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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

We present a solution of sparse ACOPF analysis on GPU. In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF solutions of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) \cite{birchfield2017tamu-cases} on GPU show promising speed-up compared to CPU based solution using a state-of-the-art solver. To our knowledge, this is the first result demonstrating acceleration of sparse ACOPF on GPUs.

Power grid analysis, GPU↗
DOE OSTI2022

Laser–solid interaction studies enabled by the new capabilities of the iP2 BELLA PW beamline

The new capabilities of the short focal length, high intensity beamline, named iP2, at the BELLA Center will extend the reach of research in high energy density science, including accessing new regimes of high gradient ion acceleration and their applications. This 1 Hz system will provide an on-target peak intensity beyond 1021 W/cm2 with a temporal contrast ratio of <10−14 that will be enabled by the addition of an on-demand double plasma mirror setup. An overview of the beamline design and the main available diagnostics are presented in this paper as well as a selection of accessible research areas. As a demonstration of the iP2 beamline's capabilities, we present 3D particle-in-cell simulations of ion acceleration in the magnetic vortex acceleration regime. The simulations were performed with pure hydrogen targets and multi-species targets. Proton beams with energy up to 125 MeV and an approximately 12° full angle emission are observed as preplasma scale length and target tilt are varied. The number of accelerated protons is on the order of 109/MeV/sr for energies above 60 MeV.

Hakimi, Sahel (ORCID:000000022493564X)↗
DOE OSTI2023

Characterizing Density and Spatial Distribution of Trap States in Ta 3 N 5 Thin Films for Rational Defect Passivation

Tantalum nitride (Ta 3 N 5 ) has gained significant attention as a potential photoanode material, yet it has been challenged by material quality issues. Defect-induced trap states are detrimental to the performance of any semiconductor material. Beyond influencing the performance of Ta 3 N 5 films, defects can also accelerate the degradation in water during desired electrochemical applications. Defect passivation has provided an enormous boost to the development of many semiconductor materials but is currently in its infancy for Ta 3 N 5 . This is in part due to a lack of experimental understanding regarding the spatial and energetic distribution of trap states throughout Ta 3 N 5 thin films. Here, we employ drive-level capacitance profiling (DLCP) to experimentally resolve the spatial and energetic distribution of trap states throughout Ta 3 N 5 thin films. The density of deeper energetic traps is found to reach ∼2.5 to 6 × 10 22 cm –3 at the interfaces of neat Ta 3 N 5 thin films, over an order of magnitude greater than the bulk. In addition to the spatial profile of deep trap states, we report neat Ta 3 N 5 thin films to be highly n-type in nature, owning a free carrier density of ∼9.74 × 10 17 cm –3 . This information, coupled with the present understanding of native oxide layers on Ta 3 N 5 , has facilitated the rational design of a targeted passivation strategy that simultaneously provides a means for catalyst immobilization. Loading catalyst via silatrane moieties suppresses the density of defects at the surface of Ta 3 N 5 thin films by two orders of magnitude, while also reducing the free carrier density of films by over one order of magnitude, effectively dedoping the films to ∼2.40 × 10 16 cm –3 . The surface passivation of Ta 3 N 5 films translates to suppressed defect-induced trapping and recombination of photoexcited carriers, as determined through absorption, photoluminescence, and transient photovoltage. Here, this illustrates how developing a deeper understanding of the distribution and influence of defects in Ta 3 N 5 thin films has the potential to guide future works and ultimately accelerate the integration and development of high-performance Ta 3 N 5 thin film devices.

defect passivation↗
DOE OSTI2022

A Path Toward Understanding the Performance Capabilities of SmartNIC Devices [Slides]

