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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The bark of the branches of holm oak (Quercus ilex L.) for a retrospective study of trace elements in the atmosphere

Tree bark has proved to be a useful bioindicator for trace elements in the atmosphere, however it reflects an exposure occurring during an unidentified period of time, so it provides spatial information about the distribution of contaminants in a certain area, but it cannot be used to detect temporal changes or trends, which is an important achievement in environmental studies. In order to obtain information about a known period of time, the bark collected from the annual segments of tree branches can be used, allowing analyses going back 10–15 years with annual resolution. In the present study, the concentrations of As, Cd, Co, Cu, Fe, Mn, Ni, Pb, V and Zn were measured by atomic emission spectrometry in a series of samples covering the period from 2001 to 2013 in an urban environment. Downward time trends were significant for Cd, Pb and Zn. The only trace element showing an upward time trend was V. The concentrations of the remaining six trace elements were constant over time, showing that their presence in bark is not simply proportional to the duration of exposure. This approach, which is simple, reliable and widely applicable at a low cost, allows the “a posteriori” reconstruction of atmospheric trace element deposition when or where no monitoring programme is in progress and no other natural archives are available. - Highlights: • Branch bark allows the historical reconstruction of atmospheric trace elements. • This approach is simple, reliable, widely applicable and “a posteriori”. • Downward time trends were found for Cd, Pb and Zn; upward trend for V.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Biomarkers of exposure in environment-wide association studies – Opportunities to decode the exposome using human biomonitoring data

The European Union's 7th Framework Programme (EU's FP7) project HEALS – Health and Environment-wide Associations based on Large Population Surveys – aims a refinement of the methodology to elucidate the human exposome. Human biomonitoring (HBM) provides a valuable tool for understanding the magnitude of human exposure from all pathways and sources. However, availability of specific biomarkers of exposure (BoE) is limited.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Efficient data IO for a Parallel Global Cloud Resolving Model

Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk without creating a serious bottleneck in the execution of the GCRM code while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables modelers to easily add variables to the output stream by specifying where in the GCRM code these variables are located and to flexibly configure the choice of outputs and distribution of data across files. The flexibility of the API is designed to allow model developers to add new data fields to the output as the model develops and new physics is added and also provides a mechanism for allowing users of the GCRM code itself to adjust the output frequency and the number of fields written depending on the needs of individual calculations. Third, we describe the mapping to the NetCDF data model with an emphasis on the grid description. Fourth, we describe our messaging algorithms and IO aggregation strategies that are used to achieve high bandwidth while simultaneously writing concurrently from many processors to shared files. We conclude with initial performance results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

JTAG-based PLC memory acquisition framework for industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLC) are the embedded devices that directly control and monitor critical industrial infrastructure processes such as nuclear plants and power grid stations. Cyberattacks often target PLCs to sabotage a physical process. A memory forensic analysis of a suspect PLC can answer questions about an attack, including compromised firmware and manipulation of PLC control logic code and I/O devices. Given physical access to a PLC, collecting forensic information from the PLC memory at the hardware-level is risky and challenging. It may cause the PLC to crash or hang since PLCs have proprietary, legacy hardware with heterogeneous architecture. This paper addresses this research problem and proposes a novel JTAG (Joint Test Action Group)-based framework, Kyros, for reliable PLC memory acquisition. Kyros systematically creates a JTAG profile of a PLC through hardware assessment, JTAG pins identification, memory map creation, and optimizing acquisition parameters. It also facilitates the community of interest (such as ICS owners, operators, and vendors) to develop the JTAG profiles of PLCs. Further, we present a case study of Kyros implementation over Allen-Bradley 1756-A10/B to help understand the framework's application on a real-world PLC used in industry settings. The sample PLC memory dumps are shared with the research community to facilitate further research.

