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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

2022 National Household Travel Survey - Oahu Add-On

# 2022 National Household Travel Survey – Oahu Add-On The Oahu add-on survey supplements the 2022 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Survey Methodology The 2022 NHTS, which covered assigned travel dates from January 2022 to January 2023, collected data on the demographic and socioeconomic composition of households as well as detailed information on travel behavior nationwide. State transportation departments and metropolitan planning agencies—like the Oahu Metropolitan Planning Organization—had the opportunity to purchase extra household samples as part of the NHTS add-on program. These additional samples, along with national samples collected in the add-on areas, are compiled for use in transportation planning, forecasting, and research. ## Survey Records, Data, and Documentation Survey records include 7,397 participants from 3,170 households in Oahu, Hawaii, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged over 14,868 trips totaling 165,000 vehicle miles traveled.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Nevada National Security Site Site-Directed Research and Development Report (FY 2018 Annual Report)

This report compiles multiple articles describing activities developed and performed under the Site-Directed Research and Development Program for the benefit the Nation during Fiscal Year 2018. Sustained investment and ongoing core innovation are the keys to successful research and development programs. These elements drive the Site-Directed Research and Development (SDRD) Program and provide solutions to some of the most challenging problems our nation and our allies face. Our Nevada enterprise, consisting of both our management and operating entity and our NNSA field office, is aggressively investing in SDRD and injecting innovation through strategic partnerships. Our partnerships with universities, industry, and our sister institutions within the National Nuclear Security Administration (NNSA) build upon our core capabilities and allow us to create innovative solutions to support our mission requirements. In 2018, we raised the investment level of SDRD for only the second time in the history of the program. Nearly at our congressionally authorized limit, SDRD has substantial resources to successfully address numerous issues. Investment is only one part of the equation; innovation is generated through collaborations that bring discovery and provide the “technical differentiation” and the return on investment we seek. This report demonstrates an enduring theme of how partnerships help us drive the best outcomes and provide the maximum impact possible, while using our resources efficiently.

36 MATERIALS SCIENCE↗
DOE OSTI2025

GAIN Base Presentation Slide Deck 2/12/25

The GAIN Base Slide Deck is a compilation of topics that GAIN presents routinely to outside entities to educate them on the GAIN program, technology, demonstrations, coal to nuclear, energy systems, Financing, Supply Chain, Legislation, Regulatory, and Consent Based Citing.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Quantum logic gate synthesis as a Markov decision process

Reinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov decision processes (MDPs). Here, we investigate the feasibility of this assumption by exploring its consequences for single-qubit quantum state preparation and gate compilation. By forming discrete MDPs, we solve for the optimal policy exactly through policy iteration. We find optimal paths that correspond to the shortest possible sequence of gates to prepare a state or compile a gate, up to some target accuracy. Our method works in both the absence and presence of noise and compares favorably to other quantum compilation methods, such as the Ross–Selinger algorithm. This work provides theoretical insight into why reinforcement learning may be successfully used to find optimally short gate sequences in quantum programming.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Inference-Engine v0.1.0

Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's "do concurrent" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside "do concurrent" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's "dot_product" intrinsic function inside "do concurrent" blocks and another method that instead uses Fortran' "matmul" array intrinsic function. We plan to investigate automatic compiler offloading of "do concurrent" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for "matmul" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.

Rouson, Damian↗
DOE OSTI2022

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

We describe the experience of converting a CUDA implementation of a parallel graph coloring algorithm to SYCL. The goals are for our work to be useful to application and compiler developers by providing a detailed description of migration paths between CUDA and SYCL. We will describe how CUDA functions are mapped to SYCL functions. Evaluating the CUDA and SYCL implementations of the algorithm shows that the performance of SYCL and CUDA kernels are comparable over the test graph set on NVIDIA P100 and V100 GPUs. The SYCL program also allows for performance evaluation with the OpenCL and Level Zero interfaces and power profiling on an Intel GPU computing platform.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Federal Resilience Resources for State Energy Offices

The Weatherization and Intergovernmental Programs Office, through the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy, has compiled federally funded and publicly available qualitative and quantitative resources that support energy resilience and disaster mitigation planning. This handout is accompanied by the downloadable Resilience Valuation Tools Table that offers more detailed specifications on each quantitative tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Archer

Archer is built on top of the LLVM/Clang compilers that support OpenMP. It applies static and dynamic analysis techniques to detect data races in OpenMP programs generating a very low runtime and memory overhead. Static analyses identify data race free OpenMP regions and exclude them from runtime analysis, which is performed by ThreadSanitizer included in LLVM/Clang.

