Search NASA⌕ Search

SEARCH · Search NASA

Results for “Application Framework”

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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Modeling and Predicting Performance of High Performance Computing Applications on Hardware Accelerators

Computers with hardware accelerators, also referred to as hybrid-core systems, speedup applications by offloading certain compute operations that can run faster on accelerators. Thus, it is not surprising that many of top500 supercomputers use accelerators. However, in addition to procurement cost, significant programming and porting effort is required to realize the potential benefit of such accelerators. Hence, before building such a system it is prudent to answer the question 'what is the projected performance benefit from accelerators for the workloads of interest?'. We address this question by way of a performance-modeling framework that predicts realizable application performance on accelerators rapidly and accurately without going to the considerable effort of porting and tuning. The modeling framework first automatically identifies commonly found compute patterns in scientific applications which we term idioms, which may benefit by accelerator technology. Next the framework models the predicted speedup of those idioms if they were to be ported to and run on hardware accelerators. As a proof of concept we characterize two kinds of accelerators 1) the FPGA accelerators on a Convey HC-1 system and 2) an NVIDIA FERMI GPU accelerator. We model performance of the idioms gather/scatter and stream and our predictions show that where these occur in two full-scale HPC applications, Milc and HYCOM, gather/scatter speeds up by as much as 15X, and stream by as much as 14X, whereas the overall compute time of Milc improves by 3.4% and HYCOM by 20%.

Computer Science↗
DOE OSTI2012

Improving High-Performance Sparse Libraries Using Compiler-Assisted Specialization: A PETSc Case Study

Computers with hardware accelerators, also referred to as hybrid-core systems, speedup applications by offloading certain compute operations that can run faster on accelerators. Thus, it is not surprising that many of top500 supercomputers use accelerators. However, in addition to procurement cost, significant programming and porting effort is required to realize the potential benefit of such accelerators. Hence, before building such a system it is prudent to answer the question 'what is the projected performance benefit from accelerators for the workloads of interest?'. We address this question by way of a performance-modeling framework that predicts realizable application performance on accelerators rapidly and accurately without going to the considerable effort of porting and tuning. The modeling framework first automatically identifies commonly found compute patterns in scientific applications which we term idioms, which may benefit by accelerator technology. Next the framework models the predicted speedup of those idioms if they were to be ported to and run on hardware accelerators. As a proof of concept we characterize two kinds of accelerators 1) the FPGA accelerators on a Convey HC-1 system and 2) an NVIDIA FERMI GPU accelerator. We model performance of the idioms gather/scatter and stream and our predictions show that where these occur in two full-scale HPC applications, Milc and HYCOM, gather/scatter speeds up by as much as 15X, and stream by as much as 14X, whereas the overall compute time of Milc improves by 3.4% and HYCOM by 20%.

Computer Science↗
DOE OSTI2023

High yield, large-scale synthesis of calcium-based microporous metal-organic framework and examination of the long-term stability for xenon adsorption applications

Here, scale-up synthesis of calcium-based microporous metal-organic framework (SBMOF-1) up to ~400 g in a batch with a yield of >90 % was achieved by a solvothermal reaction of sulfonyldibenzoic acid (SDB) with an excess of calcium chloride. Here, we observed that recrystallization of unreacted SDB at a solvothermal condition caused a moderate reaction yield (40–50 %) at the reference condition of $C_{CaCl_2}$/$C_{SDB}$=1 and $C_{SDB}$/$C_{SDB(ref)}$=1. Simply adding more reagents to the reactor did not increase the mass of product formed per unit volume due to a more pronounced loss of the yield at those conditions. By simultaneously changing the molar ratio of CaCl 2 to SDB, $C_{CaCl_2}$/$C_{SDB}$, and the molar concentration of the SDB reagent, $C_{SDB}$/$C_{SDB(ref)}$, we explored %yield of the reaction. Interestingly, a linear improvement in the yield was observed from 21% (at $C_{CaCl_2}$/$C_{SDB}$=0.5) up to 78% (at $C_{CaCl_2}$/$C_{SDB}$=6) at a fixed ratio of $C_{SDB}$/$C_{SDB(ref)}$=2 and the yield leveled off after further addition. Unlike those at $C_{CaCl_2}$/$C_{SDB}$=1, the yields at a high CaCl 2 excess continued to improve with increasing the $C_{SDB}$/$C_{SDB(ref)}$. When a large pressure vessel (2500 mL EtOH, $C_{CaCl_2}$/$C_{SDB}$=6, $C_{SDB}$/$C_{SDB(ref)}$=8) was used, about 415 g of SBMOF-1 with a yield of 92.3% was produced, indicating 16 × the space yield improvement. The ability to synthesize SBMOF-1 on a large scale allowed us to examine the long-term stability of SBMOF-1 for almost 200 days in the presence of varying levels of relative humidity.

