Search NASA⌕ Search

SEARCH · Search NASA

Results for “future of computing”

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 829 records · Page 46

THE EFFECTS OF DARK MATTER ANNIHILATION ON COSMIC REIONIZATION

We revisit the possibility of constraining the properties of dark matter (DM) by studying the epoch of cosmic reionization. Previous studies have shown that DM annihilation was unlikely to have provided a large fraction of the photons which ionized the universe, but instead played a subdominant role relative to stars and quasars. The DM might, however, have begun to efficiently annihilate with the formation of primordial microhalos at z ∼ 100–200, much earlier than the formation of the first stars. Therefore, if DM annihilation ionized the universe at even the percent level over the interval z ∼ 20–100, it could leave a significant imprint on the global optical depth, τ . Moreover, we show that cosmic microwave background polarization data and future 21 cm measurements will enable us to more directly probe the DM contribution to the optical depth. In order to compute the annihilation rate throughout the epoch of reionization, we adopt the latest results from structure formation studies and explore the impact of various free parameters on our results. We show that future measurements could make it possible to place constraints on the DM’s annihilation cross-sections, which are at a level comparable to those obtained from the observations of dwarf galaxies, cosmic-ray measurements, and studies of recombination.

79 ASTRONOMY AND ASTROPHYSICS↗

Efficient Scalable Contact Network Generation from Population Data

Modeling the contacts among a population is critical to understanding the dynamics of a disease outbreak. Contact networks, where nodes are individuals and edges are contacts among them, are used to represent these complex individual-level interactions. In this work, we are given the daily activity schedules of an urban population that represent the activity location and time of individuals in a population during a single twenty four hour period over multiple days. Using collocation to determine contact between individuals, our goal is to extract hourly contact networks from large-scale activity data. We improve upon the existing adjacency matrix-based method by implementing our custom sparse matrix multiplication algorithm. Starting with a Python implementation, we achieve a 1600x speed up in the computation with a fast custom designed sparse matrix multiplier algorithm implemented in the C++ language. This work is central to future parallel designs of the problem.

97 MATHEMATICS AND COMPUTING↗

High-Temperature Gas-Cooled Reactor Research Survey and Overview: Preliminary Data Platform Construction for the Nuclear Energy University Program

Since the U.S. Department of Energy Office of Nuclear Energy initiated the Nuclear Energy University Program (NEUP) in 2009, there are 29 NEUP projects focusing on high-temperature gas-cooled reactor (HTGR) research up to July 2022. The resultant research product, either experimental or computational, were published as final NEUP reports, journal articles and conference proceedings. However, these federally funded products have been scattered and sometimes cannot be easily accessed. To improve access to this valuable HTGR validation data and optimize the return on the significant investment made by the Department of Energy, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects to develop a public-access database specific for HTGRs applications that can be used to retrieve computational fluid dynamics and system code validation data. This effort will help guide future NEUP-funded research, define new state of the ART Phenomena Identification and Ranking Table (PIRT), and promote the usage of this data in the codes validation matrices. This report provides an overview of the NEUP-funded HTGR-related research projects from Fiscal Year (FY) 2009–2021 and identifies validation knowledge gaps still existing in HTGR thermal-fluid research. A preliminary data platform has been developed for the 29 NEUP projects investigating HTGR thermal hydraulics, including their final reports as well as the available scientific publications. As an ultimate goal for this work, the ART-GCR program will create a central database at Idaho National Laboratory to identify, organize, and store these datasets generated by experimental investigations or computational models, experimental facility descriptions, and publicly-available academic products from the HTGR-related NEUP projects and provide future guidance for the storage and transmission of important project documentations for later NEUP projects as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

VALID Past, Present, and Future [Slides]

This presentation discusses the Verified, Archived Library of Inputs and Data (VALID) procedure which is managed per computational procedure under the overall SCALE quality assurance plan. The principle behind VALID is that two independent, qualified people prepare and review the model, while a dual, independent check acts as a primary barrier to prevent errors in the library. A final check by VALID QAC of procedural compliance is then performed. The future for VALID includes plans to add more experiments, a review for all ICSBEP cases containing Deuterium, ZEUS intermediate and fast spectrum evaluations, intermediate enrichment experiments, other cases of interest to sponsors, and mixed/intermediate spectrum experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preliminary Theoretical Analysis of Mixed Precision Krylov Subspace Methods (Q3 Report)

