The performance and resource usage of sparse matrix factorizations are critical to time-to-solution and maximum problem size solvable on a given platform. In many applications, the coefficient matrices are symmetric, and exploiting symmetry will reduce both the amount of work and storage cost required for factorization. When the factorization is performed on large-scale distributed memory platforms, communication cost is critical to the performance of the algorithm. At the same time, network topologies have become increasingly complex, so that modern platforms exhibit a high level of performance variability. This makes scheduling of computations an intricate and performance-critical task. In this paper, we investigate the use of an asynchronous task paradigm, one-sided communication and dynamic scheduling in implementing sparse Cholesky factorization (symPACK) on large-scale distributed memory platforms. Our solver symPACK relies on efficient and flexible communication primitives provided by the UPC++ library. Performance evaluation shows good scalability and that symPACK outperforms state-of-the-art parallel distributed memory factorization packages, validating our approach on practical cases.

Jacquelin, Mathias↗

DOE OSTI2018

On Data Transfers Over Wide-Area Dedicated Connections

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which show concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.

Rao, Nageswara S.↗

DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗

NASA NTRS1990

High performance processors for real-time flight simulation

In order to meet the requirements of the NASA Langley Research Center for simulating the increased complexity and higher performance of modern aircraft, a flight simulation computing system with very high scalar performance is needed. The requirements and proposed response, probable areas of difficulty, planned implementation, and current status and plans are reviewed. A solution utilizing centralized minisupercomputers coupled with a proven real-time network technology will provide engineers and research scientists with the tools required for high-performance flight simulation. Subsequent to testing and verification of the initial simulation, general-purpose configuration management software with a nonconfiguration dependent serial highway driver software will be integrated to support any arbitrary combination of simulation sites.

Cleveland, Jeff I., II↗

DOE OSTI2014

Grids, virtualization, and clouds at Fermilab

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture and the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). Lastly, this work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Machine learning-accelerated discovery of heat-resistant polysulfates for electrostatic energy storage

The development of heat-resistant dielectric polymers that withstand intense electric fields at high temperatures is critical for electrification. Balancing thermal stability and electrical insulation, however, is exceptionally challenging as these properties are often inversely correlated. A traditional intuition-driven polymer design approach results in a slow discovery loop that limits breakthroughs. Here we present a machine learning-driven strategy to rapidly identify high-performance, heat-resistant polymers. A trustworthy feed-forward neural network is trained to predict key proxy parameters and down select polymer candidates from a library of nearly 50,000 polysulfates. The highly efficient and modular sulfur fluoride exchange click chemistry enables successful synthesis and validation of selected candidates. A polysulfate featuring a 9,9-di(naphthalene)-fluorene repeat unit exhibits excellent thermal resilience and achieves ultrahigh discharged energy density with over 90% efficiency at 200 °C. Its exceptional cycling stability underscores its promise for applications in demanding electrified environments.

Li, He↗

DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗

DOE OSTI2024

Significantly Promoting the Thermal Conductivity and Machinability of Negative Thermal Expansion Alloy via In Situ Precipitation of Copper Networks

Rapid advancements in electronic devices yield an urgent demand for high-performance electronic packaging materials with high thermal conductivity, low thermal expansion, and great mechanical properties. However, it is a great challenge for current design philosophies to fulfill all the requirements simultaneously. Here, an effective strategy is proposed for significantly promoting the thermal conductivity and machinability of negative thermal expansion alloy (Zr,Nb)Fe 2 through eutectic precipitation of copper networks. The eutectic dual-phase alloy exhibits an isotropic chips-matched thermal expansion coefficient and a thermal conductivity enhancement exceeding 200% compared with (Zr,Nb)Fe 2 , along with an ultimate compressive strength of 550 MPa. The addition of copper reorganizes the composition of (Zr,Nb)Fe 2 , which smooths the magnetic transition and shifts it toward higher temperature, resulting in linear low thermal expansion in a wide temperature range. The highly fine eutectic copper lamellae construct high thermal conductivity networks within (Zr,Nb)Fe 2 , serving as highways for heat transfer electrons and phonons. The in situ forming of eutectic copper lamellae also facilitates the mechanical properties by enhancing interfacial bonding and bearing additional stress after yielding of (Zr,Nb)Fe 2 . This work provides a novel strategy for promoting thermal conductivity and mechanical properties of negative thermal expansion alloys via eutectic precipitation of copper networks.

36 MATERIALS SCIENCE↗