Search NASA⌕ Search

SEARCH · Search NASA

Results for “code sharing”

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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

OpenMP application experiences: Porting to accelerated nodes

As recent enhancements to the OpenMP specification become available in its implementations, there is a need to share the results of experimentation in order to better understand the OpenMP implementation’s behavior in practice, to identify pitfalls, and to learn how the implementations can be effectively deployed in scientific codes. We report on experiences gained and practices adopted when using OpenMP to port a variety of ECP applications, mini-apps and libraries based on different computational motifs to accelerator-based leadership-class high-performance supercomputer systems at the United States Department of Energy. Additionally, we identify important challenges and open problems related to the deployment of OpenMP. Through our report of experiences, we find that OpenMP implementations are successful on current supercomputing platforms and that OpenMP is a promising programming model to use for applications to be run on emerging and future platforms with accelerated nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Ion temperature gradient turbulence modification in quasi-axisymmetry

The large flexibility of the proposed QUASAR facility is leveraged in order to explore the effect of magnetic shear on adiabatic Ion Temperature Gradient (ITG) turbulence. The QUASAR facility is a reimagining of the National Compact Stellarator Experiment utilizing and expanding upon the already constructed coil set. Recent work using fixed boundary optimization of the LI383 equilibrium (upon which QUASAR is based) has suggested possible improvements to ITG turbulence. In this work, a different approach is taken, wherein a series of self-consistent free boundary VMEC equilibria are developed for QUASAR. These equilibria assume temperature and density profiles consistent with 2% beta and ohmic current drive. In each configuration, the toroidal field coils are energized to different values and the STELLOPT code is used to vary the modular coil current and net toroidal current. The edge value of rotational transform is targeted in the optimization, producing a magnetic shear scan. All these configurations share similar neoclassical transport levels, while nonlinear GENE flux tube simulations show up to a factor of four change in adiabatic ITG turbulence at various radii. Comparisons of proxy functions and linear flux tube runs are also made. This work highlights the capability of the QUASAR experiment as a tool to explore transport in 3D magnetic fields and the possibility of the further improvements to stellarators through optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

The 2017 Bioinformatics Open Source Conference (BOSC)

The Bioinformatics Open Source Conference (BOSC) is a meeting organized by the Open Bioinformatics Foundation (OBF), a non-profit group dedicated to promoting the practice and philosophy of Open Source software development and Open Science within the biological research community. The 18th annual BOSC ( http://www.open-bio.org/wiki/BOSC_2017 ) took place in Prague, Czech Republic in July 2017. The conference brought together nearly 250 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, open and reproducible science, and this year’s theme, open data. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community, called the OBF Codefest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Hardware Evaluation: Abstract Machine Models and Proxy Architectures for Exascale Computing

The strategic and economic impacts of high performance computing (HPC) systems, over the last several decades, have enabled dramatic improvements in manufacturing, design, development, and research, across almost every sector of the U.S. economy, including genetic analysis for agriculture and medicine, oil exploration, electronics, aircraft, and automotive design, and of course national defense technologies. HPC has repeatedly compounded reductions in time-to-solution and time-to-market in each of these areas. In recognition of these strategic and economic impacts, the Department of Energy (DOE) created the Exascale Computing Project (ECP) as a broad-based technology project focusing on simultaneously co-evolving high-performance computing architecture, system software, and application software. While many details of the exascale architectures are undefined, communicating the form and direction of this co-evolution of advances, in each of these three components, across the project, presents a need for a common language through which these advances can be shared. In this document we present a series of abstract representations designed to allow application developers to focus on the aspects of the machine that are important or relevant to performance and code structure. These abstract machine models (AMMs) describe the proposed architectures at the component and system level and are intended as communication aids between application developers and hardware architects during the co-design process. In addition to providing a common language for communication, the constraints of protecting the intellectual property of ECP’s vendor partners requires that the architectural advances be presented in an abstract sense, rather than exposing the specifics of an individual vendor’s designs, while still providing enough detail such that application developers will be able to reason about the performance trade-offs in the design space of their applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Implementing Directive-Based Deferred Execution for Effective Network Aggregation