The third quarter of the project was spent performing theoretical finite precision analysis of Krylov subspace method variants that use mixed precision. Our focus here is on the Conjugate Gradient (CG) method and the Lanczos method. We have performed an analysis of maximum attainable accuracy for the classical CG method in which 3 precisions are used: a working precision ε, a precision ε IP for the inner product computations, and a precision ε MV for the matrix-vector products. Our results show that performing inner product computations in lower precision does not affect the attainable accuracy. Further, we have performed a complete error analysis of the s-step Lanczos algorithm. In this case, we show that the numerical behavior of the algorithm can be significantly improved by using extra precision in a small part of the computation. We summarize the main theorems in the remainder of the document. Other activities include attending biweekly xSDK meetings. The subsequent quarter will be spent finalizing these results into technical reports and/or manuscripts for submission to journals, as well as identifying opportunities for future work.

97 MATHEMATICS AND COMPUTING↗

Towards a More Effective Hybrid Workforce Culture in a Computationally Focused Research Center

It is essential to Sandia National Laboratory’s continued success in scientific and technological advances and mission delivery to embrace a hybrid workforce culture under which current and future employees can thrive. This report focuses on the findings of the Hybrid Work Team for the Center for Computing Research, which met weekly from March to June 2023 and conducted a survey across the Center at Sandia. Conclusions in this report are drawn from the 9 authors of this report, which comprises the Hybrid Work Team, and 15 responses to a center-wide survey, as well as numerous conversations with colleagues. A major finding was widespread dissatisfaction with the quantity, execution, and tooling surrounding formal meetings with remote participants. While there was consensus that remote work enables people to produce high quality individual and technical work, there was also consensus that there was widespread social disconnect, with particular concern about hires that were made after the onset of the Covid-19 pandemic. There were many concerns about tooling and policy to facilitate remote collaboration both within Sandia and with its external collaborators. This report includes recommendations for mitigating these problems. For problems for which obvious recommendations cannot be made, ideas of what a successful solution might look like are presented.

99 GENERAL AND MISCELLANEOUS↗

Parallel Time Integration: An Approaching Paradigm Shift for Scientific Computing

This note argues that parallel-in-time methods will be necessary for doing high-fidelity time-dependent simulations in the future. A “proof” is given to support the argument and to provide a framework for debate. The effect of a parallel-in-time paradigm on scientific computing practice is also discussed.

97 MATHEMATICS AND COMPUTING↗

Towards the next generation of Geospatial Artificial Intelligence

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote sensing, urban computing, Earth system science, cartography, and geospatial semantics. Finally, we highlight several unique future research directions of GeoAI which are classified into two groups: GeoAI method development challenges and GeoAI Ethics challenges. Topics include heterogeneity-aware GeoAI, knowledge-guided GeoAI, spatial representation learning, geo-foundation models, fairness-aware GeoAI, privacy-aware GeoAI, as well as interpretable and explainable GeoAI. We hope our review of GeoAI’s past, present, and future is comprehensive and can enlighten the next generation of GeoAI research.

58 GEOSCIENCES↗

In the Mix : A Workshop Merging Computational Chemistry and Electrochemistry Alongside Data Science

As chemistry expands to more complex and interdisciplinary areas, a new generation of diverse researchers must engage with science and learn effective cross-disciplinary collaboration and communication. To these ends, we designed and implemented In the Mix, a graduate student-led, two-day workshop for undergraduate students promoting collaborative science in the context of energy storage innovations. Here, the interactive workshop was designed for future and emerging researchers to gain hands-on experience with data science, computational chemistry, and electrochemistry techniques that are critical for developing materials for battery technologies. Participants also visited commercial renewable energy facilities to help them connect discovery-based research with industry and broader societal considerations. The workshop content and structure ensured that participants experienced the interrelatedness of the fields and understood the importance of collaborative research to yield scientific advances with real-world applications. An external team evaluated the workshop and participants’ perceptions of their experiences. While our research context was energy storage, the workshop goals and outcomes are applicable to other contexts. Interdisciplinary, experiential workshops are a key avenue to broadening participation in science and research, and the ideas presented here can be readily modified for other scientific contexts and/or incorporated as broader impact activities.