36 MATERIALS SCIENCE↗
NASA NTRS1992

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 23: Information technology and aerospace knowledge diffusion: Exploring the intermediary-end user interface in a policy framework

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowled reproduction, transfer, and use as equally important components of the process of knowledge diffusion. It is argued that the potential contributions of high-speed computing and networking systems will be diminished unless empirically derived knowledge about the information-seeking behavior of the members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Pinelli, Thomas E.↗
NASA NTRS1992

NASA/DoD Aerospace Knowledge Diffusion Research Project. XXIII - Information technology and aerospace knowledge diffusion: Exploring the intermediary-end user interface in a policy framework

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowledge production, transfer, and use as equally important components of the process of knowledge diffusion. This article argues that the potential contributions of high-speed computing and networking systems will be diminished unless empirically derived knowledge about the information-seeking behavior of members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Pinelli, Thomas E.↗
NASA NTRS2014

Development, Validation, and Application of OSSEs at NASA-GMAO

The GMAO OSSE framework has two general classes of applications. One is to estimate the potential improvements to weather forecasting and analysis by using new proposed instruments that are not as yet built or deployed. This exploits the simulated nature of the OSSE. The other is to assess various aspects of the GMAO data assimilation system. This exploits the availability of truth provided by the OSSE. Two examples of the first class of application will be offered. One concerns deployment of constellations of passive MW sounders on small CUBESATs placed in very low orbits. The other concern is increasing the frequency of radiosonde observations to 4-times daily at all current stations. Several examples of the second class will also be presented. One is an estimation of analysis error characteristics. Another is a comparison between covariances directly determined from explicitly known background errors and those estimated by computing differences between lagged forecasts using the NMC-method prior to tuning. A third is a comparison of effects of model and observation errors on analysis and forecast skill. The last is an examination of spectra of forecast errors in a study of predictability. This latter is an ongoing study.

OSSE↗
DOE OSTI2017

Quantitative multiphase model for hydrothermal liquefaction of algal biomass

Here, optimized incorporation of hydrothermal liquefaction (HTL, reaction in water at elevated temperature and pressure) within an integrated biorefinery requires accurate models to predict the quantity and quality of all HTL products. Existing models primarily focus on biocrude product yields with limited consideration for biocrude quality and aqueous, gas, and biochar co-products, and have not been validated with an extensive collection of feedstocks. In this study, HTL experiments (300 °C, 30 min) were conducted using 24 different batches of microalgae feedstocks with distinctive feedstock properties, which resulted in a wide range of biocrude (21.3–54.3 dry weight basis, dw%), aqueous (4.6–31.2 dw%), gas (7.1–35.6 dw%), and biochar (1.3–35.0 dw%) yields. Based on these results, a multiphase component additivity (MCA) model was introduced to predict yields and characteristics of the HTL biocrude product and aqueous, gas, and biochar co-products, with only feedstock biochemical (lipid, protein, carbohydrate, and ash) and elemental (C/H/N) composition as model inputs. Biochemical components were determined to distribute across biocrude product/HTL co-products as follows: lipids to biocrude; proteins to biocrude > aqueous > gas; carbohydrates to gas ≈ biochar > biocrude; and ash to aqueous > biochar. Modeled quality indicators included biocrude C/H/N contents, higher heating value (HHV), and energy recovery (ER); aqueous total organic carbon (TOC) and total nitrogen (TN) contents; and biochar carbon content. The model was validated with HTL data from the literature, the potential to expand the application of this modeling framework to include waste biosolids (e.g., wastewater sludge, manure) was explored, and future research needs for industrial application were identified. Ultimately, the MCA model represents a critical step towards the integration of cultivation models with downstream HTL and biorefinery operations to enable system-level optimization, valorization of co-product streams (e.g., through catalytic hydrothermal gasification and nutrient recovery), and the navigation of tradeoffs across the value chain.