SmartNICs, accelerator devices integrated with a network, have conventionally been utilized to offload low-level networking functionality. However, newer SmartNIC variants, which incorporate a system-on-chip (SoC) with traditional designs, are challenging this precedent. Leveraging significantly augmented resources, these new devices offer increased versatility and the potential to more effectively complement a given architecture’s CPU. Naturally, there is performance overhead associated with offloading tasks from a host CPU to a SmartNIC. As SmartNICs become more versatile and are used for a wider range of computational tasks, it is critical to understand how well the SmartNICs perform those respective tasks in order to determine whether the cost of offloading is worthwhile. In this work, we lay out a path to understand the important question of when and when not to offload to SmartNIC devices by way of a series of microbenchmarks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) architecture, GPU-accelerated error-bounded compressors (such as CUSZ and cuZFP) have been developed. However, they suffer from either low performance or low compression ratios. To this end, we propose CUSZ+ to target both high compression ratios and throughputs. We identify that data sparsity and data smoothness are key factors for high compression throughputs. Our key contributions in this work are fourfold: (1) We propose an efficient compression workflow to adaptively perform run-length encoding and/or variable-length encoding. (2) We derive Lorenzo reconstruction in decompression as multidimensional partial-sum computation and propose a fine-grained Lorenzo reconstruction algorithm for GPU architectures. (3) We carefully optimize each of CUSZ kernels by leveraging state-of-the-art CUDA parallel primitives. (4) We evaluate CUSZ+ using seven real-world HPC application datasets on V100 and A100 GPUs. Experiments show CUSZ+ improves the compression throughputs and ratios by up to 18.4x and 5.3x, respectively, over CUSZ on the tested datasets.

Tian, Jiannan↗
DOE OSTI2022

CEBAF Accelerator Tunnel Robot Project

Advancements in the field of robotics allow for the use of remotely controlled robots to perform tasks that have typically required human intervention. Jefferson Lab has explored the possibilities of robots placed in the accelerator tunnel to perform remote inspections that would otherwise require powering down equipment and completing lengthy radiological surveys that impact beam operations. A robotic solution ? driven by a human operator ? could not only reduce accelerator down time but also support the Lab's radiation exposure policy (known as "ALARA" - As Low As Reasonably Acceptable) by handling routine tunnel and beamline investigations in place of a human being. However, operating a remote device in a radioactive, high electronic-noise area is not a trivial task and drop-in solutions are rarely as simple as they seem. We will present the past prototypes that were tested as well follow-on technology developed from the project. We will also briefly survey current applications of robots at accelerator facilities with an eye toward future applications.

McGuckin, Theodore↗
DOE OSTI2025

Experience with the alpaka performance portability library in the CMS software

ion Library for Parallel Kernel Acceleration) is a header-only C++ library that provides performance portability across different back-ends, abstracting the underlying levels of parallelism. It supports serial and parallel execution on CPUs, and extremely parallel execution on NVIDIA, AMD and Intel GPUs.This contribution will show how alpaka is used in the CMS software to develop and maintain a single code base; to use different toolchains to build the code for each supported back-end, and link them into a single application; to seamlessly select the best backend at runtime, and implement portable reconstruction algorithms that run efficiently on CPUs and GPUs from different vendors. It will describe the validation and deployment of the alpaka-based implementation in the CMS High Level Trigger, and highlight how it achieves near-native performance.

Alawieh, Jaafar [CERN]↗
DOE OSTI2020

OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration

Attached accelerators have been frequently used in recent High Per- formance Computing (HPC) systems because of their high performance/power ratio. In particular, the Graphics Processing Unit (GPU) is the most popu- lar accelerator owing to its high peak FLOPS performance and high memory bandwidth supported by HBM2, etc. However, the performance of GPU depends highly on a large degree of SIMD parallelism and has difficulty sustaining a high performance on programs with frequent branch operations or a partially low degree of parallelism.By contrast, a Field Programmable Gate Array (FPGA) has received attention as a different type of accelerator than GPU as a fully reconfigurable processor fitting the target applications. The high performance of FPGA is mainly provided by a pipelined operation and optimized circuit suitable for any operation even with frequent conditional branches. We have been focusing on the flexibility of FPGA to compensate for the weakness of GPU. We believe that the coupling of GPU with FPGA can result in one of the most powerful accelerating platforms available.However, the program coding of GPU and FPGA coupling can be quite difficult for application users. Traditionally, CUDA by NVIDIA has been the most popular programming language with the largest share of GPUs used in HPC, whereas a hardware description language such as Verilog HDL has been used in FPGA programming. OpenCL coding has recently become available even on high-end FPGAs. Moreover, several recent studies have also enabled the OpenACC coding for use in FPGA. In this study, we provide a unified programming system based on OpenACC for a platform equipped with both GPU and FPGA aiming at the next-generation accelerated supercomputer framework. Our programming environment is called Multi-Hybrid OpenACC Translator (MHOAT), and in this paper, we describe the basic concept and prototype system of MHOAT based on an evaluation on the amount of coding required and the performance of a hybrid multi-device accelerated system.

