Search NASA⌕ Search

SEARCH · Search NASA

Results for “concurrent programs”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Smart Matrix Development for Direct Carbonate Fuel Cell

FCE’s (FuelCell Energy, Inc.) SureSourceTM products based on high-temperature internal-reforming direct carbonate fuel cell (DFC®) technology are striving to meet growing worldwide demand for high-efficiency ultra-clean power for on-site electric and combined heat and power (CHP) generation. It promises ~20% higher energy conversion efficiency than existing technologies and its large-scale deployment would help to reduce GHG (Green House Gas) emission. In this program, FCE, teamed with University of Connecticut (UConn) and Illinois Institute of Technology (IIT), successfully developed an innovative electrolyte matrix (dubbed smart matrix since it promises higher power output, longer service life, and cost reduction gains concurrently) to enable the products to worldwide deployment. The electrolyte membrane (matrix) holds a very important key to fulfill these promises. The matrix, a porous microstructure consisting mainly of ultra-fine sub-micron α-LiAlO 2 powders sandwiched between two electrodes, immobilizes liquid electrolyte, isolates fuel from oxidant and facilitates ionic transport. However, faster coarsening of α-LiAlO 2 at the reducing anode side lowers capillary electrolyte-retention and eventually leads to matrix drying, limiting stack service life. This program, spanning over 3.5 years, successfully developed a high-yield cost-effective commercial-ready smart matrix with robust and stable fine-pore microstructure to enable the SureSource plants meeting DOE 2020 targets for CHP distributed generation fuel cell systems. Fundamental coarsening mechanism was established by investigating in detail the effects of electrolyte chemistry, powder morphology, powder purity, electrolyte chemistry, gas atmosphere and temperature. More stable powders with higher crystallinity, less surface disorder, less metastable impurities, less agglomeration and more uniform particle-size distribution have improved stability. FCE devised an innovative cost-effective additive approach to disrupt the fundamental coarsening process to enhance stability. The smart matrix design was validated in numerous long-term accelerated single cells and several 30kW technology stacks, many operated for >5,000 hours. Manufacturing process was successfully optimized to produce high-yield full-area (1 m 2 ) product-size smart matrices. Field deployment has been initiated. Successful development of this innovative smart matrix enables a quantum jump in useful life (100%) and power output (>20%). These improvements may project to >20% lower COE (Cost of Electricity) making the SureSource highly competitive with U.S. grid electricity cost leading to large-scale deployment, realizing the U.S. Government’s energy, environment, and economic agenda.

03 NATURAL GAS↗
DOE OSTI2015

eXascale PRogramming Environment and System Software (XPRESS)

Exascale systems, with a thousand times the compute capacity of today’s leading edge petascale computers, are expected to emerge during the next decade. Their software systems will need to facilitate the exploitation of exceptional amounts of concurrency in applications, and ensure that jobs continue to run despite the occurrence of system failures and other kinds of hard and soft errors. Adapting computations at runtime to cope with changes in the execution environment, as well as to improve power and performance characteristics, is likely to become the norm. As a result, considerable innovation is required to develop system support to meet the needs of future computing platforms. The XPRESS project aims to develop and prototype a revolutionary software system for extreme-­scale computing for both exascale and strong­scaled problems. The XPRESS collaborative research project will advance the state-­of-­the-­art in high performance computing and enable exascale computing for current and future DOE mission-­critical applications and supporting systems. The goals of the XPRESS research project are to: A. enable exascale performance capability for DOE applications, both current and future, B. develop and deliver a practical computing system software X-­stack, OpenX, for future practical DOE exascale computing systems, and C. provide programming methods and environments for effective means of expressing application and system software for portable exascale system execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Roofline scaling trajectories: A method for parallel application and architectural performance analysis

The end of Dennard scaling signaled a shift in HPC supercomputer architectures from systems built from single-core processor architectures to systems built from multicore and eventually manycore architectures. This transition substantially complicated performance optimization and analysis as new programming models were created, new scaling methodologies deployed, and on-chip contention became a bottleneck to performance. Existing distributed memory performance models like logP and logGP were unable to capture this contention. The Roofline model was created to address this contention and its interplay with locality. However, to date, the Roofline model has focused on full-node concurrency. In this paper, we extend the Roofline model to capture the effects of concurrency on data locality and on-chip contention. We demonstrate the value of this new technique by evaluating the NAS parallel benchmarks on both multicore and manycore architectures under both strong-And weak-scaling regimes. In order to quantify the interplay between programming model and locality, we evaluate scaling under both the OpenMP and flat MPI programming models.