Remote direct memory access technology provides an efficient mechanism for one-sided communication that can be leveraged to implement a distributed shared memory programming model. However, when applications generate large numbers of small, irregular messages, network congestion often arises. Existing solutions address this small message problem by facilitating message aggregation but typically require disruptive code transformations that detract from the algorithmic intent of applications, or can be limited by dependent operations on aggregated data between synchronisation points. A solution is to use a directive-assisted approach that enables compilers to transform code dependent on aggregated communication for deferred execution. This paper presents an algorithm that a compiler can use to implement and optimise deferred execution for code dependent on aggregated data, based on an "aggregation context" extension for the OpenSHMEM partitioned global address space library. This new capability addresses a key challenge of message aggregation, allowing its full potential to reduce network congestion and enhance programmability to be realised.

Welch, Aaron [ORNL]↗
DOE OSTI2024

SINGLE BUNCH TRACKING ON THE TEN-PASS ER@CEBAF ENERGY RECOVERY BEAMLINE

The proposed ten-pass energy recovery linac (ERL) demonstration (five accelerating, five decelerating) at the CEBAF accelerator, ER@CEBAF, involves a multi-GeV en- ergy range of a continuous electron beam. New CEBAF transverse optics were designed for this ERL demonstration. This redesign incorporates additional components in Arc A, including a path length chicane and new quadrupoles to ensure proper dispersion localization. The new five energy recovery passes with a shared arc transport scheme chal- lenge the overall beamline optics design, including large beta functions in the CEBAF spreaders and recombiners. Here we discuss results of bunch tracking performed using the elegant tracking code for the full ER@CEBAF beamline

Neththikumara, I.↗
NASA NTRS1997

Mitochondrial gene arrangement of the horseshoe crab Limulus polyphemus L.: conservation of major features among arthropod classes

Numerous complete mitochondrial DNA sequences have been determined for species within two arthropod groups, insects and crustaceans, but there are none for a third, the chelicerates. Most mitochondrial gene arrangements reported for crustaceans and insect species are identical or nearly identical to that of Drosophila yakuba. Sequences across 36 of the gene boundaries in the mitochondrial DNA (mtDNA) of a representative chelicerate. Limulus polyphemus L., also reveal an arrangement like that of Drosophila yakuba. Only the position of the tRNA(LEU)(UUR) gene differs; in Limulus it is between the genes for tRNA(LEU)(CUN) and ND1. This positioning is also found in onychophorans, mollusks, and annelids, but not in insects and crustaceans, and indicates that tRNA(LEU)(CUN)-tRNA(LEU)(UUR)-ND1 was the ancestral gene arrangement for these groups, as suggested earlier. There are no differences in the relative arrangements of protein-coding and ribosomal RNA genes between Limulus and Drosophila, and none have been observed within arthropods. The high degree of similarity of mitochondrial gene arrangements within arthropods is striking, since some taxa last shared a common ancestor before the Cambrian, and contrasts with the extensive mtDNA rearrangements occasionally observed within some other metazoan phyla (e.g., mollusks and nematodes).

Non-NASA Center↗
NASA NTRS2009

Extreme Programming: Maestro Style

"Extreme Programming: Maestro Style" is the name of a computer programming methodology that has evolved as a custom version of a methodology, called extreme programming that has been practiced in the software industry since the late 1990s. The name of this version reflects its origin in the work of the Maestro team at NASA's Jet Propulsion Laboratory that develops software for Mars exploration missions. Extreme programming is oriented toward agile development of software resting on values of simplicity, communication, testing, and aggressiveness. Extreme programming involves use of methods of rapidly building and disseminating institutional knowledge among members of a computer-programming team to give all the members a shared view that matches the view of the customers for whom the software system is to be developed. Extreme programming includes frequent planning by programmers in collaboration with customers, continually examining and rewriting code in striving for the simplest workable software designs, a system metaphor (basically, an abstraction of the system that provides easy-to-remember software-naming conventions and insight into the architecture of the system), programmers working in pairs, adherence to a set of coding standards, collaboration of customers and programmers, frequent verbal communication, frequent releases of software in small increments of development, repeated testing of the developmental software by both programmers and customers, and continuous interaction between the team and the customers. The environment in which the Maestro team works requires the team to quickly adapt to changing needs of its customers. In addition, the team cannot afford to accept unnecessary development risk. Extreme programming enables the Maestro team to remain agile and provide high-quality software and service to its customers. However, several factors in the Maestro environment have made it necessary to modify some of the conventional extreme-programming practices. The single most influential of these factors is that continuous interaction between customers and programmers is not feasible.

