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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Exploring the Limits of Cooling for Extreme Heat Flux Applications: Data Centers and Power Electronic

We developed an Extreme Heat Flux Micro-cooler (EHFµ-C) capable of removing heat flux of ~1 kW/cm 2 with a small temperature rise ~10°C. This represents greater than 10× reduction in thermal resistance compared to the state-of-the-art single-phase cooling technologies (~0.5 cm 2 -°C/W) that greatly increases the efficiency, resulting in improved performance and reliability for microprocessors and power electronics. The EHFµ-Cooler utilizes liquid wicking (no pump) and thin-film evaporation in a 30 µm thick wick porous microstructure such as copper inverse opal (CIO), silicon and AlN pin fins along with a 3D manifold (copper wiremesh and silicon) with liquid routing and vapor extraction channels achieving an unprecedented vapor quality ~ >0.9. The proposed EHFµ-Cooler significantly reduces device temperature, resulting in 25-50% improvement in reliability and device performance. Based on very conservative estimates, the total energy saving for data centers due to improved performance can be 6 billion kWh/year (>$300M). Better cooling, leading to more efficient, higher performance and more reliable power electronics, would save the nation 3 Quad of primary energy in 2030. Just for automotive application, a 10% increase in fuel efficiency for SiC-based power electronics equates to >20 million gallons of fuel savings annually. The proposed EHFµ-Cooler technology ensures the United States maintains its technological lead in high-performance computing and high-power electronics, while at the same time improving the energy efficiency, and as a result reducing energy-related emissions such as greenhouse gases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

Modem Handles Data At 160 Mb/s

Trellis-coded octal-phase-shift-keying modem transmits and receives continuous or bursted digital data for satellite applications. Helps satisfy increasing demands for communication of high-speed digital data from sources like high-performance computers and high-definition television transmitters, as well as multiplexed signals from slower signal sources. Increases maximum effective bit rate accommodated in standard 72-MHz-wide commercial satellite-transponder radio channel from 120 Mb/s to 160 Mb/s. Principal advantages: spectral efficiency and power efficiency.

Budinger, James M.↗
NASA NTRS1993

New computing systems, future computing environment, and their implications on structural analysis and design

Recent advances in computer technology that are likely to impact structural analysis and design of flight vehicles are reviewed. A brief summary is given of the advances in microelectronics, networking technologies, and in the user-interface hardware and software. The major features of new and projected computing systems, including high performance computers, parallel processing machines, and small systems, are described. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed. The impact of the advances in computer technology on structural analysis and the design of flight vehicles is described. A scenario for future computing paradigms is presented, and the near-term needs in the computational structures area are outlined.

Noor, Ahmed K.↗
NASA NTRS1990

Are highly parallel systems ready for prime time?

This is the edited and abbreviated transcript of a panel discussion held on May 9, 1989, in Los Angeles, during the conference "Parallel Computational Fluid Dynamics-Implementations and Results Using MIMD Computers." The purpose of the conference was to discuss recent developments in the use of MIMD parallel computers in high-performance computational fluid dynamics. The intent of the panel discussion was to summarize the findings of the meeting, and to give a perspective on the state of the art in using parallel computers for solving large-scale engineering and scientific application problems. The panelists were Creon Levit (NAS Systems Division, NASA-Ames Research Center, Moffett Field, California), Kent Misegades (Cray Research, Inc., Mendota Heights, Minnesota), Gary Montry (Myrias Computer Corporation, Albuquerque, New Mexico), Ken Neves (Boeing Computer Services, Seattle, Washington), Anthony Patera (Massachusetts Institute of Technology, Cambridge, Massachusetts), and Justin Rattner (Intel Scientific Computers, Beaverton, Oregon).

Simon, Horst D.↗
NASA NTRS1998

RIACS

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: (1) Automated Reasoning. (2) Human-Centered Computing. and (3) High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling.

Moore, Robert C.↗
NASA NTRS2002

Code Optimization and Parallelization on the Origins: Looking from Users' Perspective

Parallel machines are becoming the main compute engines for high performance computing. Despite their increasing popularity, it is still a challenge for most users to learn the basic techniques to optimize/parallelize their codes on such platforms. In this paper, we present some experiences on learning these techniques for the Origin systems at the NASA Advanced Supercomputing Division. Emphasis of this paper will be on a few essential issues (with examples) that general users should master when they work with the Origins as well as other parallel systems.