Ibrahim, K↗
DOE OSTI2022

HOMP (Hybrid Operation and Maintenance Platform) [SWR-22-81]

The HOMP software module is contained within NREL's Hybrid Optimization and Performance Platform (HOPP) at this URL: https://github.com/NREL/HOPP/tree/feature/HOMP. HOMP is a python-based software module which can be used concurrently with the Hybrid Optimization and Performance Platform (HOPP) to model, simulate, and optimize degradation, reliability, and operations and maintenance of hybrid power plant components. The program currently models lithium ion battery, PEM electrolyzer, wind turbine, and solar PV array components, which enables users to understand the design and operation tradeoffs of hybrid power plants. For instance, HOMP enables users to answer questions like: how large does a battery bank need to be to achieve optimal charge/discharge rates for performance and reliability? How does plant design change for different objectives (e.g., profit versus resilience)? Under what conditions is it better to produce electricity versus hydrogen? How do we optimally control hybrid power plants to reduce downtime and increase performance?

Clark, Caitlyn↗
DOE OSTI2015

A Parallel Computing Framework for Finding the Supported Solutions to a Biobjective Network Optimization Problem

Abstract Solving multi‐objective combinatorial optimization problems can quickly become computationally challenging when applied to large networks generated from big data. Present‐day first‐rate Mixed Integer Programming (MIP) solvers have parallelism built‐in to take advantage of multicore architectures; but specialized network optimization algorithms that can often solve graph problems more efficiently than a general MIP solver are typically programmed serially. Thus, these network algorithm implementations do not take full advantage of modern multicore computer capabilities. Many parallel computing languages include a fork/join framework into their concurrency packages that allow for simple conversion of recursive serial algorithms to operate in parallel without having to use complicated low‐level message‐passing interfaces. Fork/join is particularly well suited to divide and conquer algorithms such as Non‐Inferior Set Estimation (NISE) method for computing the supported Pareto front of a multi‐objective optimization problem. This work develops a simple general parallel NISE (pNISE) implementation using the Java 7 concurrency tools, and then offers results from a specific implementation of solving a bi‐objective shortest path problem. The results indicate that this method is capable of sizeable speed‐ups on both small‐scale personal computers as well as large‐scale shared memory supercomputers. Finally, other network problems suitable to this method are discussed, including multi‐objective variants of the minimum spanning tree problem, transportation problem, assignment problem, maximum flow problem, and the minimum‐cost flow problem. Copyright © 2015 John Wiley & Sons, Ltd.

Medrano, Fernando Antonio↗
DOE OSTI2020

Hanford Site Rare Plant Monitoring Report for Calendar Year 2015

In 2015, two separate rare plant monitoring efforts occurred on the portion of the Hanford Site managed by the U.S. Department of Energy (DOE) (referred to herein as Central Hanford). 1. Upland plants of conservation concern were inventoried concurrently with efforts to map plant communities on Central Hanford. Plants were selected based on 2015 status with the Washington State Department of Natural Resources Natural Heritage Program (WNHP) listings, which are summarized in the bullets below. This effort was led by Mission Support Alliance (MSA) and subcontracted personnel from SEE Botanical Consulting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Research Performance Progress Report - DOE Solar Program, Soft Costs, National Lab Projects: Promotion of PV Soft Cost Reductions in the Southeastern US

Beginning in 2014, the installed solar capacity in South Carolina (SC) grew from less than 20 megawatts to more than 300 megawatts today. Concurrently, the number of customer-sited, load-centered solar generation is expected to grow from less than 500 statewide to as many as 10,000 by 2021. This growth is the direct result of a landmark state policy initiative, Act 236, passed by the South Carolina General Assembly and signed into law by the Governor in June of 2014. Today, local policy makers in South Carolina are ill-equipped to handle the onslaught of solar permitting and zoning requests expected to come with such quick growth of an emerging market. Similarly, the state’s building inspectors, first responders, and tax assessors know little about photovoltaic (PV) technology and best practices. Finally, South Carolina’s workforce and workforce trainers continue to be underprepared to benefit from the tremendous opportunity created by the passage of Act 236. Each of these deficits in knowledge of and preparedness for solar PV translates into higher “soft costs” of installed solar PV in South Carolina.