Rais, Muhammad Haris↗
DOE OSTI2022

HIDRA-MAT liquid metal droplet injector for liquid metal applications in HIDRA

A liquid metal droplet injector was explicitly designed for the Hybrid Illinois Device for Research and Applications Material Analysis Test-stand (HIDRA-MAT) at the University of Illinois Urbana-Champaign to prepare liquid metal plasma-facing components (PFCs) for plasma exposure. The design goals were to create a compact, reliable, and robust design that could apply liquid metal droplets in-vacuo to a variety of samples. The injector was designed for liquid metal use, and results discussed pertain to lithium. The injector can produce lithium droplets of consistent size by utilizing programmable piston movement. Here, droplet formation data is presented for four different piston step sizes (0.125 mm, 0.25 mm, 0.5 mm, and 1 mm) at three different nozzle temperatures (185 °C, 230 °C, and 270 °C). Droplets are formed on the injector nozzle tip and a linear shift mechanism vertically translates the droplet to the substrate for application. This design prevents the droplet from inadvertently detaching off the nozzle and falling to the sample. Application of the liquid metal droplet ensures placement consistency on the substrate and helps avoid damage to components in HIDRA-MAT that should not interact with liquid metals. A description of the liquid lithium droplet creation and application results is given and provides additional insight into the cooling and oxidation of lithium droplets under vacuum conditions. A second nozzle was fabricated and demonstrated repeatability in droplet diameter creation having a variance of ±0.14 mm for droplets created from the same number of piston steps. The end-use for the injector on HIDRA-MAT is to apply liquid metals to PFCs and expose them to HIDRA's plasma with subsequent intershot in-vacuo surface analysis in HIDRA-MAT for plasma-material interaction studies.

42 ENGINEERING↗
DOE OSTI2025

A comparative analysis of numerical approaches for the description of gas flow in clay-based repository systems: From a laboratory to a large-scale gas injection test

There is nowadays a consensus among many countries that geological disposal is a favourable solution for the long-term management. Although different host formations and different barrier systems are under consideration around the world, clay-based materials form an important component for waste isolation in most national programmes. Hence, a good comprehension of the effect of gas flow on the hydro-mechanical behaviour of clay-based soils is essential, both at laboratory and field scale. Task B under the international cooperative project DECOVALEX-2023 has recently shown that, after some enhancement, models can be employed to reproduce laboratory scale tests, even with different sample geometries 37 . However, further work is required to understand whether they can be applied to simulate a large-scale experiment. Up-scaling of models for the advective transport of gas through clay-based low permeable material presents a number of problems related to the difficulty in obtaining consistent hydrogeological parameters and constitutive relationships at both laboratory and field scale. Based on a unique dataset from a large-scale gas injection test (Lasgit) performed at the Äspö Hard Rock Laboratory (Sweden), Task B within DECOVALEX-2023 has explored the refinement of these numerical strategies applied to the simulation of gas flow. Work performed within the task reveals that codes do not need to be substantially modified from the laboratory models to reproduce full-scale tests: indeed, model parameters calibrated and validated at laboratory scale have been applied to predict field scale gas flow at Lasgit, including peak gas pressure and injected cumulative gas volume. By means of (1) the introduction of interfaces between blocks to reflect the experimental configuration and the (2) adjustment of some parameters (e.g., higher permeability), the updated models are able to represent most of the key features observed in the experimental data, even at a large scale.

Tamayo-Mas, E↗
DOE OSTI2022

3D Simulations of gas injection on callovo-oxfordian claystone assuming spatial heterogeneity and anisotropy

A series of gas injection tests on Callovo-Oxfordian (COx) claystone from the Bure underground research laboratory (URL) in France were carried out at the British Geological Survey (BGS). The tests were performed using a triaxial apparatus specifically designed to capture small volumetric strains induced by the injected gas flow and consequent material dilatancy. The long-duration experiments were monitored throughout. Measurements also included pressure, stresses (axial and radial stresses prescribed for each test stage), rate of gas inflow, gas outflow volume as well as pore-pressures observed at various points of the sample. A coupled hydro-gas-mechanical 3D numerical model has been developed to simulate the tests. Initial permeability is assumed heterogeneous throughout the specimen and embedded fractures are incorporated in the formulation. Gas pressure-induced deformations during the test lead to variations of permeability due to changes in matrix porosity and, especially, fracture aperture as well as fracture orientation due to material anisotropy. A programme of sensitivity analyses involving the variation of different aspects and parameters of the model contributes to a better understanding of the phenomena and highlights its complexity. The model is able to reproduce the observed behaviour of the tests.

