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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Designing Energy-Efficient Quantum Computers Through Prediction and Reduction of Cooling Requirements for Cryogenic Electronics

Quantum computing has been identified as a “wild card” by the International Energy Agency in predicting future global data center energy usage. This is primarily because both uncertainty in the extent to which quantum computing will be adopted, and uncertainty in the power consumption of individual quantum data centers. Unlike the classical counterparts, quantum computers need to be maintained at near absolute zero, requiring energy-intensive cryogenic cooling systems. Therefore, as quantum computers scale up from existing 50 qubit technology demonstrations to the 10,000 to 100,000 qubit systems that will be able to solve complex problems, the energy consumption of both the electronics and the required cooling systems will also increase. To predict this scaling, this work analyzes the energy requirements for both computation and cooling of quantum hardware. We show that the energy requirements for cooling of quantum computers is determined by several computing system parameters, including the number and type of physical qubits, the operating temperature, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. The energy requirements can then be found based on thermal system parameters such as cooling efficiency and cryostat heat transfer. Analysis of these parameters shows that the energy required for cooling is significantly larger than that required for computation, a reversal from energy usage patterns seen in conventional computing. The results and discussions provide a road-map for creating energy efficient quantum computers through the selection of computer architectures and cryogenic system configurations that minimize cooling requirements.

energy efficiency↗
DOE OSTI2017

Sustaining Moore's law with 3D chips

Here, rather than continue the expensive and time-consuming quest for transistor replacement, the authors argue that 3D chips coupled with new computer architectures can keep Moore's law on its traditional scaling path.

3D chip manufacturing↗
DOE OSTI2024

Towards exascale for wind energy simulations

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer flows that are of direct relevance to wind energy production. The first code, NekRS, is a high-order, unstructured-grid, spectral element code. The second code, AMR-Wind, is a second-order, block-structured, finite-volume code with adaptive mesh refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system, using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

17 WIND ENERGY↗
NASA NTRS1989

Group implicit concurrent algorithms in nonlinear structural dynamics

During the 70's and 80's, considerable effort was devoted to developing efficient and reliable time stepping procedures for transient structural analysis. Mathematically, the equations governing this type of problems are generally stiff, i.e., they exhibit a wide spectrum in the linear range. The algorithms best suited to this type of applications are those which accurately integrate the low frequency content of the response without necessitating the resolution of the high frequency modes. This means that the algorithms must be unconditionally stable, which in turn rules out explicit integration. The most exciting possibility in the algorithms development area in recent years has been the advent of parallel computers with multiprocessing capabilities. So, this work is mainly concerned with the development of parallel algorithms in the area of structural dynamics. A primary objective is to devise unconditionally stable and accurate time stepping procedures which lend themselves to an efficient implementation in concurrent machines. Some features of the new computer architecture are summarized. A brief survey of current efforts in the area is presented. A new class of concurrent procedures, or Group Implicit algorithms is introduced and analyzed. The numerical simulation shows that GI algorithms hold considerable promise for application in coarse grain as well as medium grain parallel computers.

Ortiz, M.↗
DOE OSTI2024

Fiber optic computing using distributed feedback

Abstract The widespread adoption of machine learning and other matrix intensive computing algorithms has renewed interest in analog optical computing, which has the potential to perform large-scale matrix multiplications with superior energy scaling and lower latency than digital electronics. However, most optical techniques rely on spatial multiplexing, requiring a large number of modulators and detectors, and are typically restricted to performing a single kernel convolution operation per layer. Here, we introduce a fiber-optic computing architecture based on temporal multiplexing and distributed feedback that performs multiple convolutions on the input data in a single layer. Using Rayleigh backscattering in standard single mode fiber, we show that this technique can efficiently apply a series of random nonlinear projections to the input data, facilitating a variety of computing tasks. The approach enables efficient energy scaling with orders of magnitude lower power consumption than GPUs, while maintaining low latency and high data-throughput.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

HPC I/O innovations in the exascale era

As high performance computing architecture evolves to deliver ever-increasing performance, the middleware tools also need to adapt in order for applications to better use these higher-performance features. Here, the Adaptable Input Output System (ADIOS), which provides scalable IO performance for exascale HPC applications is one such middleware. During the Exascale Computing Project (ECP), key portions of the ADIOS environment were adapted to respond to ongoing developments in exascale computing and the stresses and opportunities inherent in those changes. This paper examines those changes and where appropriate compares them to pre-exascale implementations.

