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At least 1,027 records · Page 57

Characterization of In-Use Medium Duty Electric Vehicle Driving and Charging Behavior: Preprint

The U.S. Department of Energy's American Recovery and Reinvestment Act (ARRA) deployment and demonstration projects are helping to commercialize technologies for all-electric vehicles (EVs). Under the ARRA program, data from Smith Electric and Navistar medium duty EVs have been collected, compiled, and analyzed in an effort to quantify the impacts of these new technologies. Over a period of three years, the National Renewable Energy Laboratory (NREL) has compiled data from over 250 Smith Newton EVs for a total of over 100,000 days of in-use operation. Similarly, data have been collected from over 100 Navistar eStar vehicles, with over 15,000 operating days having been analyzed. NREL has analyzed a combined total of over 4 million kilometers of driving and 1 million hours of charging data for commercial operating medium duty EVs. In this paper, the authors present an overview of medium duty EV operating and charging behavior based on in-use data collected from both Smith and Navistar vehicles operating in the United States. Specifically, this paper provides an introduction to the specifications and configurations of the vehicles examined; discusses the approach and methodology of data collection and analysis, and presents detailed results regarding daily driving and charging behavior. In addition, trends observed over the course of multiple years of data collection are examined, and conclusions are drawn about early deployment behavior and ongoing adjustments due to new and improving technology. Results and metrics such as average daily driving distance, route aggressiveness, charging frequency, and liter per kilometer diesel equivalent fuel consumption are documented and discussed.

25 ENERGY STORAGE↗

Towards Resiliency Evaluation of Vector Programs

The systems resilience research community has developed methods to manually insert additional source-program level assertions to trap errors, and also devised tools to conduct fault injection studies for scalar program codes. In this work, we contribute the first vector oriented LLVM-level fault injector VULFI to help study the effects of faults in vector architectures that are of growing importance, especially for vectorizing loops. Using VULFI, we conduct a resiliency study of nine real-world vector benchmarks using Intel’s AVX and SSE extensions as the target vector instruction sets, and offer the first reported understanding of how faults affect vector instruction sets. We take this work further toward automating the insertion of resilience assertions during compilation. This is based on our observation that during intermediate (e.g., LLVM-level) code generation to handle full and partial vectorization, modern compilers exploit (and explicate in their code-documentation) critical invariants. These invariants are turned into error-checking code. We confirm the efficacy of these automatically inserted low-overhead error detectors for vectorized for-loops.

fault injection↗

Integer Sum Reduction with OpenMP on an AMD MI100 GPU

Sum reduction is a primitive operation in parallel computing. Device offload support allows a user to use OpenMP directives to take advantage of a highly capable GPU. In this paper, we present the integer sum reduction annotated with the OpenMP directives and evaluate the performance impacts of tunable parameters with the AOMP and GCC compilers on an AMD MI100 GPU. In addition, we explain the implementations of the OpenMP reduction by the compilers. Sweeping over the pruned parameter space, we find that the speedup is approximately 20 with AOMP, and the reduction performance using AOMP is approximately 11% higher than that using GCC. However, the OpenMP offload performance is approximately 30% lower compared to the performance of the reductions written with rocThrust or hipCUB.

Jin, Zheming↗

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]↗

Really Embedding Domain-Specific Languages into C++

The following topics are dealt with: program compilers; optimising compilers; parallel processing; software engineering; learning (artificial intelligence); multiprocessing systems; shared memory systems; optimisation; computational complexity; specification languages.

Finkel, Hal J.↗

Future Directions in Computer Graphics and Visualization: From CG&A's Editorial Board

With many new members joining the CG&A editorial board over the past year, and with a renewed commitment to not only document the state of the art in computer graphics research and applications but to anticipate and where possible foster future areas of scientific discourse and industrial practice, we asked editorial and advisory council members about where they see their fields of expertise going. The answers compiled here aren’t meant to be all encompassing or deterministic when it comes to the opportunities computer graphics and interactive visualization hold for the future. Instead, we aim to accomplish two things: give a more in-depth introduction of members of the editorial board to the CG&A readership and encourage cross-disciplinary discourse toward approaching, complementing, or disputing the visions laid out in this compilation.