14 SOLAR ENERGY↗
DOE OSTI2016

A Review of Lightweight Thread Approaches for High Performance Computing

High-level, directive-based solutions are becoming the programming models (PMs) of the multi/many-core architectures. Several solutions relying on operating system (OS) threads perfectly work with a moderate number of cores. However, exascale systems will spawn hundreds of thousands of threads in order to exploit their massive parallel architectures and thus conventional OS threads are too heavy for that purpose. Several lightweight thread (LWT) libraries have recently appeared offering lighter mechanisms to tackle massive concurrency. In order to examine the suitability of LWTs in high-level runtimes, we develop a set of microbenchmarks consisting of commonlyfound patterns in current parallel codes. Moreover, we study the semantics offered by some LWT libraries in order to expose the similarities between different LWT application programming interfaces. This study reveals that a reduced set of LWT functions can be sufficient to cover the common parallel code patterns and that those LWT libraries perform better than OS threads-based solutions in cases where task and nested parallelism are becoming more popular with new architectures.

Castello, Adrian↗
DOE OSTI2023

A Task Based Approach for Co-Scheduling Ensemble Workloads on Heterogeneous Nodes

Scientific workflows consist of multiple, connected applications, with data and results flowing from one to another in a pipeline. Traditionally, such workflows are executed in sequential order, storing intermediate data in storage disks. Co-scheduling application workflows concurrently on the same compute nodes would greatly reduce the cost of moving data to/from storage and allow real-time analysis of intermediate results. Nevertheless, most parallel programming runtimes do not allow seamless integration of various applications in a scientific workflow, in part due to the complexity of managing data and resources. The situation is even more complicated for heterogeneous systems. In this work we extend the Minos Computing Library (MCL) runtime to accelerate pipe-lined and parallel workloads where multiple applications are running in the same system. MCL’s asynchronous task library and runtime dynamically manages resources to allow co-scheduling of multiple processes sharing heterogeneous resources. In addition, we design a custom ex- tension of the Open Compute Language (OpenCL) to enable multiple processes to share device memory. We enable MCL to coordinate these shared buffers to allow for easy, fast data sharing between applications. Using malleable micro-benchmarks and two application workflows that combine scientific simulation and AI-based analysis, we show that our method outperforms traditional approaches.

Index Terms—Parallel systems, Scheduling and Task ↗
DOE OSTI2024

Towards reverse mode automatic differentiation of Kokkos-based codes

Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and the solving of nonlinear problems. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years, has been integrated into programming environments such as Jax, PyTorch, and TensorFlow to support derivative computations needed for training of machine learning models, facilitating wide-spread use of these technologies. The C++ language has become the de facto standard for scientific computing due to numerous factors, yet language complexity has made the wide-spread adoption of AD technologies for C++ difficult, hampering the incorporation of powerful differentiable programming approaches into C++ scientific simulations. This is exacerbated by the increasing emergence of architectures, such as GPUs, with limited memory capabilities and requiring massive thread-level concurrency. C++ AD tools must effectively use these environments to bring novel scientific simulations to next-generation DOE experimental and observational facilities. In this project, we investigated source transformation-based automatic differentiation using LLVM compiler infrastructure to automatically generate portable and efficient gradient computations of Kokkos-based code. We have demonstrated that our proposed strategy is feasible by investigating the usage of a prototype LLVM-based source transformation tool to generate gradients of simple functions made of sequences of simple Kokkos parallel regions. Speedups of up to 500x compared to Sacado were observed on NVIDIA V100 GPU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled future climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.

APSIM↗
DOE OSTI2016

User-Assisted Store Recycling for Dynamic Task Graph Schedulers

The emergence of the multi-core era has led to increased interest in designing effective yet practical parallel programming models. Models based on task graphs that operate on single-assignment data are attractive in several ways: they can support dynamic applications and precisely represent the available concurrency. However, they also require nuanced algorithms for scheduling and memory management for efficient execution. In this paper, we consider memory-efficient dynamic scheduling of task graphs. Specifically, we present a novel approach for dynamically recycling the memory locations assigned to data items as they are produced by tasks. We develop algorithms to identify memory-efficient store recycling functions by systematically evaluating the validity of a set of (user-provided or automatically generated) alternatives. Because recycling function can be input data-dependent, we have also developed support for continued correct execution of a task graph in the presence of a potentially incorrect store recycling function. Experimental evaluation demonstrates that our approach to automatic store recycling incurs little to no overheads, achieves memory usage comparable to the best manually derived solutions, often produces recycling functions valid across problem sizes and input parameters, and efficiently recovers from an incorrect choice of store recycling functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optimization of distributed compute resources utilization in the CMS Global Pool

The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and Glidein- WMS, for a total of around 500k CPU cores. This system dynamically manages workloads based on priorities defined by the collaboration. Additionally, CMS scheduling strategies must be flexible to handle multiple concurrent workloads while considering changing processing demands and resource availability from various providers.Efficient utilization of vast amounts of distributed compute resources is a key element for the success of the scientific programs of the LHC experiments. Optimizing the system is essential to maximize resource efficiency and fully utilize the distributed computing power. The CMS Submission Infrastructure team thus systematically investigates sources of inefficiency in workload scheduling to reduce their impact. In addition, a strategy of pilot overloading has been introduced to compensate for other inefficiency sources, thereby optimizing resource utilization and enhancing computational throughput.