ADIOS↗
DOE OSTI2025

Comparing cross-platform performance via node-to-node scaling studies

Due to the increasing diversity of high-performance computing architectures, researchers and practitioners are increasingly interested in comparing a code’s performance and scalability across different platforms. However, there is a lack of available guidance on how to actually set up and analyze such cross-platform studies. In this paper, we contend that the natural base unit of computing for such studies is a single compute node on each platform and offer guidance in setting up, running, and analyzing node-to-node scaling studies. In conclusion, we propose templates for presenting scaling results of these studies and provide several case studies highlighting the benefits of this approach.

cross-platform studies↗
NASA NTRS1991

High performance computing system for flight simulation at NASA Langley

The computer architecture and components used in the NASA Langley Advanced Real-Time Simulation System (ARTSS) are briefly described and illustrated with diagrams and graphs. Particular attention is given to the advanced Convex C220 processing units, the UNIX-based operating system, the software interface to the fiber-optic-linked Computer Automated Measurement and Control system, configuration-management and real-time supervisor software, ARTSS hardware modifications, and the current implementation status. Simulation applications considered include the Transport Systems Research Vehicle, the Differential Maneuvering Simulator, the General Aviation Simulator, and the Visual Motion Simulator.

Cleveland, Jeff I., II↗
DOE OSTI2023

A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow

Background: Wildfires are becoming more severe, so we need improved tools to predict them over a wide range of conditions and scales. One approach towards this goal entails the use of coupled fire/atmosphere modelling tools. Although significant progress has been made in advancing their physical fidelity, existing tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. Aims: The aim of this study was to present a new framework that enables landscape-scale wildfire simulations with physical representation of combustion at an affordable cost. Methods: We developed a coupled fire/atmosphere simulation framework using TensorFlow, which enables efficient and scalable computations on Tensor Processing Units. Key Results: Simulation results for a prescribed fire were compared with experimental data. Predicted fire behavior and statistical analysis for fire spread rate, scar area, and intermittency showed overall reasonable agreement. Scalability analysis was performed, showing close to linear scaling. Conclusions: While mesh refinement was shown to have less impact on global quantities, such as fire scar area and spread rate, it benefits predictions of intermittent fire behavior, buoyancy-driven dynamics, and small-scale turbulent motion. Implications: This new simulation framework is efficient in capturing both global quantities and unsteady dynamics of wildfires at high spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Final Technical Report for CMSC 838L

This paper describes Rahul Vishnoi’s final project supporting in his Graduate School curriculum CMSC 838L, Advanced Topics in Programming Languages and Computer Architecture. This project was selected to intersect with his work as a Pathways Intern supporting Code 583, the Ground Software Systems Branch, at NASA’s Goddard Space Flight Center (GSFC). In this project, Field Programmable Gate Array (FPGA) hardware from Xilinx is used to replace and offload processor and memory-intensive computations from a microcontroller/Processing System (PS) to the FPGA Programmable Logic (PL). An interface between the PL and PS in the form of a C library allows for this bridging of capability.

Microcontroller, FPGA, Embedded Development, Xilin↗
NASA NTRSDate not supplied

Rapid Spacecraft Payload Development: In-Orbit Demonstration of Flight Software Reuse, Scalability, and Dependability

As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.

computer programming↗
DOE OSTI2021

MATAR: A performance portability and productivity implementation of data-oriented design with Kokkos

There is a need for simple, fast, and memory-efficient multidimensional data structures for dense and sparse storage that arise with numerical methods and in software applications. The data structures must perform equally well across multiple computer architectures, including CPUs and GPUs. For this purpose, we developed MATAR, a C++ software library that allows for simple creation and use of intricate data structures that is also portable across disparate architectures using Kokkos. Here, the performance aspect is achieved by forcing contiguous memory layout (or as close to contiguous as possible) for multidimensional and multi-size dense or sparse MATrix and ARray (hence, MATAR) types. Our results show that MATAR has the capability to improve memory utilization, performance, and programmer productivity in scientific computing. This is achieved by fitting more work into the available memory, minimizing memory loads required, and by loading memory in the most efficient order. This document describes the purpose of the work, the implementation of each of the data types, and the resulting performance both in some simple baseline test cases and in an application code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Cosmological neutrino simulations at extreme scale

Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision from theoretical predictions of neutrino clustering. Numerical simulations of the non-linear evolution of cold dark matter and neutrinos play a pivotal role in this process. We incorporate neutrinos into the cosmological N-body code CUBEP3M and discuss the challenges associated with pushing to the extreme scales demanded by the neutrino problem. We highlight code optimizations made to exploit modern high performance computing architectures and present a novel method of data compression that reduces the phase-space particle footprint from 24 bytes in single precision to roughly 9 bytes. We scale the neutrino problem to the Tianhe-2 supercomputer and provide details of our production run, named TianNu, which uses 86% of the machine (13,824 compute nodes). With a total of 2.97 trillion particles, TianNu is currently the world’s largest cosmological N-body simulation and improves upon previous neutrino simulations by two orders of magnitude in scale. We finish with a discussion of the unanticipated computational challenges that were encountered during the TianNu runtime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hardware design and testing of the generic rear transition module for the global trigger subsystem of ATLAS Phase-II Upgrade