Atzeni, Simone↗
DOE OSTI2025

Mapping Spiking Neural Networks to Heterogeneous Crossbar Architectures using Integer Linear Programming

Advances in novel hardware devices and architectures allow Spiking Neural Network (SNN) evaluation using ultra-low power, mixed-signal, memristor crossbar arrays. As individual network sizes quickly scale beyond the dimensional capabilities of single crossbars, networks must be mapped onto multiple crossbars. Crossbar sizes within modern Memristor Crossbar Architectures (MCAs) are determined predominately not by device technology but by network topology; more, smaller crossbars consume less area thanks to the high structural sparsity found in larger, brain-inspired SNNs. Motivated by continuing increases in SNN sparsity due to improvements in training methods, we propose utilizing heterogeneous crossbar sizes to further reduce area consumption. This approach was previously unachievable as prior compiler studies only explored solutions targeting homogeneous MCAs. Our work improves on the state-of-the-art by providing Integer Linear Programming (ILP) formulations supporting arbitrarily heterogeneous architectures. By modeling axonal interactions between neurons, our methods produce better mappings while removing inhibitive a priori knowledge requirements. We first show a 16.7-27.6% reduction in area consumption for square-crossbar homogeneous architectures. Then, we demonstrate 66.9-72.7% further reduction when using a reasonable configuration of heterogeneous crossbar dimensions. Next, we present a new optimization formulation capable of minimizing the number of inter-crossbar routes. When applied to solutions already near-optimal in area, an 11.9-26.4% routing reduction is observed without impacting area consumption. Finally, we present a profile-guided optimization capable of minimizing the number of runtime spikes between crossbars. Compared to the best-area-then-route optimized solutions, we observe a further 0.5-14.8% inter-crossbar spike reduction while requiring 1–3 orders of magnitude less solver time.

Pohl, Devin [ORNL] (ORCID:0009000040149027)↗
DOE OSTI2015

Final report: Compiled MPI. Cost-Effective Exascale Application Development

This is the final report on Compiled MPI: Cost-Effective Exascale Application Development, and summarizes the results under this project. The project investigated runtime enviroments that improve the performance of MPI (Message-Passing Interface) programs; work at Illinois in the last period of this project looked at optimizing data access optimizations expressed with MPI datatypes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A Lithography‐Free and Field‐Programmable Photonic Metacanvas

Abstract The unique correspondence between mathematical operators and photonic elements in wave optics enables quantitative analysis of light manipulation with individual optical devices. Phase‐transition materials are able to provide real‐time reconfigurability of these devices, which would create new optical functionalities via (re)compilation of photonic operators, as those achieved in other fields such as field‐programmable gate arrays (FPGA). Here, by exploiting the hysteretic phase transition of vanadium dioxide, an all‐solid, rewritable metacanvas on which nearly arbitrary photonic devices can be rapidly and repeatedly written and erased is presented. The writing is performed with a low‐power laser and the entire process stays below 90 °C. Using the metacanvas, dynamic manipulation of optical waves is demonstrated for light propagation, polarization, and reconstruction. The metacanvas supports physical (re)compilation of photonic operators akin to that of FPGA, opening up possibilities where photonic elements can be field programmed to deliver complex, system‐level functionalities.

Dong, Kaichen↗
DOE OSTI2020

Consistency of $^{16}O(n,α)$ cross sections

The evaluated $^{16}O(n,α)$ cross sections in the ENDF/B-VIII.0 nuclear data library remain uncertain because of systematic discrepancies in the measured data. In the energy region below the first excited state, R-matrix analyses rely heavily on the inverse reaction, and in particular, they rely on the measured $^{13}C(α,n)^{16}O$ cross sections reported by Bair et al. in 1973 and Harissopulos et al. in 2005. The Harissopulos cross section values are systematically lower than those previously reported by Bair. Here, drawing on the available experimental information, this paper briefly describes and demonstrates that the two sets of measured cross sections are consistent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Clacc: Translating OpenACC to OpenMP in Clang

OpenACC was launched in 2010 as a portable programming model for heterogeneous accelerators. Although various implementations already exist, no extensible, open-source, production-quality compiler support is available to the community. This deficiency poses a serious risk for HPC application developers targeting GPUs and other accelerators, and it limits experimentation and progress for the OpenACC specification. To address this deficiency, Clacc is a recent effort funded by the US Exascale Computing Project to develop production OpenACC compiler support for Clang and LLVM. A key feature of the Clacc design is to translate OpenACC to OpenMP to build on Clang's existing OpenMP compiler and runtime support. In this paper, we describe the Clacc goals and design. We also describe the challenges that we have encountered so far in our prototyping efforts, and we present some early performance results.