Applications, State of Field↗

Understanding Portability of a High-Level Programming Model on Contemporary Heterogeneous Architectures

Accelerator-based heterogeneous computing is gaining momentum in the high-performance computing arena. However, the increased complexity of heterogeneous architectures demands more generic, high-level programming models. OpenACC is one such attempt to tackle this problem. Although the abstraction provided by OpenACC offers productivity, it raises questions concerning both functional and performance portability. In this article, the authors propose HeteroIR, a high-level, architecture-independent intermediate representation, to map high-level programming models, such as OpenACC, to heterogeneous architectures. They present a compiler approach that translates OpenACC programs into HeteroIR and accelerator kernels to obtain OpenACC functional portability. They then evaluate the performance portability obtained by OpenACC with their approach on 12 OpenACC programs on Nvidia CUDA, AMD GCN, and Intel Xeon Phi architectures. They study the effects of various compiler optimizations and OpenACC program settings on these architectures to provide insights into the achieved performance portability.

97 MATHEMATICS AND COMPUTING↗

Sampling on NISQ Devices: "Who’s the Fairest One of All?"

Modern NISQ devices are subject to a variety of biases and sources of noise that degrade the solution quality of computations carried out on these devices. A natural question that arises in the NISQ era, is how fairly do these devices sample ground state solutions. To this end, we run five fair sampling problems (each with at least three ground state solutions) that are based both on quantum annealing and, on the Grover Mixer, -QAOA algorithm for gate-based NISQ hardware. In particular, we use seven IBM Q devices, the Aspen-9 Rigetti device, the IonQ device, and three D-Wave quantum annealers. For each of the fair sampling problems, we measure the ground state probability, the relative fairness of the frequency of each ground state solution with respect to the other ground state solutions, and the aggregate error as given by each hardware provider. Overall, our results show that NISQ devices do not achieve fair sampling yet. Furthermore, we also observe differences in the software stack with a particular focus on compilation techniques that illustrate what work will still need to be done to achieve a seamless integration of frontend (i.e., quantum circuit description) and backend compilation.

Computer Science↗

SPEL: Software tool for Porting E3SM Land Model with OpenACC in a Function Unit Test Framework

Most high-end computers adopt hybrid architecture, porting a large-scale scientific code onto accelerators is necessary. The paper presents a generic method for porting large-scale scientific code onto accelerators using compiler directives within a modularized function unit test platform. We have implemented the method and designed a software tool (SPEL) to port the E3SM Land Model (ELM) onto the GPUs in the Summit computer. SPEL automatically generates GPU-ready test modules for all ELM functions, such as CanopyFlux, SoilTemperature, and EcosystemDynamics. SPEL breaks the ELM into a collection of standalone unit test programs for easy code verification and further performance improvement. We further optimize several ELM test modules with advanced techniques, including memory reduction, reconstructed parallel loops, and asynchronous GPU kernel launch. We hope our study will inspire new toolkit developments that expedite large-scale scientific code porting with compiler directives.

Schwartz, Peter↗

HSLOT: The HERCULES Scriptable Loop Transformations Engine

HSLOT arms users with a rich set of configurable transformation directives, to be used as-they-are or to be specialized and combined into powerful custom transformations. We offer a plethora of loop transformations, which includes both the classic set (unroll, fuse, fission, tile, and so on) as well as unique ones (specialize, swap nest, split, fork, and so on) that are not found in other state-of-the-art systems. We show how HSLOT enables more transformations such as merging two loops that cannot be fused because of data dependencies and how HSLOT can be used in a simple and systematic fashion to improve memory accesses and expose better parallelism. To use our system, users simply annotate loops with the transformations sequence and compile with our Open64-based HSLOTimplementing Fortran compiler, HSLF90, which produces both object files and optionally source. We describe our experiment results using a set of scientific kernels written in Fortran with HSLOT directives on AMD 32 core system.