25 ENERGY STORAGE↗

Quantum Distributed Unit Commitment: An Application in Microgrids

The dawn of quantum computing brings on a revolution in the way combinatorially complex power system problems such as Unit Commitment are solved. The Unit Commitment problem complexity is expected to increase in the future because of the trend toward the increase of penetration of intermittent renewables. Even though quantum computing has proven effective for solving a host of problems, its applications for power systems’ problems have been rather limited. Here, in this paper, a quantum unit commitment is innovatively formulated and the quantum version of the decomposition and coordination alternate direction method of multipliers (ADMM) is established. The above is achieved by devising quantum algorithms and by exploiting the superposition and entanglement of quantum bits (qubits) for solving subproblems, which are then coordinated through ADMM to obtain feasible solutions. The main contributions of this paper include: 1) the innovative development of a quantum model for Unit Commitment; 2) development of decomposition and coordination-supported framework which paves the way for the utilization of limited quantum resources to potentially solve the large-scale discrete optimization problems; 3) devising the novel quantum distributed unit commitment (QDUC) to solve the problem in a larger scale than currently available quantum computers are capable of solving. The QDUC results are compared with those from its classical counterpart, which validate the efficacy of quantum computing.

97 MATHEMATICS AND COMPUTING↗

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physics models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High mass and halo resolution from fast low resolution simulations

Generating mocks for future sky surveys requires large volumes and high resolutions, which is computationally expensive even for fast simulations. Here we try to develop numerical schemes to calibrate various halo and matter statistics in fast low resolution simulations compared to high resolution N-body and hydrodynamic simulations. For the halos, we improve the initial condition resolution and develop a halo finder "relaxed-FoF", where we allow different linking lengths for different halo mass and velocity dispersions. We show that our relaxed-FoF halo finder improves the common statistics, such as halo bias, halo mass function, halo auto power spectrum, cross correlation coefficient with the reference halo catalog, and halo-matter cross power spectrum. We also calibrate small-scale velocities of small halos to improve the power spectrum in redshift space. For the matter statistics, we incorporate the potential gradient descent (PGD) method into fast simulations to improve the matter distribution at nonlinear scales. By building a lightcone output, we show that the PGD method significantly improves the weak lensing convergence tomographic power spectrum. With these improvements FastPM is comparable to the high resolution full N-body simulation of the same mass resolution, with two orders of magnitude fewer time steps. These techniques can be used to improve the halo and matter statistics of FastPM simulations for mock catalogs of future surveys such as DESI and LSST.

79 ASTRONOMY AND ASTROPHYSICS↗

Reaching new peaks for the future of the CMS HTCondor Global Pool

The CMS experiment at CERN employs a distributed computing infrastructure to satisfy its data processing and simulation needs. The CMS Submission Infrastructure team manages a dynamic HTCondor pool, aggregating mainly Grid clusters worldwide, but also HPC, Cloud and opportunistic resources. This CMS Global Pool, which currently involves over 70 computing sites worldwide and peaks at 350k CPU cores, is employed to successfully manage the simultaneous execution of up to 150k tasks. While the present infrastructure is sufficient to harness the current computing power scales, CMS latest estimates predict a noticeable expansion in the amount of CPU that will be required in order to cope with the massive data increase of the High-Luminosity LHC (HL-LHC) era, planned to start in 2027. This contribution presents the latest results of the CMS Submission Infrastructure team in exploring and expanding the scalability reach of our Global Pool, in order to preventively detect and overcome any barriers in relation to the HL-LHC goals, while maintaining high effciency in our workload scheduling and resource utilization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

MOOSE IPL Extensions (Control Logic)

In FY-2015, the development of MOOSE was driven by the needs of the NEAMS MOOSE-based applications, BISON, MARMOT, and RELAP-7. An emphasis was placed on the continued upkeep and improvement MOOSE in support of the product line integration goals. New unified documentation tools have been developed, several improvements to regression testing have been enforced and overall better software quality practices have been implemented. In addition the Multiapps and Transfers systems have seen significant refactoring and robustness improvements, as has the “Restart and Recover” system in support of Multiapp simulations. Finally, a completely new “Control Logic” system has been engineered to replace the prototype system currently in use in the RELAP-7 code. The development of this system continues and is expected to handle existing needs as well as support future enhancements.

97 MATHEMATICS AND COMPUTING↗

Evaluating Trade-offs in Potential Exascale Interconnect Topologies

This study looks at the high-level trade-offs for interconnect architectures that are likely to be available in HPC machines in the 2021-2022 timeframe. The study uses multiple simulation models to look at the effects of varying machine size, injection bandwidth and topology for a selected set of benchmark communication patterns. The studies show the sensitivity of various applications to these network parameters. This study can help inform decisions on node size versus number of nodes, which topology is most efficient for our applications, how much injection bandwidth to provision, etc. These simulations only look at interconnects with maximally configured global bandwidth, and studies of networks configured with less will be the subject of future milestones.