58 GEOSCIENCES↗
DOE OSTI2012

Phase II Study of Short-Course Radiotherapy Plus Concomitant and Adjuvant Temozolomide in Elderly Patients With Glioblastoma

Purpose: Radiotherapy (RT) and chemotherapy may prolong survival in older patients (age {>=}70 years) with glioblastoma multiforme (GBM), although the survival benefits remain poor. This Phase II multicenter study was designed to evaluate the efficacy and safety of an abbreviated course of RT plus concomitant and adjuvant temozolomide (TMZ) in older patients with GBM. Patients and Methods: Seventy-one eligible patients 70 years of age or older with newly diagnosed GBM and a Karnofsky performance status {>=}60 were treated with a short course of RT (40 Gy in 15 fractions over 3 weeks) plus TMZ at the dosage of 75 mg/m{sup 2} per day followed by 12 cycles of adjuvant TMZ (150-200 mg/m{sup 2} for 5 days during each 28-day cycle). The primary endpoint was overall survival (OS). Secondary endpoints included progression-free survival and toxicity. Results: The Median OS was 12.4 months, and the 1-year and 2-year OS rates were 58% and 20%, respectively. The median and 1-year rates of progression-free survival were 6 months and 20%, respectively. All patients completed the planned programme of RT. Grade 3 or 4 adverse events occurred in 16 patients (22%). Grade 3 and 4 neutropenia and/or thrombocytopenia occurred in 10 patients (15%), leading to the interruption of treatment in 6 patients (8%). Nonhematologic Grade 3 toxicity was rare, and included fatigue in 4 patients and cognitive disability in 1 patient. Conclusions: A combination of an abbreviated course of RT plus concomitant and adjuvant TMZ is well tolerated and may prolong survival in elderly patients with GBM. Future randomized studies need to evaluate the efficacy and toxicity of different schedules of RT in association with chemotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Validation of a 4D-PET Maximum Intensity Projection for Delineation of an Internal Target Volume

Purpose: The delineation of internal target volumes (ITVs) in radiation therapy of lung tumors is currently performed by use of either free-breathing (FB) {sup 18}F-fluorodeoxyglucose-positron emission tomography-computed tomography (FDG-PET/CT) or 4-dimensional (4D)-CT maximum intensity projection (MIP). In this report we validate the use of 4D-PET-MIP for the delineation of target volumes in both a phantom and in patients. Methods and Materials: A phantom with 3 hollow spheres was prepared surrounded by air then water. The spheres and water background were filled with a mixture of {sup 18}F and radiographic contrast medium. A 4D-PET/CT scan was performed of the phantom while moving in 4 different breathing patterns using a programmable motion device. Nine patients with an FDG-avid lung tumor who underwent FB and 4D-PET/CT and >5 mm of tumor motion were included for analysis. The 3 spheres and patient lesions were contoured by 2 contouring methods (40% of maximum and PET edge) on the FB-PET, FB-CT, 4D-PET, 4D-PET-MIP, and 4D-CT-MIP. The concordance between the different contoured volumes was calculated using a Dice coefficient (DC). The difference in lung tumor volumes between FB-PET and 4D-PET volumes was also measured. Results: The average DC in the phantom using 40% and PET edge, respectively, was lowest for FB-PET/CT (DCAir = 0.72/0.67, DCBackground 0.63/0.62) and highest for 4D-PET/CT-MIP (DCAir = 0.84/0.83, DCBackground = 0.78/0.73). The average DC in the 9 patients using 40% and PET edge, respectively, was also lowest for FB-PET/CT (DC = 0.45/0.44) and highest for 4D-PET/CT-MIP (DC = 0.72/0.73). In the 9 lesions, the target volumes of the FB-PET using 40% and PET edge, respectively, were on average 40% and 45% smaller than the 4D-PET-MIP. Conclusion: A 4D-PET-MIP produces volumes with the highest concordance with 4D-CT-MIP across multiple breathing patterns and lesion sizes in both a phantom and among patients. Freebreathing PET/CT consistently underestimates ITV when compared with 4D PET/CT for a lesion affected by respiration.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Dosimetric Impact of the Interplay Effect During Stereotactic Lung Radiation Therapy Delivery Using Flattening Filter-Free Beams and Volumetric Modulated Arc Therapy