Norris, Jeffrey↗
NASA NTRSDate not supplied

DELTA: An Open-Source Framework to Simplify Deep Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA for deep learning on satellite imagery based on tensorflow. It helps simplify data engineering and preprocessing steps and reduces the need for a lot of the boilerplate code that needs written to make datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the grunt work. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping.

Michael von Pohle↗
DOE OSTI2024

Accelerating Application Bulk Synchronous Writes in HPC Environments

High-bandwidth storage tiers are becoming more common for their capability to absorb high-rate, bursty I/Os. Notably, the designs of these fast storage tiers differ from system to system. The variation of these layers and non-uniform methods of access can pose chal- lenges for applications seeking to run at multiple HPC facilities. Therefore, in this work, we present Spectral, a rapid-output ab- straction library to accelerate application, bulk-synchronous writes on HPC systems. We design Spectral to enable applications to use high-bandwidth storage, such as node-local storage and dis- tributed, write-caches (e.g., burst buffers) transparently without requiring modifications to the application or file system source code. The key idea is to allow applications to spend most of the time performing productive work and to not require any source code changes for maximum portability on different HPC archi- tectures. Spectral internally re-routes write-only files through available, high-performance I/O resources before ultimately mi- grating them to the shared global parallel file system. For instance, on Summit, Spectral transparently places application outputs on node-local storage and then utilizes asynchronous migration to the center-wide GPFS file system. We evaluate Spectral on the Summit HPC system (1024 nodes) using the IOR benchmark and real scientific applications. Spectral shows linear performance scaling, improving application write performance by over an order of magnitude when compared to GPFS.

Khan, Awais↗
DOE OSTI2024

Planar slicing for nonextrusion AM processes

Extrusion-based AM processes, including material extrusion and directed energy deposition, construct objects by continuously depositing a relatively small amount of molten feedstock to a specific location. Nonextrusion AM processes, on the other hand, tend to form each layer by linearly or areally projecting either energy onto a vat of photocurable liquid or a binding agent into a bed of loose powder. Such systems vary significantly from extrusion-based AM processes but do share similarities. The general approach to path planning is the same, but nonextrusion processes typically favor the use of bitmap representations, instead of polygons, for pathing computation and do not use a g-code file to command the printer. In this chapter, a high-level discussion of these differences will be covered.

Macdonald, Eric↗
NASA NTRS2011

Use of Apollo 17 Epoch Neutron Spectrum as a Benchmark in Testing LEND Collimated Sensor

The Apollo 17 neutron experiment LPNE provided a unique set of data on production of neutrons in the Lunar soil bombarded by Galactic Cosmic Rays (GCR). It serves as valuable "ground-truth" in the age of orbital remote sensing. We used the neutron data attributed to Apollo 17 epoch as a benchmark for testing the LEND's collimated sensor, as introduced by the geometry of collimator and efficiency of He3 counters. The latter is defined by the size of gas counter and pressure inside it. The intensity and energy spectrum of neutrons escaping the lunar surface are dependent on incident flux of Galactic Cosmic Rays (GCR) whose variability is associated with Solar Cycle and its peculiarities. We obtain first the share of neutrons entering through the field of view of collimator as a fraction of the total neutron flux by using the angular distribution of neutron exiting the Moon described by our Monte Carlo code. We computed next the count rate of the 3He sensor by using the neutron energy spectrum from McKinney et al. [JGR, 2006] and by consider geometry and gas pressure of the LEND sensor. Finally the neutron count rate obtained for the Apollo 17 epoch characterized by intermediate solar activity was adjusted to the LRO epoch characterized by low solar activity. It has been done by taking into account solar modulation potential, which affects the GCR flux, and in turn changes the neutron albedo flux.