Tsunashima, Ryuta↗
DOE OSTI2023

Membrane Pretreatment and Cell Conditioning for Proton Exchange Membrane Water Electrolysis

As the research community studying proton exchange membrane water electrolysis (PEMWE) grows, it is important to develop methods that achieve transparent, reproducible research. Reproducibility of performance and durability is a challenge facing the PEMWE field, as the published literature includes a wide spread of results obtained with nominally similar materials. Prior round-robin performance benchmarking efforts [1] have identified inadequate cell conditioning as a major source of variation in apparent cell performance. Inadequate pre-treatment and conditioning can lead to instability in initial performance and adds ambiguity to durability measurements. However, excessively prolonged conditioning procedures limit the throughput of testing and the pace of research. Pretreatment and conditioning methods vary significantly across the research literature, but little systematic investigation is available into the mechanisms of these procedures or how procedural differences may impact results. This presentation will discuss investigations into the effects of membrane pre-treatment and operating procedures during cell conditioning on initial performance and catalyst-specific accelerated stress tests, with the aim of recommending procedures to enable clear, reproducible, and high-throughput research. Methods investigated include the use of hydrogen peroxide, acids, and hydration at elevated temperature for membrane pretreatment, and conditioning procedures such as current or voltage holds and cycling. The investigations cover both the impacts of these procedures on cell performance and stability as well as underlying mechanisms and processes taking place in the cell materials.

cell↗
DOE OSTI2020

CDFG Extraction Tool for LLVM

With the dawn of the exascale era, computer scientists and engineers are faced with tremendous challenges across all facets of the HPC system - scalability, performance, reliability, and power consumption. In particular, the power-performance benefit from one processor generation to the next is seeing ever-diminishing returns and will require fundamental changes in the way we approach computation. In fact, it is likely that different applications will require different types of accelerators in order to meet power, performance, and reliability requirements at scale. One potential type of accelerator, a dataflow architecture, diverges from the traditional sequentially executed instruction model into one that reflects the inherent instruction-level parallelism in a program. This work presents the initial steps toward a tool that can extract the control-dataflow graph from an application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Durability of Pt-Alloy Catalyst for Heavy-Duty Polymer Electrolyte Fuel Cell Applications under Realistic Conditions

As an emerging technology, polymer electrolyte fuel cells (PEFCs) powered by clean hydrogen can be a great source of renewable power generation with flexible utilization because of high gravimetric energy density of hydrogen. To be used in real-life applications, PEFCs need to maintain their performance for long-term use under a wide range of conditions. Therefore, it's important to understand the degradation of the PEFC under protocols that are closely related to the catalyst lifetime. Alloying Pt with transitional metal improves catalyst activity. It is also crucial to understand Pt alloys degradation mechanisms to improve their durability. To study durability of Pt alloys, accelerated stress tests (ASTs) are performed on Pt-Co catalyst supported on two types of carbon. Two different AST protocols were being studied: Membrane Electrolyte Assembly (MEA) AST based on the protocol introduced by the Million Mile Fuel Cell Truck consortium in 2023 and Catalyst AST, adopted from the U.S. Department of Energy (DoE).

25 ENERGY STORAGE↗
DOE OSTI2025

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

General relativistic MHD simulations of non-thermal flaring in Sagittarius A*

Sgr A* exhibits regular variability in its multiwavelength emission, including daily X-ray flares and roughly continuous near-infrared (NIR) flickering. The origin of this variability is still ambiguous since both inverse Compton and synchrotron emission are possible radiative mechanisms. The underlying particle distributions are also not well constrained, particularly the non-thermal contribution. In this work, we employ the GPU-accelerated general relativistic magnetohydrodynamics code H-AMR to perform a study of flare flux distributions, including the effect of particle acceleration for the first time in high-resolution 3D simulations of Sgr A*. For the particle acceleration, we use the general relativistic ray-tracing code bhoss to perform the radiative transfer, assuming a hybrid thermal+non-thermal electron energy distribution. We extract ~60 h light curves in the sub-millimetre, NIR and X-ray wavebands, and compare the power spectra and the cumulative flux distributions of the light curves to statistical descriptions for Sgr A* flares. Our results indicate that non-thermal populations of electrons arising from turbulence-driven reconnection in weakly magnetized accretion flows lead to moderate NIR and X-ray flares and reasonably describe the X-ray flux distribution while fulfilling multiwavelength flux constraints. These models exhibit high rms per cent amplitudes, $\gtrsim 150{{\ \rm per\ cent}}$ both in the NIR and the X-rays, with changes in the accretion rate driving the 230 GHz flux variability, in agreement with Sgr A* observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper describes and demonstrates the performance of the open-source C++ matrix and array (MATAR) library that uniquely offers: (1) a straightforward syntax for programming productivity, (2) usable data structures for data-oriented programming (DOP) for performance, and (3) a simple interface to the open-source C++ Kokkos library for portability and memory management across CPUs and GPUs. The portability across architectures with a single code implementation is achieved by automatically switching between diverse fine-grained parallelism backends (e.g., CUDA, HIP, OpenMP, pthreads, etc.) at compile time. The MATAR library solves many longstanding challenges associated with easily writing software that can run in parallel on any computer architecture. This work benefits projects seeking to write new C++ codes while also addressing the challenges of quickly making existing Fortran codes performant and portable over modern computer architectures with minimal syntactical changes from Fortran to C++. We demonstrate the feasibility of readily writing new C++ codes and modernizing existing codes with MATAR to be performant, parallel, and portable across diverse computer architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Machine learning for reducing noise in RF control signals at industrial accelerators