Purpose: We investigated the dosimetric impact of the interplay effect during RapidArc stereotactic body radiation therapy for lung tumors using flattening filter-free (FFF) beams with different dose rates. Methods and Materials: Seven tumors with motion ≤20 mm, treated with 10-MV FFF RapidArc, were analyzed. A programmable phantom with sinusoidal longitudinal motion (30-mm diameter “tumor” insert; period = 5 s; individualized amplitude from planning 4-dimensional computed tomography) was used for dynamic dose measurements. Measurements were made with GafChromic EBT III films. Plans delivered the prescribed dose to 95% of the planning target volume, created by a 5-mm expansion of the internal target volume. They comprised 2 arcs and maximum dose rates of 400 and 2400 MU/min. For 2400 MU/min plans, measurements were repeated at 3 different initial breathing phases to model interplay over 2 to 3 fractions. For 3 cases, 2 extra plans were created using 1 full rotational arc (with contralateral lung avoidance sector) and 1 partial arc of 224° to 244°. Dynamic and convolved static measurements were compared by use of gamma analysis of 3% dose difference and 1 mm distance-to-agreement. Results: For 2-arc 2400 MU/min plans, maximum dose deviation of 9.4% was found in a single arc; 7.4% for 2 arcs (single fraction) and <5% and 3% when measurements made at 2 and 3 different initial breathing phases were combined, simulating 2 or 3 fractions. For all 7 cases, >99% of the area within the region of interest passed the gamma criteria when all 3 measurements with different initial phases were combined. Single-fraction single-arc plans showed higher dose deviations, which diminished when dose distributions were summed over 2 fractions. All 400 MU/min plans showed good agreement in a single fraction measurement. Conclusion: Under phantom conditions, single-arc and single-fraction 2400 MU/min FFF RapidArc lung stereotactic body radiation therapy is susceptible to interplay. Two arcs and ≥2 fractions reduced the effect to a level that appeared unlikely to be clinically significant.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Kinetic analysis of Cas12a and Cas13a RNA-Guided nucleases for development of improved CRISPR-Based diagnostics

Bacterial CRISPR systems provide acquired immunity against invading nucleic acids by activating RNA-programmable RNases and DNases. Cas13a and Cas12a enzymes bound to CRISPR RNA (crRNA) recognize specific nucleic acid targets, initiating cleavage of the targets as well as non-target (trans) nucleic acids. Here, we examine the kinetics of single-turnover target and multi-turnover trans-nuclease activities of both enzymes. High-turnover, non-specific Cas13a trans-RNase activity is coupled to rapid binding of target RNA. By contrast, low-turnover Cas12a trans-nuclease activity is coupled to relatively slow cleavage of target DNA, selective for DNA over RNA, indifferent to base identity, and preferential for single-stranded substrates. Combining multiple crRNA increases detection sensitivity of targets, an approach we use to quantify pathogen DNA in samples from patients suspected of Buruli ulcer disease. Results reveal that these enzymes are kinetically adapted to play distinct roles in bacterial adaptive immunity and show how kinetic analysis can be applied to CRISPR-based diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Volatile particles measured by vapor-particle separator

