Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Portability”

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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The ArborX Library: Version 2.0

This article provides an overview of the 2.0 release of the ArborX library, a performance portable geometric search library based on Kokkos. We describe the major changes in ArborX 2.0 including a new interface for the library to support a wider range of user problems, new search data structures (brute force and distributed), support for user functions to be executed on the results (callbacks), and an expanded set of the supported algorithms (ray tracing and clustering).

GPU↗
DOE OSTI2020

Pre-exascale accelerated application development: The ORNL Summit experience

High-performance computing (HPC) increasingly relies on heterogeneous architectures to achieve higher performance. In the Oak Ridge Leadership Facility (OLCF), Oak Ridge, TN, USA, this trend continues as its latest supercomputer, Summit, entered production in early 2019. The combination of IBM POWER9 CPU and NVIDIA V100 GPU, along with a fast NVLink2 interconnect and other latest technologies, pushes system performance to a new height and breaks the exascale barrier by certain measures. Due to Summit's powerful GPUs and much higher GPU–CPU ratio, offloading to accelerators becomes a requirement for any application, which intends to effectively use the system. To facilitate navigating a complex landscape of competing heterogeneous architectures, a collection of applications from a wide spectrum of scientific domains is selected for early adoption on Summit. In this article, the experience and lessons learned are summarized, in the hope of providing useful guidance to address new programming challenges, such as scalability, performance portability, and software maintainability, for future application development efforts on heterogeneous HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Quantitative Failure Analysis on Capacity Fade in Rechargeable Lithium Metal Cells

Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.

25 ENERGY STORAGE↗
DOE OSTI2025

Elucidating Sodium-Sulfur Battery Chemistry using Operando Transmission X-ray Microscopy and X-ray Absorption Spectroscopy

Room-temperature sodium-sulfur (Na-S) batteries offer a beneficial and cost-effective solution for powering modern electric grids and devices. However, Na-S batteries suffer from performance decay during battery cycling due to the sluggish kinetics and polysulfide shuttling. Revealing the conversion mechanism of the Na-S chemistry is critical to designing high-capacity and stable Na-S batteries. In this study, we employed operando X-ray microscopy and operando X-ray absorption spectroscopy to elucidate the sulfur conversion in a carbon host using an ether-based electrolyte. We reveal the structural and chemical evolution of the sulfur cathode during cycling, which results in volume expansion and the dissolution of active material, ultimately affecting the battery performance. Our work provides fundamental insight into the sulfur reaction scheme, addressing the lingering challenges before establishing inexpensive Na-S batteries for broad applications, including portable electronics and large-scale energy storage.

Jagadeesan, Sathya Narayanan [SLAC National Accele↗
DOE OSTI2023

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗
DOE OSTI2020

HDF5-Version 1.12.0

The HDF5 library and file format implement the HDF5 data model for storing and managing data. This implementation supports an unlimited variety of datatypes and is designed for flexible and efficient I/O and for high volume and complex data. It is highly portable and extensible, allowing applications to evolve in their use of HDF5. The HDF5 Technology suite includes tools and applications for managing, manipulating, viewing, and analyzing data in the HDF5 format and other implementations.

The HDF Group, None↗
DOE OSTI2023

MPICH

MPICH is a high-performance and widely portable implementation of the MPI-4 standard from the Argonne National Laboratory. This release has all MPI 4 functions and features required by the standard with the exception of support for the user-defined data representations for I/O.

ECP↗
DOE OSTI2019

Electronic Structure Engine

INQ is an engine for electronic structure calculations. INQ is implemented as a C++ library of components designed to build a parallel, portable code for electronic structure calculations, including ground state and excited states. INQ is based on density functional theory (DFT). It can calculate ground state properties in DFT, and also excited states using time-dependent DFT (TDDFT) in real-time and linear-response. It implements different approximations for the exchange and correlation part: semi-local functionals like LDAs, GGAs and metaGGAs, and hybrid functionals that are implemented through the ACE approach for fast execution.

ANDRADE-VALENCIA, XAVIERI↗
DOE OSTI2020

A memory-driven mapping algorithm for heterogeneous systems

mpibind is a memory-driven algorithm to map parallel hybrid applications to the underlying hardware resources transparently, efficiently, and portably. There are two fundamental aspects of this algorithm. First, unlike existing mappings, its primary design point is the memory system. Compute elements are selected based on the identified memory components and not vice versa. Second, it embodies a global awareness of hybrid programming abstractions as well as heterogeneous devices.

Leon Borja, EdgarA↗
DOE OSTI2020

Quantum Fast Approximate Synthesis Tool (QFAST) v1.0.0

We present QFAST, a quantum synthesis tool designed to produce short circuits and to scale well in practice. Our contributions are: 1) a novel representation of circuits able to encode placement and topology; 2) a hierarchical approach with an iterative refinement formulation that combines "coarse-grained" fast optimization during circuit structure search with a good, but slower, optimization stage only in the final circuit instantiation stage. When compared against state-of-the-art techniques, although not optimal, QFAST can generate much shorter circuits for "time dependent evolution" algorithms used by domain scientists. We also show the composability and tunability of our formulation in terms of circuit depth and running time. For example, we show how to generate shorter circuits by plugging in the best available third party synthesis algorithm at a given hierarchy level. Composability enables portability across chip architectures, which is missing from the available approaches.