Industrial particle accelerators typically operate in dirtier environments than research accelerators, leading to increased noise in RF and electronic systems. Furthermore, given that industrial accelerators are mass produced, less attention is given to optimizing the performance of individual systems. As a result, industrial accelerators tend to underperform their own hardware capabilities. Improving signal processing for these machines will improve cost and time margins for deployment, helping to meet the growing demand for accelerators for medical sterilization, food irradiation, cancer treatment, and imaging. Our work focuses on using machine learning techniques to reduce noise in RF signals used for pulse-to-pulse feedback in industrial accelerators. Here we review our algorithms and observed results for simulated RF systems, and discuss next steps with the ultimate goal of deployment on industrial systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Bayesian optimization of laser wakefield acceleration via spectral pulse shaping

In this paper, we investigate the effect of spectral pulse shaping of the laser driver on the performance of channel-guided, laser–plasma accelerators. The study was carried out with the assistance of Bayesian optimization using particle-in-cell simulations. We used a realistic plasma profile based on a novel optical-field-ionized channel technique with ionization injection and low, on-axis plasma densities to maximize the energy gain of the electron bunch trailing the laser. Spectral shaping allows us to modify the temporal profile of the laser driver while keeping the laser energy constant, affecting the acceleration and injection processes. In addition, we consider how modifying the plasma channel parameters may affect the target outputs. Given the complexity and breadth of the parameter space in question, we used numerical optimization to identify high-performing configurations. In particular, we found laser profiles with additional spectral content that, when used with optimal plasma channel parameters, result in charge content an order of magnitude higher than the baseline Gaussian case while also increasing the mean energy of the electron bunch.

Physics - Plasma physics↗
DOE OSTI2024

A Performance and Energy Study of GPU-Resident Preconditioners for Conjugate Gradient Solvers: In the Context of Existing and Novel Approaches

Optimizing a particular subprogram out of the set of Basic (sparse) Linear Algebra Subprograms (BLAS) for a given architecture is a common topic of research. In applications, however, these BLAS functions rarely appear in isolation; usually, many of them are used together, in various combinations and with varying inputs. As the need to solve a large, sparse linear system is ubiquitous throughout HPC applications, linear solvers constitute a realistic, sufficiently complex and well-defined representative use case for composite BLAS routines. To this end, based on a representative set of matrices drawn from a diverse set of fields, we present a framework to study, from the performance and energy perspective, the efficacy of GPU- resident parallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and incomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated by an iterative process. The development of this preconditioner was motivated by solving large graph Laplacian linear systems, for which the existing preconditioners either perform slow on GPU-based platforms or are not applicable. We compare the performance of these preconditioners on different hardware accelerator architectures, i.e., AMD MI250X, MI100, Nvidia A100, V100, and Jetson. Our experiments reveal performance trade-offs and provide information on how to select the best strategy for the given linear system, dictated by its properties, and the platform of interest. We demonstrate the application of our novel preconditioner for solving CG and graph Laplacian systems. Overall, the framework can be utilized as a benchmark to guide informed decisions in choosing a specific preconditioner, i.e., whether it is better to rely on the performance of a triangular solver or on the performance of sparse matrix-vector product. Finally, by considering power consumption to solve the linear systems, we report the energy footprint for the solvers.

Preconditioned Conjugate Gradient, GPUs, iterative↗