97 MATHEMATICS AND COMPUTING↗

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

RASM is a multi-disciplinary project, which brings together researchers from six state universities, one military postgraduate school, and one DoE laboratory to address the core modeling objectives of the arctic research community articulated in the Arctic System Modeling report by Roberts et al. (2010b). This report advocates the construction of a regional downscaling tool to generate probabilistic decadal projections of Greenland ice sheet retreat, evolution of arctic sea ice cover, changes in land surface vegetation, and regional processes leading to arctic amplification. Unified coupled models such as RASM are ideal for this purpose because they simulate fine-scale physics, essential for the realistic representation of intra-annual variability, in addition to processes fundamental to long term climatic shifts (Hurrell et al. 2009). By using RASM with boundary conditions from a global model, we can generate many-member ensembles essential for understanding uncertainty in regional climate projections (Hawkins and Sutton 2009). This probabilistic approach is computationally prohibitive for high-resolution global models in the foreseeable future, and also for regional models interactively nested within global simulations. Yet it is fundamental for quantifying uncertainty in decadal forecasts to make them useful for decision makers (Doherty et al. 2009). For this reason, we have targeted development of ensemble generation techniques as a core project task (Task 4.5). Environmental impact assessment specialists need high-fidelity regional ensemble projections to improve the accuracy of their work (Challinor et al. 2009; Moss et al. 2010). This is especially true of the Arctic, where economic, social and national interests are rapidly reshaping the high north in step with regional climate change. During the next decade, considerable oil and gas discoveries are expected across many parts of the marine and terrestrial Arctic (Gautier et al. 2009), the economics of the Northern Sea Route will steadily improve (Arctic Council 2009), and sovereign claims over the Arctic Ocean will increasingly be subject to international negotiations (Proelss 2009). Issues such as these have led to an expanding demand for Arctic climate projections to aid national and commercial decisions. However, detailed information from existing models is lacking. RASM will enhance the existing Arctic system modeling capabilities and align them with the scientific and societal needs outlined above. The science involved in the development of RASM will be integrated with teaching and training at a few different levels. RASM PIs will supervise at least six postdoctoral and doctoral students with additional involvement of undergraduate research assistants. RASM postdoctoral fellows and graduate trainees will benefit from being a part of a large, collaborative, and multi-disciplinary research projects employing state-of-the-art modeling and computational tools. They will also have the opportunity to contribute to the UTEP-led education and outreach effort developed specifically for RASM. The UTEP team will use RASM as a platform for education and outreach. First, we will develop products for public dissemination, such as curriculum units, lesson plans and other materials (simulations, movies, and images) for use by students and teachers in high school and university classrooms. Second, we will facilitate bringing RASM PIs, postdocs, and graduate students into the classroom, through electronic mentorship and by contributing content via online lectures and presentations. Third, by the use of problem-based learning (PBL) approaches, we will provide real-world scenarios and problems enabling students to do research and develop position papers or presentations on topics related to RASM. (Problem-based learning is a student-centered, inquiry-based approach in which students work in teams to solve challenging, open-ended problems.) Fourth, we will develop teacher-training materials that will be developed into workshops (face-to-face or online) to help teachers understand how to use the materials we supply. Overall, we will provide a broad, and long-term RASM program for education and outreach. RASM education and outreach activities will target underrepresented populations - in particular, Hispanic students and teachers. For example, the UTEP student body is more than 70 percent Hispanic and 55 percent female, and the majority of students are the first in their families to attend college. Students from underrepresented groups will be given the chance to expand their understanding of the different scientific knowledge and processes associated with RASM. We will develop an eye-catching RASM website to include information about the project, model results and educational materials, and lists of RASM publications and presentations.

54 ENVIRONMENTAL SCIENCES↗

Summer Report: Tool Integration for Variable-Precision Computing

This summer I worked in the tools group of the variable-precision computing effort at Lawrence Livermore National Laboratory (LLNL). I coordinated an integration project that combined three existing tools into a single pipeline for automated mixed-precision tuning at the source code level. This involved coordinating efforts between several different project groups and making improvements to all three tools. Two of the tools are already available publicly as open-source projects, and the third has been submitted for release. This document serves as an overview of the summer's efforts, focusing on our contributions as well as ideas for future work.

97 MATHEMATICS AND COMPUTING↗