Younis, Ed↗
DOE OSTI2020

miniWeather

The code “miniWeather” solves the 2-D Euler equations with a Finite-Volume method on a regular Cartesian grid with Runge-Kutta time stepping, 4th-order hypervisocisty, and 4th-order spatial accuracy. The code is primarily a parallel programming training mini application in Fortran, C, and C++ with MPI, OpenMP, OpenMP offload, OpenACC, and C++ portability approaches. It can also serve as a mini application for acceptance testing for new machines and compilers for both functionality and performance.

Norman, MatthewR↗
DOE OSTI2020

PyFloT v0.1

PyFlot is a combination of python and C++ which aims at tuning floating point precision inside scientific applications. PyFloT uses link time interposition for portability and generality. The set of functions of interest are wrapped with code that enables either profiling or their lowering based on the classification criteria: SLOC (Source code LOCation) or backtrace. PyFloT implementation has only be validated using the GNU compiler toolchain.

Brunie, Hugo↗
DOE OSTI2020

GauXC v0.1.0

GauXC is a modern, modular C++ library for the numerical exchange-correlation (XC) integration required for the Gaussian basis set discretization of Kohn-Sham density functional theory (DFT). The modular nature of GauXC allows for an extensible software design which enables performance portability on an array of CPU and GPU architectures.

Williams-Young, David↗
DOE OSTI2021

OSHMPI: Open SHMEM Implementation over MPI

Open SHMEM is an increasingly popular standard of the SHMEM programing model. OSHMPI provides a light weight Open SHMEM implementation on top of the portable MPI Interface

SI, MIN↗
DOE OSTI2020

MIQS v0.6

In this research, we propose a novel Metadata Indexing and Querying for Self-describing formats (MIQS), which removes the external DBMS and utilizes in-memory index to achieve efficient metadata searching. MIQS follows the self-contained data management paradigm and provides portable and schema-free metadata indexing and querying functionalities for self-describing file formats. We have evaluated MIQS with the state-of-the-art MongoDB-based metadata indexing solution. MIQS achieved up to 99% time reduction in index construction and up to 172,000X search performance improvement with up to 75% reduction in memory footprint.

Byna, Suren↗
DOE OSTI2020

MIQS v0.6

In this research, we propose a novel Metadata Indexing and Querying for Self-describing formats (MIQS), which removes the external DBMS and utilizes in-memory index to achieve efficient metadata searching. MIQS follows the self-contained data management paradigm and provides portable and schema-free metadata indexing and querying functionalities for self-describing file formats. We have evaluated MIQS with the state-of-the-art MongoDB-based metadata indexing solution. MIQS achieved up to 99% time reduction in index construction and up to 172,000X search performance improvement with up to 75% reduction in memory footprint.

Byna, Suren↗
DOE OSTI2020

TaskWorks v1.0

TaskWorks is a portable, high-level, task engine designed for HPC workloads. Applications can create tasks and define dependencies between them with the task engine. Once the task is defined and submitted to TaskWorks, the TaskWorks engine will execute it according to the specified dependencies, without additional input from the application. TaskWorks has an integrated event manager monitors files, sockets, timers, and MPI operations, and these events can be used as task dependencies. TaskWorks is compatible with MPI and is designed to work efficiently with HPC applications that perform.

Koziol, Quincey↗
DOE OSTI2019

HALA: Handy Accelerated Linear Algebra

Accelerated linear algebra libraries often come with C-style of interfaces or even older Fortran77 standards, which makes it difficult to use within generic template programming environment of modern C++. For example, the BLAS and derived standards such as cuBLAS do not accept overloads and a different functions have to be called for each input type, thus it is very challenging to write a single template that handles multiple precision modes and works well with different C++ containers. HALA offers a series of templates that wrap around the BLAS/cuBLAS and other similar methods, automatically infer the relevant types and call the appropriate back-end. The templates work out-of-the-box with all C++ standard vector-like containers and can be easily extended (with template specializations) to handle user-provided containers. The HALA API is also overloaded to handle both GPU and CPU cases with a single "engine" class, thus a single high-level algorithms can utilize both CPU or GPU backends, i.e., the HALA API is unified and handles the variations between cuBLAS and BLAS. In addition to BLAS and cuBLAS, wrapper templates are provided for subset of LAPACK, cuSparse, and Cholmod methods. Work is in progress to complete as many of these standards as possible. HALA also includes a module for low-level extended register vectorization for complex number arithmetic and several simple solvers that build on the basic linear algebra capabilities. A single unified C++ API will benefit fast prototyping and easily writing code that is portable across GPU/CPU platforms as well as precision types and user containers. Note that HALA does not provide any accelerated algorithms, it simply serves as a "handy" front-end to other standards.

Stoyanov, MiroslavK.↗