Kartsaklis, Christos↗

Traits drive global wood decomposition rates more than climate

Wood decomposition is a major component of the global carbon cycle. Decomposition rates vary across climate gradients, which is thought to reflect the effects of temperature and moisture on the metabolic kinetics of decomposers. However, decomposition rates also vary with wood traits, which may reflect the influence of stoichiometry on decomposer metabolism as well as geometry relating the surface areas that decomposers colonize with the volumes they consume. In this paper, we combined metabolic and geometric scaling theories to formalize hypotheses regarding the drivers of wood decomposition rates, and assessed these hypotheses using a global compilation of data on climate, wood traits, and wood decomposition rates. Our results are consistent with predictions from both metabolic and geometric scaling theories. Approximately half of the global variation in decomposition rates was explained by wood traits (nitrogen content and diameter), whereas only a fifth was explained by climate variables (air temperature, precipitation, and relative humidity). These results indicate that global variation in wood decomposition rates is best explained by stoichiometric and geometric wood traits. Our findings suggest that inclusion of wood traits in global carbon cycle models can improve predictions of carbon fluxes from wood decomposition.

Hu, Zhenhong↗

Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

Abstract The regional variability in tundra and boreal carbon dioxide (CO 2 ) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO 2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO 2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO 2 fluxes and test the accuracy and uncertainty of different statistical models. CO 2 fluxes were upscaled at relatively high spatial resolution (1 km 2 ) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO 2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr −1 , respectively) compared to tundra (average annual NEE +10 and −2 g C m −2 yr −1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO 2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO 2 sink during 1990–2015, although uncertainty remains high.

Virkkala, Anna‐Maria↗

Health Benefits of Particle Filtration

The evidence of health benefits of particle filtration in homes and commercial buildings is reviewed. Prior reviews of papers published before 2000 are summarized. The results of 16 more recent intervention studies are compiled and analyzed. Also, reviewed are four studies that modeled health benefits of using filtration to reduce indoor exposures to particles from outdoors. Prior reviews generally concluded that particle filtration is, at best, a source of small improvements in allergy and asthma health effects; however, many early studies had weak designs. A majority of recent intervention studies employed strong designs and more of these studies report statistically significant improvements in health symptoms or objective health outcomes, particularly for subjects with allergies or asthma. The percent age improvement in health outcomes is typically modest, for example, 7percent to 25percent. Delivery of filtered air to the breathing zone of sleeping allergic or asthmatic persons may be more consistently effective in improving health than room air filtration. Notable are two studies that report statistically significant improvements, with filtration, in markers that predict future adverse coronary events. From modeling, the largest potential benefits of indoor particle filtration may be reductions in morbidity and mortality from reducing indoor exposures to particles from outdoor air.

54 ENVIRONMENTAL SCIENCES↗

Toward Understanding the Effect of Low-Activity Waste Glass Composition on Sulfur Solubility

The concentration of sulfur in nuclear waste glass melter feed must be maintained below the point where salt accumulates on the melt surface. The allowable concentrations may range from 0.37 to over 2.05 weight percent (of SO3 on a calcined oxide basis). If the amount of sulfur exceeds its tolerance level a molten salt will accumulate and upset melter operations and potentially shorten melter useful life. Therefore relatively conservative limits have been placed on sulfur loading in melter feed which in-turn significantly impacts the amount of glass that will be produced, in particular at the Hanford site. Crucible-scale sulfur solubility data and scaled melter sulfur tolerance data have been collected on simulated Hanford waste glasses over the last 15 years. These data were compiled and analyzed. A model was developed to predict the solubility of SO3 in glass based on 312 individual glass compositions. This model was shown to well represent the data, accounting for over 80% of the variation in data and was well validated. The model was also found to accurately predict the tolerance for sulfur in melter feed based on 19 scaled melter tests. The model is appropriate for control of waste glass processing which includes uncertainty quantification. The model also gives quantitative estimates of component concentration effects on sulfur solubility. The components that most increase sulfur solubility are Li2O > V2O5 ≈ TiO2 < CaO < P2O5 ≈ ZnO. The components that most decrease sulfur solubility are Cl > Cr2O3 > SiO2 ≈ ZrO2 > Al2O3.