Mascheroni, Marco [UC, San Diego (main)]↗
DOE OSTI2019

DARMA-EMPIRE Integration and Performance Assessment – Interim Report

We begin by presenting an overview of the general philosophy that is guiding the novel DARMA developments, followed by a brief reminder about the background of this project. We finally present the FY19 design requirements. As the Exascale era arises, DARMA is uniquely positioned at the forefront of asychronous many-task (AMT) research and development (R&D) to explore emerging programming model paradigms for next-generation HPC applications at Sandia, across NNSA labs, and beyond. The DARMA project explores how to fundamentally shift the expression(PM) and execution(EM)of massively concurrent HPC scientific algorithms to be more asynchronous, resilient to executional aberrations in heterogeneous/unpredictable environments, and data-dependency conscious—thereby enabling an intelligent, dynamic, and self-aware runtime to guide execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

NSTX-U Advances in Real-Time C++11 on Linux

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) will serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Micromagnetic Code Development of Advanced Magnetic Structures Final Report CRADA No. TC-1561-98

The specific goals of this project were to: Further develop the previously written micromagnetic code DADIMAG (DOE code release number 980017); Validate the code. The resulting code was expected to be more realistic and useful for simulations of magnetic structures of specific interest to Read-Rite programs. We also planned to further the code for use in internal LLNL programs. This project complemented LLNL CRADA TC-840-94 between LLNL and Read-Rite, which allowed for simulations of the advanced magnetic head development completed under the CRADA. TC-1561-98 was effective concurrently with LLNL non-exclusive copyright license (TL-1552-98) to Read-Rite for DADIMAG Version 2 executable code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Distributed Generation as a Potential Market for Solid Oxide Fuel Cells

This report explores relevant segments of the United States’ (U.S.) distributed generation (DG) market including military applications that are potential market opportunities for SOFC systems. The growth of the identified market segments through 2025 are evaluated along with an assessment of the landscape of competing technologies such as reciprocating engines and intermittent renewable energy technologies. The cost and performance of an nTH-of-a-kind (NOAK) 1-MWe class advanced SOFC DG system are estimated assuming the fruition of the goals of the SOFC program. Historical experiences with related technology, including effects of increased production capacity on capital costs, were used to develop a potential cost evolution trajectory of the DG SOFC system, which is compared with the concurrent evolution of competitive DG technologies to evaluate market penetration and cumulative capacity necessary for DG SOFC systems to be cost competitive.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Understanding Biomass Burning Aerosol via Integrated Analyses of Aerosol Mass Spectrometry Data from DOE Campaigns and ACRF Long Term Measurements

Biomass burning (BB) is one of the largest sources of aerosol particles in the atmosphere and a significant source of trace gases important to atmospheric chemistry. Organic aerosols from biomass burning sources (BBOA) are an important but poorly characterized component of the earth’s climate system. BBOA composition and life cycle processes are associated with enormous complexities and contribute significantly to model uncertainties. Hence it is important to improve the ability to simulate the concentration and properties (chemical, optical, and hygroscopic) of BBOA and the atmospheric aging processes that affect these properties. Here, we propose to analyze ambient data collected from the DOE Biomass Burning Observation Project (BBOP) field campaign and from a long term measurement site of the Atmospheric Radiation Measurement (ARM) program – the Southern Great Plains (SGP), where transported BB plumes and elevated BBOA episodes were frequently observed. This project is aimed at 1) gaining detailed, quantitative understanding of the chemical and physical properties of BBOA and their chemical changes during atmospheric aging via advanced analysis of aerosol measurement data acquired at the summit of Mt. Bachelor (MBO) during the BBOP campaign and through integration with concurrent measurements of trace gases, particle properties, and meteorological conditions performed at MBO and from the G-1 aircraft; 2) gaining better understanding of BBOA properties and its roles in radiative forcing via analysis of routine data from the ARM long-term measurement sites; and 3) integrating the results from 1) and 2) into a global database of aerosol mass spectrometry and collaborate with modelers on evaluating and improving numerical model performance as part of the ASR program.

54 ENVIRONMENTAL SCIENCES↗