Chang, Yan-Tyng Sherry↗
NASA NTRS2002

RIACS FY2002 Annual Report

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

Leiner, Barry M.↗
NASA NTRSDate not supplied

Somatic Mutation Analysis in Spaceflight: NASA Twins Genome Study

The NASA Twins Genome Study investigates the effects of spaceflight on somatic mutation accumulation by comparing genome-wide sequence data from a spaceflight astronaut and his Earth-bound twin. Utilizing advanced computational software on high performance computers, this study identifies and maps somatic mutations, with implications for understanding spaceflight-associated health risks, including cancer, neurodegeneration, and cardiovascular disease. The findings aim to bridge rodent and human space research, offering insights into tissue-specific pathophysiology, risk models, and potential therapeutic interventions.

somatic mutation↗
DOE OSTI2023

Towards Lightweight Data Integration Using Multi-Workflow Provenance and Data Observability

Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a crucial role in scientific discovery, especially in the current AI era, by enabling Responsible AI development, FAIR, Reproducibility, and User Steering. However, the heterogeneous nature of science poses challenges such as dealing with multiple supporting tools, cross-facility environments, and efficient HPC execution. Building on data observability, adapter system design, and provenance, we propose MIDA: an approach for lightweight runtime Multi-workflow Integrated Data Analysis. MIDA defines data observability strategies and adaptability methods for various parallel systems and machine learning tools. With observability, it intercepts the dataflows in the background without requiring instrumentation while integrating domain, provenance, and telemetry data at runtime into a unified database ready for user steering queries. We conduct experiments showing end-to-end multi-workflow analysis integrating data from Dask and MLFlow in a real distributed deep learning use case for materials science that runs on multiple environments with up to 276 GPUs in parallel. We show near-zero overhead running up to 100,000 tasks on 1,680 CPU cores on the Summit supercomputer.

Santos Souza, Renan↗
DOE OSTI2015

R&D100: Lightweight Distributed Metric Service

On today's High Performance Computing platforms, the complexity of applications and configurations makes efficient use of resources difficult. The Lightweight Distributed Metric Service (LDMS) is monitoring software developed by Sandia National Laboratories to provide detailed metrics of system performance. LDMS provides collection, transport, and storage of data from extreme-scale systems at fidelities and timescales to provide understanding of application and system performance with no statistically significant impact on application performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Preemptive resource management for dynamically arriving tasks in an oversubscribed heterogeneous computing system

We design resource management heuristics that assign serial tasks to the nodes of a heterogeneous high performance computing (HPC) system. The value of completing these tasks is modeled using monotonically decreasing utility functions that represent the time-varying importance of the task. The value of completing a task is equal to its utility function at the time of its completion. The overall performance of this system is measured using the total utility earned by all tasks during some interval of time. To maximize the performance of such a system where the preemption of tasks is possible, we have designed, analyzed, and compared a set of resource allocation heuristic techniques. We combine two utility-aware heuristics with three different preemption techniques to create six preemption-capable heuristics. We also consider the two utility-aware heuristics without preemption. We use simulation studies to evaluate this set of eight heuristics and compare them with an FCFS heuristic, which is often used in real systems, and random assignments. In general, our set of eight heuristics is able to significantly outperform the comparison heuristics, and the preemption-capable heuristics are able to significantly increase the utility earned compared to the heuristics that do not use preemption. We analyze the performance tradeoffs among the different preemption-capable heuristics under a variety of oversubscribed workload environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Evaluating Performance Portability of OpenACC

Accelerator-based heterogeneous computing is gaining momentum in High Performance Computing arena. However, the increased complexity of the accelerator architectures demands more generic, high-level programming models. OpenACC is one such attempt to tackle the problem. While the abstraction endowed by OpenACC offers productivity, it raises questions on its portability. This paper evaluates the performance portability obtained by OpenACC on twelve OpenACC programs on NVIDIA CUDA, AMD GCN, and Intel MIC architectures. We study the effects of various compiler optimizations and OpenACC program settings on these architectures to provide insights into the achieved performance portability.