Denny, Joel↗
DOE OSTI2015

Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code

Highly optimized programs are prone to bit rot, where performance quickly becomes suboptimal in the face of new hardware and compiler techniques. In this paper we show how to automatically lift performance-critical stencil kernels from a stripped x86 binary and generate the corresponding code in the high-level domain-specific language Halide. Using Halide's state-of-the-art optimizations targeting current hardware, we show that new optimized versions of these kernels can replace the originals to rejuvenate the application for newer hardware. The original optimized code for kernels in stripped binaries is nearly impossible to analyze statically. Instead, we rely on dynamic traces to regenerate the kernels. We perform buffer structure reconstruction to identify input, intermediate and output buffer shapes. Here, we abstract from a forest of concrete dependency trees which contain absolute memory addresses to symbolic trees suitable for high-level code generation. This is done by canonicalizing trees, clustering them based on structure, inferring higher-dimensional buffer accesses and finally by solving a set of linear equations based on buffer accesses to lift them up to simple, high-level expressions. Helium can handle highly optimized, complex stencil kernels with input-dependent conditionals. We lift seven kernels from Adobe Photoshop giving a 75 % performance improvement, four kernels from Irfan View, leading to 4.97 x performance, and one stencil from the mini GMG multigrid benchmark netting a 4.25 x improvement in performance. We manually rejuvenated Photoshop by replacing eleven of Photoshop's filters with our lifted implementations, giving 1.12 x speedup without affecting the user experience.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Gleipnir: toward practical error analysis for Quantum programs

Practical error analysis is essential for the design, optimization, and evaluation of Noisy Intermediate-Scale Quantum(NISQ) computing. However, bounding errors in quantum programs is a grand challenge, because the effects of quantum errors depend on exponentially large quantum states. In this work, we present Gleipnir, a novel methodology toward practically computing verified error bounds in quantum programs. Gleipnir introduces the (ρ,δ)-diamond norm, an error metric constrained by a quantum predicate consisting of the approximate state ρ and its distance δ to the ideal state ρ. This predicate (ρ,δ) can be computed adaptively using tensor networks based on the Matrix Product States. Gleipnir features a lightweight logic for reasoning about error bounds in noisy quantum programs, based on the (ρ,δ)-diamond norm metric. Furthermore, our experimental results show that Gleipnir is able to efficiently generate tight error bounds for real-world quantum programs with 10 to 100 qubits, and can be used to evaluate the error mitigation performance of quantum compiler transformations.

Tao, Runzhou↗
DOE OSTI2024

ThunderBoltz API

The ThunderBoltz application programming interface (API) code is written in Python and is comprised of a set of tools to facilitate compilation of the ThunderBoltz code, as well as fast assembly and formatting of input files for the ThunderBoltz code, post-processing tools of ThunderBoltz results, plotting tools, and runs/schedules the ThunderBoltz code executable for calculations. The ThunderBoltz API code is utilized for importing and manipulating input cross section sets, input conditions, and any other simulation settings made available within the ThunderBoltz input deck via user-defined settings or via automatic generation. The API comes with a set of plotting capabilities of input cross sections, results from ThunderBoltz, and post-processed results carried out with the API.

Park, Ryan↗
DOE OSTI2017

Tracking the Sun 10: The Installed Price of Residential and Non-Residential Photovoltaic Systems in the United States

Berkeley Lab’s Tracking the Sun report series is dedicated to summarizing trends in the installed price of grid-connected, residential and non-residential systems solar photovoltaic (PV) systems in the United States. The present report, the tenth edition in the series, focuses on systems installed through year-end 2016, with preliminary data for the first half of 2017. The report provides an overview of both long-term and more-recent trends, highlighting key drivers for installed price declines over different time horizons. The report also extensively characterizes the widespread variability in system pricing, comparing installed prices across states, market segments, installers, and various system and technology characteristics. The trends described in this report derive from project-level data collected by state agencies and utilities that administer PV incentive programs, solar renewable energy credit (SREC) registration systems, or interconnection processes. In total, data for this report were compiled and cleaned for more than 1.1 million individual PV systems, though the analysis in the report is based on a subset of that sample, consisting of roughly 630,000 systems with available installed price data. The full underlying dataset of project-level data (excluding any confidential information) is available in a public data file, for use by other researchers and analysts.

14 SOLAR ENERGY↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Analyses to Inform Equitable Investment Prioritization

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. Megan Day and Liz Ross, along with their co-authors and supported by NREL's Sustainable Communities Catalyzer, identified areas where disadvantaged community indicators intersect with high potential for renewable energy deployment. Through a geospatial intersection of energy burden, environmental hazard, and sociodemographic data with the technical generation potential and levelized cost of energy for multiple renewable energy technologies, we identified trends across disadvantaged community indicators and renewable energy deployment potential. Combining metrics across several tools, including the State and Local Planning for Energy (SLOPE) platform, the Low-Income Energy Affordability (LEAD) tool, and the Environmental Justice Screening and Mapping (EJSCREEN) tool, we compiled a dataset that can be used to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantage communities.

catalyzer↗