Abstract In the framework of the ATLAS experiment’s Phase-II Upgrade at the High-Luminosity Large Hadron Collider (HL-LHC), new and improved trigger hardware and algorithms will be implemented onto a single-level, 10 μs-latency architecture. The Global Trigger is a new subsystem which will bring event-filter capabilities by performing offline-like algorithms on full-granularity calorimeter data. The implementation of the functionality is firmware-focused and composed of several processing nodes, which are hosted on identical hardware, made up of an Advanced Telecommunications Computing Architecture (ATCA) front board, called Global Common Module (GCM), and a rear transition module (RTM), called Generic RTM (GRM). The GRM, which was developed to mitigate the risks deriving from the complex design and power management of the GCM, features an advanced Xilinx Versal Prime system-on-chip and can handle communication with the GCM and Front-End Link eXchange (FELIX) subsystem and trigger processors through 124 25.8 Gb/s transceiver links, for readout and control. Additionally, the GRM mounts a Low-Power GigaBit Transceiver (lpGBT) chip which enables emulation of the detector front-ends for integration tests. This paper presents the GRM hardware design and its testing.

Instruments & Instrumentation↗
DOE OSTI2013

HPC Colony II: FAST_OS II: Operating Systems and Runtime Systems at Extreme Scale

HPC Colony II has been a 36-month project focused on providing portable performance for leadership class machines—a task made difficult by the emerging variety of more complex computer architectures. The project attempts to move the burden of portable performance to adaptive system software, thereby allowing domain scientists to concentrate on their field rather than the fine details of a new leadership class machine. To accomplish our goals, we focused on adding intelligence into the system software stack. Our revised components include: new techniques to address OS jitter; new techniques to dynamically address load imbalances; new techniques to map resources according to architectural subtleties and application dynamic behavior; new techniques to dramatically improve the performance of checkpoint-restart; and new techniques to address membership service issues at scale.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Interfacing Computer Aided Parallelization and Performance Analysis

When porting sequential applications to parallel computer architectures, the program developer will typically go through several cycles of source code optimization and performance analysis. We have started a project to develop an environment where the user can jointly navigate through program structure and performance data information in order to make efficient optimization decisions. In a prototype implementation we have interfaced the CAPO computer aided parallelization tool with the Paraver performance analysis tool. We describe both tools and their interface and give an example for how the interface helps within the program development cycle of a benchmark code.

Jost, Gabriele↗
NASA NTRS2011

Architecture for a 1-GHz Digital RADAR

An architecture for a Direct RF-digitization Type Digital Mode RADAR was developed at GSFC in 2008. Two variations of a basic architecture were developed for use on RADAR imaging missions using aircraft and spacecraft. Both systems can operate with a pulse repetition rate up to 10 MHz with 8 received RF samples per pulse repetition interval, or at up to 19 kHz with 4K received RF samples per pulse repetition interval. The first design describes a computer architecture for a Continuous Mode RADAR transceiver with a real-time signal processing and display architecture. The architecture can operate at a high pulse repetition rate without interruption for an infinite amount of time. The second design describes a smaller and less costly burst mode RADAR that can transceive high pulse repetition rate RF signals without interruption for up to 37 seconds. The burst-mode RADAR was designed to operate on an off-line signal processing paradigm. The temporal distribution of RF samples acquired and reported to the RADAR processor remains uniform and free of distortion in both proposed architectures. The majority of the RADAR's electronics is implemented in digital CMOS (complementary metal oxide semiconductor), and analog circuits are restricted to signal amplification operations and analog to digital conversion. An implementation of the proposed systems will create a 1-GHz, Direct RF-digitization Type, L-Band Digital RADAR--the highest band achievable for Nyquist Rate, Direct RF-digitization Systems that do not implement an electronic IF downsample stage (after the receiver signal amplification stage), using commercially available off-the-shelf integrated circuits.

Mallik, Udayan↗
DOE OSTI2022

Spectral quadrature for the first principles study of crystal defects: Application to magnesium

In this work, we present an accurate and efficient finite-difference formulation and parallel implementation of Kohn-Sham Density (Operator) Functional Theory (DFT) for non periodic systems embedded in a bulk environment. Specifically, employing non-local pseudopotentials, local reformulation of electrostatics, and truncation of the spatial Kohn-Sham Hamiltonian, and the Linear Scaling Spectral Quadrature method to solve for the pointwise electronic fields in real-space and the non-local component of the atomic force, we develop a parallel finite difference framework suitable for distributed memory computing architectures to simulate non-periodic systems embedded in a bulk environment. Choosing examples from magnesium-aluminum alloys, we first demonstrate the convergence of energies and forces with respect to spectral quadrature polynomial order, and the width of the spatially truncated Hamiltonian. Next, we demonstrate the parallel scaling of our framework, and show that the computation time and memory scale linearly with respect to the number of atoms. Next, we use the developed framework to simulate isolated point defects and their interactions in magnesium-aluminum alloys. Our findings conclude that the binding energies of divacancies, Al solute-vacancy and two Al solute atoms are anisotropic and are dependent on cell size. Furthermore, the binding is favorable in all three cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