Borosilicate↗

Predicting nepheline precipitation in waste glasses using ternary submixture model and machine learning

Nepheline precipitation in nuclear waste glasses during vitrification can be detrimental due to its negative effect on chemical durability. Developing models to accurately predict nepheline precipitation from compositions is important to increase waste loading since existing models can be overly conservative. In this study, an expanded dataset containing 955 glasses was compiled from literature data, where 355 glasses are for high-level waste (HLW). Previously developed submixture models were refitted using the new dataset, where a misclassification rate of 7.8% was achieved. Nine machine learning (ML) algorithms (e.g., k-nearest neighbor, Gaussian process regression, artificial neural network, support vector machine, decision tree, etc.) were applied to evaluate their ability of predicting nepheline precipitation from compositions. Model accuracy, precision, recall/sensitivity, and F1 score were systemically compared between different ML algorithms and modeling protocols. Good model prediction with an accuracy ~0.9 (misclassification rate of ~10%) was observed with different algorithms under certain protocol. This study evaluated various ML models to predict nepheline precipitations in waste glasses, highlighting the importance of data preparation, modeling protocol, and their effect on model stability and reproducibility. The results provide insights into applying ML to predict glass properties and suggest areas for future research on modeling nepheline precipitations.

Lu, Xiaonan↗

A Critical Review of Heliostat Design for Concentrating Solar Thermal Technologies

Heliostat designs have undergone a widespread and eclectic development process, with many unique designs demonstrated. However, recent developments do not show the overall cohort converging toward a globally accepted universal design. Here, this study characterizes heliostats by breaking down and evaluating design traits based on emergent patterns from a comprehensive compilation of known heliostat designs spanning several decades. Four main categories for evaluation emerged: heliostat base, heliostat primary axis, heliostat drive, and facet support. Each of these four categories is further defined by four subtypes so that all heliostats fall into a single subtype within each category. The classified heliostats are ranked, yielding several view slices into the heliostat compilation or a breakdown of heliostats by type. An analysis of the breakdown shows several trends: a scale-up of established designs, new approaches at small to medium scales, and a movement toward greater adoption of linear drives. These trends reflect the most meaningful contributing factors to a proposed trajectory for a new era of heliostat designs striving to meet widely considered cost targets of $\$$50/m 2 or $\$$75/m 2 .

14 SOLAR ENERGY↗

SU-E-J-104: Single Photon Image From PET with Insertable SPECT Collimator for Boron Neutron Capture Therapy: A Feasibility Study

Purpose: The aim of our proposed system is to confirm the feasibility of extraction of two types of images from one positron emission tomography (PET) module with an insertable collimator for brain tumor treatment during the BNCT. Methods: Data from the PET module, neutron source, and collimator was entered in the Monte Carlo n-particle extended (MCNPX) source code. The coincidence events were first compiled on the PET detector, and then, the events of the prompt gamma ray were collected after neutron emission by using a single photon emission computed tomography (SPECT) collimator on the PET. The obtaining of full width at half maximum (FWHM) values from the energy spectrum was performed to collect effective events for reconstructed image. In order to evaluate the images easily, five boron regions in a brain phantom were used. The image profiles were extracted from the region of interest (ROI) of a phantom. The image was reconstructed using the ordered subsets expectation maximization (OSEM) reconstruction algorithm. The image profiles and the receiver operating characteristic (ROC) curve were compiled for quantitative analysis from the two kinds of reconstructed image. Results: The prompt gamma ray energy peak of 478 keV appeared in the energy spectrum with a FWHM of 41 keV (6.4%). On the basis of the ROC curve in Region A to Region E, the differences in the area under the curve (AUC) of the PET and SPECT images were found to be 10.2%, 11.7%, 8.2% (center, Region C), 12.6%, and 10.5%, respectively. Conclusion: We attempted to acquire the PET and SPECT images simultaneously using only PET without an additional isotope. Single photon images were acquired using an insertable collimator on a PET detector. This research was supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies (ICT) and Future Planning (MSIP)(Grant No.2009 00420) and the Radiation Technology R and D program (Grant No.2013M2A2A7043498), Republic of Korea.