Sabne, Amit J↗
NASA NTRS1998

Workload Characterization of CFD Applications Using Partial Differential Equation Solvers

Workload characterization is used for modeling and evaluating of computing systems at different levels of detail. We present workload characterization for a class of Computational Fluid Dynamics (CFD) applications that solve Partial Differential Equations (PDEs). This workload characterization focuses on three high performance computing platforms: SGI Origin2000, EBM SP-2, a cluster of Intel Pentium Pro bases PCs. We execute extensive measurement-based experiments on these platforms to gather statistics of system resource usage, which results in workload characterization. Our workload characterization approach yields a coarse-grain resource utilization behavior that is being applied for performance modeling and evaluation of distributed high performance metacomputing systems. In addition, this study enhances our understanding of interactions between PDE solver workloads and high performance computing platforms and is useful for tuning these applications.

Waheed, Abdul↗
DOE OSTI2023

A Vision for Coupling Operation of US Fusion Facilities with HPC Systems and the Implications for Workflows and Data Management

The operation of large US Department of Energy (DOE) research facilities, like the DIII-D National Fusion Facility, results in the collection of complex multi-dimensional scientific datasets, both experimental and model-generated. In the future, it is envisioned that integrated data analysis coupled with large-scale high performance computing (HPC) simulations will be used to improve experimental planning and operation. Practically, massive data sets from these simulations provide the physics basis for generation of both reduced semi-analytic and machine-learning-based models. Storage of both HPC simulation datasets (generated from US DOE leadership computing facilities) and experimental datasets presents significant challenges. In this paper, we present a vision for a DOE-wide data management workflow that integrates US DOE fusion facilities with leadership computing facilities. Data persistence and long-term availability beyond the length of allocated projects is essential, particularly for verification and recalibration of artificial intelligence and machine learning (AI/ML) models. Because these data sets are often generated and shared among hundreds of users across multiple leadership computing facility centers, they would benefit from cross-platform accessibility, persistent identifiers (e.g. DOI, or digital object identifier), and provenance tracking. Here, the ability to handle different data access patterns suggests that a combination of low cost, high latency (e.g. for storing ML training sets) and high cost, low latency systems (e.g. for real-time, integrated machine control feedback) may be needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Compute Server Performance Results

Parallel-vector supercomputers have been the workhorses of high performance computing. As expectations of future computing needs have risen faster than projected vector supercomputer performance, much work has been done investigating the feasibility of using Massively Parallel Processor systems as supercomputers. An even more recent development is the availability of high performance workstations which have the potential, when clustered together, to replace parallel-vector systems. We present a systematic comparison of floating point performance and price-performance for various compute server systems. A suite of highly vectorized programs was run on systems including traditional vector systems such as the Cray C90, and RISC workstations such as the IBM RS/6000 590 and the SGI R8000. The C90 system delivers 460 million floating point operations per second (FLOPS), the highest single processor rate of any vendor. However, if the price-performance ration (PPR) is considered to be most important, then the IBM and SGI processors are superior to the C90 processors. Even without code tuning, the IBM and SGI PPR's of 260 and 220 FLOPS per dollar exceed the C90 PPR of 160 FLOPS per dollar when running our highly vectorized suite,

Stockdale, I. E.↗
DOE OSTI2017

Security and Cloud Outsourcing Framework for Economic Dispatch

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for the Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Digital Agriculture↗
DOE OSTI2014

Implementing Nonlinear Buoyancy and Excitation Forces in the WEC-Sim Wave Energy Converter Modeling Tool: Preprint

Wave energy converters (WECs) are commonly designed and analyzed using numerical models that combine multi-body dynamics with hydrodynamic models based on the Cummins Equation and linearized hydrodynamic coefficients. These modeling methods are attractive design tools because they are computationally inexpensive and do not require the use of high performance computing resources necessitated by high-fidelity methods, such as Navier Stokes computational fluid dynamics. Modeling hydrodynamics using linear coefficients assumes that the device undergoes small motions and that the wetted surface area of the devices is approximately constant. WEC devices, however, are typically designed to undergo large motions in order to maximize power extraction, calling into question the validity of assuming that linear hydrodynamic models accurately capture the relevant fluid-structure interactions. In this paper, we study how calculating buoyancy and Froude-Krylov forces from the instantaneous position of a WEC device (referred to as instantaneous buoyancy and Froude-Krylov forces from herein) changes WEC simulation results compared to simulations that use linear hydrodynamic coefficients. First, we describe the WEC-Sim tool used to perform simulations and how the ability to model instantaneous forces was incorporated into WEC-Sim. We then use a simplified one-body WEC device to validate the model and to demonstrate how accounting for these instantaneously calculated forces affects the accuracy of simulation results, such as device motions, hydrodynamic forces, and power generation.

13 HYDRO ENERGY↗