09 BIOMASS FUELS↗
DOE OSTI2026

Data-Driven Performance Optimization of Gamma Spectrometers With Many Channels

In gamma spectrometers with variable spectroscopic performance across many channels (e.g., many pixels or voxels), a tradeoff exists between including data from successively worse-performing readout channels and increasing efficiency. Brute-force calculation of the optimal set of included channels is exponentially infeasible as the number of channels grows, and approximate methods are required. In this work, we present a data-driven framework for attempting to find near-optimal sets of included detector channels. The framework leverages non-negative matrix factorization (NMF) to learn the behavior of gamma spectra across the detector and clusters similarly-performing detector channels together. Performance comparisons are then made between spectra with channel clusters removed, which is more feasible than brute force. The framework is general and can be applied to arbitrary, user-defined performance metrics depending on the application. We apply this framework to optimizing gamma spectra measured by H3D M400 CdZnTe (CZT) spectrometers, which exhibit variable performance across their crystal volumes. In particular, we show several examples optimizing various performance metrics for uranium and plutonium gamma spectra in non-destructive assay (NDA) for nuclear safeguards, and explore trends in performance versus parameters such as clustering algorithm type. We also compare the NMF + clustering pipeline to several non-machine-learning (ML) algorithms, including several greedy algorithms. Although, we find that the NMF + clustering pipeline tends to find the best-performing set of detector voxels, significantly improving over the unoptimized spectra, but that a greedy accumulation of spectra segmented by detector depth can, in some cases, give similar performance improvements in much less computation time.

Energy resolution↗
NASA NTRS2000

IsoWAN: A NASA Science and Engineering Information and Services Framework

We believe that the next evolutionary step in supporting wide-area application and services delivery to customers is a network framework that provides for collocation of applications and services at distinct sites in the network, an interconnection between these sites that is performance optimized for these applications, and value-added services for applications. We use the term IsoWAN to describe an advanced, isolated network interconnect services framework that will enable applications to be more secure, and able to access and be in use in both local and remote environments. The main functions of an IsoWAN are virtual localization of application services, an application service interface, coordinated delivery of applications and associated data to the customer, and supporting collaborative application development for customers. An initial pilot network between three NASA Centers: Ames Research Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, has been built and its properties will be discussed.

Korsmeyer, David J.↗
DOE OSTI2025

Directed energy deposition of functionally graded V-4Cr-4Ti to Fe-9Cr transition for fusion power systems

This study proposes a graded structure via additive manufacturing for divertor and first wall blanket applications in fusion reactors. Materials were selected based on thermodynamic calculations to operate from 1100 °C at the plasma-facing level to 550 °C at the structural steel level. Conventional joining methods often lead to failures due to discrete reaction layers with significant mechanical property differences. Using laser beam-directed energy deposition (LB-DED), this study demonstrates the fabrication of a VCrTi-Gr91 steel functionally graded component through a novel process parameter optimization framework. A systematic approach included powder characterization, single-track depositions, and construction of printability maps. Near full-density specimens of each interlayer were additively manufactured, and a transition from V-based alloys to reduced activation ferritic martensitic steels was achieved. Computational material selection of interlayer alloys and thermodynamic/diffusion kinetics simulations prevented most interface incompatibilities. A brittle intermetallic formed at one interface, causing cracking, which was not predicted by current thermodynamic models. Transition alloy design approach was updated with a more recent database and a mitigation strategy has been proposed to eliminate the formation of deleterious intermetallic phases. Ultimately, LB-DED has proven effective for producing multi-material graded systems for fusion applications, with the demonstrated process parameter optimization framework applicable to various materials.