Vapor-Particle Separator (VPS) is a new technology developed for characterization of the volatile fraction of particulate matter in a combustion aerosol population. VPS incorporates a novel metallic membrane and operates in a cross-flow filtration mode for separation of vapor and solid (i.e. non-volatile) particles. Demonstration of the VPS technology on aircraft engine-emitted particles has led to the improvement of the technology and increased confidence on the robustness of its field performance. In this study, the performance of the VPS was evaluated against the Particle Measurement Programme (PMP) volatile particle remover (VPR), a standardized device used in heavy duty diesel engines for separation and characterization of non-volatile particulate matter. Using tetracontane particles in the laboratory reveals that the VPS performed reasonably well in removing the volatile species. In the field conditions, a single-mode particle size distribution was found for emitted particles from a T63 turboshaft engine at both idle and cruise engine power conditions. Removal of the volatile T63 engine particles by the VPS was consistent with that of PMP VPR. In tests on an F117 turbofan engine, the size distribution at the idle (4% rated) engine power condition was found to be bimodal, with the first mode consisting of particles smaller than 10nm, which are believed to be mostly semi-volatile particles, while the second mode of larger size was a mixture of semi-volatile and non-volatile particles. The distribution was single modal at the 33% rated engine power with no secondary mode observed. Altogether, for particles emitted by both engines, the removal efficiency of the VPS appears to surpass that of the PMP VPR by 8-10%.

42 ENGINEERING↗
DOE OSTI2022

Designing sequence-defined peptoids for fibrillar self-assembly and silicification

In the biological environment, mineral crystals exquisitely controlled by biomacromolecules often show intricate hierarchical structures and superior mechanical properties. Among these biominerals, spicules, hybrid silica/protein superstructures serving as skeletal elements in demosponges, represent an excellent example for motivating the synthesis of silica materials. Herein, by designing sequence-defined peptoids containing side chains with a strong binding to silica, we demonstrated that self-assembly of these peptoids into fiber structures enables the mimicking of both biocatalytic and templating functions of silicatein filaments for the formation of silica fibers at near-neutral pH and ambient temperature. We further showed that the presence of amino groups is significant for the nucleation of silica on self-assembled peptoid nanofibers. Molecular dynamics simulation further confirmed that having silica-binding of amino side chains is critical for self-assembled peptoid fibers in triggering silica formation. Here, we demonstrated that tuning inter-peptoid interactions by varying carboxyl and amino side chains significantly influences the assembly kinetics and final morphologies of peptoid assemblies as scaffolds for directing silica mineralization to form silica spheres, fibers, and sheets. The formation of silica shell on peptoid fibers increased the mechanical property of peptoid hydrogel materials by nearly 1000-fold, highlighting the great potential of using silicification to enhance the mechanical property of hydrogel materials for applications including tissue engineering. Since peptoids are highly robust and programmable, we expect that self-assembly of peptoids containing solid-binding side chains into hierarchical materials opens new opportunities in the design and synthesis of highly tunable scaffolds that direct the formation of composite nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Accelerating solidification process simulation for large-sized system of liquid metal atoms using GPU with CUDA

Molecular dynamics simulation is a powerful tool to simulate and analyze complex physical processes and phenomena at atomic characteristic for predicting the natural time-evolution of a system of atoms. Precise simulation of physical processes has strong requirements both in the simulation size and computing timescale. Therefore, finding available computing resources is crucial to accelerate computation. However, a tremendous computational resource (GPGPU) are recently being utilized for general purpose computing due to its high performance of floating-point arithmetic operation, wide memory bandwidth and enhanced programmability. As for the most time-consuming component in MD simulation calculation during the case of studying liquid metal solidification processes, this paper presents a fine-grained spatial decomposition method to accelerate the computation of update of neighbor lists and interaction force calculation by take advantage of modern graphics processors units (GPU), enlarging the scale of the simulation system to a simulation system involving 10 000 000 atoms. In addition, a number of evaluations and tests, ranging from executions on different precision enabled-CUDA versions, over various types of GPU (NVIDIA 480GTX, 580GTX and M2050) to CPU clusters with different number of CPU cores are discussed. The experimental results demonstrate that GPU-based calculations are typically 9∼11 times faster than the corresponding sequential execution and approximately 1.5∼2 times faster than 16 CPU cores clusters implementations. On the basis of the simulated results, the comparisons between the theoretical results and the experimental ones are executed, and the good agreement between the two and more complete and larger cluster structures in the actual macroscopic materials are observed. Moreover, different nucleation and evolution mechanism of nano-clusters and nano-crystals formed in the processes of metal solidification is observed with large-sized system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Learning functional priors and posteriors from data and physics