07 ISOTOPE AND RADIATION SOURCES↗

TH-E-BRD-01: Innovation in (gold) Nanoparticle-Enhanced Therapy

Radiation therapy relies on the concept of delivering high dose to tumor volumes whilst simultaneously aiming to minimize irradiation of healthy tissue. Gold and other metallic nanoparticles (GNPs) have the potential to greatly enhance dose depositions in their close proximity. While it was originally thought that this effect would only be significant for kV photon beams, it has been shown that GNPs also enhance dose and increase cell killing and survival fraction for MV photons as well as protons. GNPs have been shown to be preferentially taken up in tumors, depending on the GNP properties either internalized in the tumor cells or clustering in the tumor vasculature. Therefore GNPs offer an intriguing additional option to target the tumor while sparing healthy tissue. While a growing amount of research shows GNP induced enhancement factors in the order of 1.5 and higher, GNPs have not yet entered into clinical routine. In this symposium we will have three presentations discussing the current status of GNP based research, the potential to include GNPs in radiation therapy and the limitations and problems to use GNPs in the clinic. Physical and biological underpinnings of radiosensitization with gold nano particles An evolving body of recent literature alludes to the potential to sensitize tumors to radiation therapy using metallic nanoparticles. In preclinical studies, the techniques that hold promise for eventual clinical deployment are nanoparticle-assisted radiation dose enhancement and hyperthermic radiosensitization. To understand the underlying nanoparticle-radiation interactions, computational techniques offer an explanation for and predict the biophysical consequences at a nano-/meso-scopic scale. Nonetheless, there are persisting gaps in knowledge relating to the molecular mechanism of action of these radiosensitization approaches — some of these issues will be addressed. Since the literature relating to the diverse disciplines involved in these efforts spans across multiple specialties (clinical radiation oncology, radiation physics, radiation biology, nanotechnology, material science, biomedical engineering, pharmacology, chemistry, and tumor biology) and numerous specialty journals, there is no single compilation of extant research in this arena or forum for merging analogous concepts and paradigms. This symposium will provide such a venue — my presentation will start with familiarizing the audience with the potential applications of metallic nanoparticles in radiation therapy using specific illustrative examples and begin to explore ways to understand the underlying mechanisms of the effects observed. Biological effects of Gold nanoparticles in radiation therapy Gold nanoparticles (GNP) have been investigated as platforms to carry drugs or radio-sensitizing agents to tumors due to the biocompatibility of gold and relative ease of conjugation with therapeutic and targeting moieties. Recently, there has been interest in exploiting the physical properties of gold, specifically the high atomic number, to enhance radiation therapy. When irradiated, gold atoms will produce low energy electrons, depositing energy within a short distance. The ratio of dose deposited in the presence of the GNP to the dose deposited in the absence of GNP is referred to as the dose enhancement factor (DEF). This factor has been shown to depend on the concentration of GNP and the energy of the incident photons. The physics of this process, preliminary in vitro and in vivo experiments and future directions for this nascent field are described in this presentation. Gold Nanoparticles for improved therapeutic outcome in radiation therapy The application of nanoparticles (NPs) for improved therapeutics is at the forefront of cancer nanotechnology. Among other NP systems, gold nanoparticles (GNPs) are extensively used due to its impressive ability to act as both an anticancer drug carrier in chemotherapy and as a dose enhancer in radiotherapy. Cellular uptake of GNPs was dependent on their size. Among GNPs of diameter between 14–74 nm, GNPs of size 50 nm has the highest uptake. Radiosensitization was dependent on the size of the GNPs as well. GNPs of size 50-nm showed the highest radiosensitization enhancement factor compared to GNPs of 14 and 74 nm for lower- (105 kVp) and higher- (6 MVp) energy photons. GNPs used in those studies were predominantly localized in the cell cytoplasm. However, the therapeutic response can be further enhanced if NPs can be effectively targeted into the nucleus. Here, we present an effective strategy for designing a GNP-peptide complex for nuclear targeting. Two peptides were conjugated onto a GNP: One peptide enhanced the uptake while the other peptide enhanced the nuclear delivery. The nuclear-targeted cells displayed a fourfold increase in the therapeutic response when treated with radiation as compared to untargeted ones. DNA double-strand breaks were quantified using radiation-induced foci of γ- H2AX and 53BP1, and a modest increase in the number of foci per nucleus was observed in irradiated cell populations with internalized GNPs. This research will establish a more aggressive NP-based treatment approach for improved outcome in cancer therapy. Learning Objectives: Introduce radiosensitization concepts of metallic nanoparticle and provide the theoretical basis Provide an overview over the size and coating dependence for GNP uptake in cells Provide a compilation of the extant, multi-discipline research on metallic nanoparticles Understand the prospects for future studies and innovations and the potential for applications of metallic nanoparticles in radiation therapy.

60 APPLIED LIFE SCIENCES↗