Chin, Gordon↗
DOE OSTI2015

CosmoSIS: Modular cosmological parameter estimation

Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. Here we present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in CosmoSIS, including CAMB, Planck, cosmic shear calculations, and a suite of samplers. Lastly, we illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Performance upgrades to the MCNP6 burnup capability for large scale depletion calculations

The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. With the merger of MCNPX and MCNP5, MCNP6 combined the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. The new MCNP6 depletion capability was first showcased at the International Congress for Advancements in Nuclear Power Plants (ICAPP) meeting in 2012. At that conference the new capabilities addressed included the combined distributive and shared memory parallel architecture for the burnup capability, improved memory management, physics enhancements, and new predictability as compared to the H.B Robinson Benchmark. At Los Alamos National Laboratory, a special purpose cluster named “tebow,” was constructed such to maximize available RAM per CPU, as well as leveraging swap space with solid state hard drives, to allow larger scale depletion calculations (allowing for significantly more burnable regions than previously examined). As the MCNP6 burnup capability was scaled to larger numbers of burnable regions, a noticeable slowdown was realized.This paper details two specific computational performance strategies for improving calculation speedup: (1) retrieving cross sections during transport; and (2) tallying mechanisms specific to burnup in MCNP. To combat this slowdown new performance upgrades were developed and integrated into MCNP6 1.2.

42 ENGINEERING↗
DOE OSTI2022

Design of an Additively Manufactured Recuperator With 800 °C Inlet Temperature for sCO2 Power Cycle Application

Abstract Recuperators with design temperatures at and above 800 °C can further increase the thermal efficiency of supercritical CO2 power cycles by enabling higher turbine exhaust temperatures. Mar-M247 is a well-suited nickel-based superalloy for high temperature service due to its high creep strength that prevents excessive material thickness being required for pressure containment. Additive manufacturing using a high-speed laser-directed energy deposition (L-DED) process presents a promising solution, with build trials demonstrating the ability to produce nonconventional flow channels for enhanced heat transfer. A design process is presented that includes aerothermal and mechanical evaluation to maximize performance within the constraints of the manufacturing process. A 2-D heat transfer network and pressure drop code allows prediction of flow distribution and its effect on overall thermal performance. Established literature correlations, along with CFD simulation, inform the prediction of heat transfer coefficients and friction factors for the flowpaths and enhancement features in the heat exchanger core. Mechanical evaluation using finite element analysis (FEA) modeling with the intent of the ASME Boiler & Pressure Vessel Code (BPVC) Section VIII, Div. 2 assesses the operational safety of the design. The detailed design features annular finned passages that take advantage of helical flow paths to distribute the flow from separated headers to shared heat transfer surfaces. Performance predictions for the recuperator at a 50 kW scale provide insights into the feasibility of the additively manufactured (AM) process to produce recuperators on a commercial scale that extend existing operating envelopes.

Engineering↗
DOE OSTI2021

Evaluating the Performance of Integer Sum Reduction in SYCL on GPUs

SYCL is a promising programming model for heterogeneous computing—allowing a single-source code to target devices from multiple vendors. One significant task performed on these accelerators is a primitive operation for integer sum reduction. This paper presents several SYCL implementations of integer sum reduction—using atomic functions, shared local memory, vectorized memory accesses and parameterized workload sizes—to compare the performance and maturity of SYCL against open-source vendor-specific implementations of the same reduction. For a sufficiently large number of integers, tuning the parameters of our SYCL implementations achieves 1.4X speedup over the open-source implementations on an Intel UHD630 integrated GPU. The SYCL reduction is 3% faster than the templated reduction in Thrust, and 0.3% faster than the device reduction in CUB on an Nvidia P100 GPU. The SYCL reduction is 1.9% faster than the templated reduction in Thrust, and 0.4% faster than the device reduction in CUB on an Nvidia V100 GPU.

Jin, Zheming↗
NASA NTRSDate not supplied

DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources

Michael von Pohle↗