Additive manufacturing↗
NASA NTRS1989

Maintenance = reuse-oriented software development

Maintenance is viewed as a reuse process. In this context, a set of models that can be used to support the maintenance process is discussed. A high level reuse framework is presented that characterizes the object of reuse, the process for adapting that object for its target application, and the reused object within its target application. Based upon this framework, a qualitative comparison is offered of the three maintenance process models with regard to their strengths and weaknesses and the circumstances in which they are appropriate. To provide a more systematic, quantitative approach for evaluating the appropriateness of the particular maintenance model, a measurement scheme is provided, based upon the reuse framework, in the form of an organized set of questions that need to be answered. To support the reuse perspective, a set of reuse enablers are discussed.

Basili, Victor R.↗
DOE OSTI2024

CHMMPY: A python package for constrained Hidden Markov Models

SAND2025-11909O chmmpy software analyzes multivariate timeseries data to detect patterns. It uses a Hidden Markov Model (HMM) and application-specific constraints that reflect known relationships among hidden states to accomplish this. The chmmpy software provides a generic framework for expressing application-specific constraints and supporting constrained HMM inference using optimization solvers. chmmpy is available on GitHub. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William↗
DOE OSTI2024

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Rutishauser, David↗
DOE OSTI2013

A Model-Based Framework for Air Quality Indices and Population Risk Evaluation, with an Application to the Analysis of Scottish Air Quality Data

Summary The paper is devoted to the development of a statistical framework for air quality assessment at the country level and for the evaluation of the ambient population exposure and risk with respect to airborne pollutants. The framework is based on a multivariate space–time model and on aggregated indices defined at different levels of aggregation in space and time. The indices are evaluated, uncertainty included, by considering both the model outputs and the information on the population spatial distribution. The framework is applied to the analysis of air quality data for Scotland for 2009 referring to European and Scottish air quality legislation.

Unbalanced networks↗
NASA NTRS1996

Ra: The Sun for Science and Humanity

To guide the development of the Ra Strategic Framework, we defined scientific and applications objectives. For our primary areas of scientific interest, we choose the corona, the solar wind, the Sun's effect on the Earth, and solar theory and model development. For secondary areas of scientific interest, we selected sunspots, the solar constant, the Sun's gravitational field, helioseismology and the galactic cosmic rays. We stress the importance of stereoscopic imaging, observations at high spatial, spectral, and temporal resolutions, as well as of long duration measurements. Further exploration of the Sun's polar regions is also important, as shown already by the Ulysses mission. From an applications perspective, we adopted three broad objectives that would derive complementary inputs for the Strategic Framework. These were to identify and investigate: possible application spin-offs from science missions, possible solar-terrestrial missions dedicated to a particular application, and possible future applications that require technology development. The Sun can be viewed as both a source of resources and of threats. Our principal applications focus was that of threat mitigation, by examining ways to improve solar threat monitoring and early warning systems. We compared these objectives to the mission objectives of past, current, and planned international solar missions. Past missions (1962-1980) seem to have been focused on improvement of scientific knowledge, using multiple instrument spacecraft. A ten year gap followed this period, during which the results from previous missions were analyzed and solar study programmes were prepared in international organizations. Current missions (1990-1996) focus on particular topics such as the corona, solar flares, and coronal mass ejections. In planned missions, Sun/Earth interactions and environmental effects of solar activity are becoming more important. The corona is the centre of interest of almost all planned missions. It seems that no international long-term strategy has yet been adopted. For these plans the number of necessary future missions can be reduced and the onboard instrumentation can be optimized by performing a comparative analysis. The study of the corona must be done from different observing locations, orbits closer to the Sun, and by different means. The Cluster mission replacement is in progress; however, if the replacement is not implemented, the ISTP programme will fade after 1998. Furthermore, the physics of the Sun's interior should be emphasized more in the Mid- and Far-Term programmes. Finally, more emphasis should be placed on monitoring space weather and forecasting Sun/Earth interactions.

Source record↗
DOE OSTI2016

Development of a Neural Network-Based Renewable Energy Forecasting Framework for Process Industries

This paper presents a neural network-based forecasting framework for photovoltaic power (PV) generation as a decision-supporting tool to employ renewable energies in the process industry. The applicability of the proposed framework is illustrated by comparing its performance against other methodologies such as linear and nonlinear time series modelling approaches. A case study of an actual PV power plant in South Korea is presented.

14 SOLAR ENERGY↗