In this work, we develop a new Bayesian framework based on deep neural networks to be able to extrapolate in space-time using historical data and to quantify uncertainties arising from both noisy and gappy data in physical problems. Specifically, the proposed approach has two stages: (1) prior learning and (2) posterior estimation. At the first stage, we employ the physics-informed Generative Adversarial Networks (PI-GAN) to learn a functional prior either from a prescribed function distribution, e.g., Gaussian process, or from historical data and physics. At the second stage, we employ the Hamiltonian Monte Carlo (HMC) method to estimate the posterior in the latent space of PI-GANs. In addition, we use two different approaches to encode the physics: (1) automatic differentiation, used in the physicsinformed neural networks (PINNs) for scenarios with explicitly known partial differential equations (PDEs), and (2) operator regression using the deep operator network (DeepONet) for PDE-agnostic scenarios. We then test the proposed method for (1) meta-learning for one-dimensional regression, and forward/inverse PDE problems (combined with PINNs); (2) PDE-agnostic physical problems (combined with DeepONet), e.g., fractional diffusion as well as saturated stochastic (100-dimensional) flows in heterogeneous porous media; and (3) spatial-temporal regression problems, i.e., inference of a marine riser displacement field using experimental data from the Norwegian Deepwater Programme (NDP). The results demonstrate that the proposed approach can provide accurate predictions as well as uncertainty quantification given very limited scattered and noisy data, since historical data could be available to provide informative priors. In summary, the proposed method is capable of learning flexible functional priors, e.g., both Gaussian and non-Gaussian process, and can be readily extended to big data problems by enabling mini-batch training using stochastic HMC or normalizing flows since the latent space is generally characterized as low dimensional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Fine-grained Asynchronous Bulk Synchronous parallelism model for PGAS applications

The Partitioned Global Address Space (PGAS) model is well suited for executing irregular applications on cluster-based systems, due to its efficient support for short, one-sided messages. Separately, the actor model has been gaining popularity as a productive asynchronous message-passing approach for distributed objects in enterprise and cloud computing platforms, typically implemented in languages such as Erlang, Scala or Rust. To the best of our knowledge, there has been no past work on using the actor model to deliver both productivity and scalability to irregular PGAS applications with large number of small messages. In this paper, we introduce a new programming system for PGAS applications, in which point-to-point remote operations can be expressed as fine-grained asynchronous actor messages. In our approach, the programmer does not need to worry about programming complexities related to message aggregation and termination detection. Our approach can be viewed as extending the classical Bulk Synchronous Parallelism model with fine-grained asynchronous communications within a phase or superstep. Here, we believe that our approach offers a desirable point in the productivity-performance space for PGAS applications, with more scalable performance and higher productivity relative to past approaches. Specifically, for seven irregular mini-applications from the Bale Kernels and three graph kernels executed using 2048 cores in the NERSC Cori system, our approach shows geometric mean performance improvements of ≥ 20X relative to standard PGAS versions (UPC and OpenSHMEM) while maintaining comparable productivity to those versions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Kokkos: Enabling manycore performance portability through polymorphic memory access patterns

The manycore revolution can be characterized by increasing thread counts, decreasing memory per thread, and diversity of continually evolving manycore architectures. High performance computing (HPC) applications and libraries must exploit increasingly finer levels of parallelism within their codes to sustain scalability on these devices. We found that a major obstacle to performance portability is the diverse and conflicting set of constraints on memory access patterns across devices. Contemporary portable programming models address manycore parallelism (e.g., OpenMP, OpenACC, OpenCL) but fail to address memory access patterns. The Kokkos C++ library enables applications and domain libraries to achieve performance portability on diverse manycore architectures by unifying abstractions for both fine-grain data parallelism and memory access patterns. In this paper we describe Kokkos’ abstractions, summarize its application programmer interface (API), present performance results for unit-test kernels and mini-applications, and outline an incremental strategy for migrating legacy C++ codes to Kokkos. Furthermore, the Kokkos library is under active research and development to incorporate capabilities from new generations of manycore architectures, and to address a growing list of applications and domain libraries.

97 MATHEMATICS AND COMPUTING↗