A scalable parallel algorithm for multiple objective linear programs

NASA Technical Reports Server (NTRS)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

Optimized bit extraction using distortion modeling in the scalable extension of H.264/AVC.

PubMed

Maani, Ehsan; Katsaggelos, Aggelos K

2009-09-01

The newly adopted scalable extension of H.264/AVC video coding standard (SVC) demonstrates significant improvements in coding efficiency in addition to an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. Due to the complicated hierarchical prediction structure of the SVC and the concept of key pictures, content-aware rate adaptation of SVC bit streams to intermediate bit rates is a nontrivial task. The concept of quality layers has been introduced in the design of the SVC to allow for fast content-aware prioritized rate adaptation. However, existing quality layer assignment methods are suboptimal and do not consider all network abstraction layer (NAL) units from different layers for the optimization. In this paper, we first propose a technique to accurately and efficiently estimate the quality degradation resulting from discarding an arbitrary number of NAL units from multiple layers of a bitstream by properly taking drift into account. Then, we utilize this distortion estimation technique to assign quality layers to NAL units for a more efficient extraction. Experimental results show that a significant gain can be achieved by the proposed scheme.

The Efficiency and the Scalability of an Explicit Operator on an IBM POWER4 System

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Biegel, Bryan A. (Technical Monitor)

2002-01-01

We present an evaluation of the efficiency and the scalability of an explicit CFD operator on an IBM POWER4 system. The POWER4 architecture exhibits a common trend in HPC architectures: boosting CPU processing power by increasing the number of functional units, while hiding the latency of memory access by increasing the depth of the memory hierarchy. The overall machine performance depends on the ability of the caches-buses-fabric-memory to feed the functional units with the data to be processed. In this study we evaluate the efficiency and scalability of one explicit CFD operator on an IBM POWER4. This operator performs computations at the points of a Cartesian grid and involves a few dozen floating point numbers and on the order of 100 floating point operations per grid point. The computations in all grid points are independent. Specifically, we estimate the efficiency of the RHS operator (SP of NPB) on a single processor as the observed/peak performance ratio. Then we estimate the scalability of the operator on a single chip (2 CPUs), a single MCM (8 CPUs), 16 CPUs, and the whole machine (32 CPUs). Then we perform the same measurements for a chache-optimized version of the RHS operator. For our measurements we use the HPM (Hardware Performance Monitor) counters available on the POWER4. These counters allow us to analyze the obtained performance results.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE PAGES

Desai, Ajit; Khalil, Mohammad; Pettit, Chris; ...

2017-09-21

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desai, Ajit; Khalil, Mohammad; Pettit, Chris

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm.

PubMed

Kamath, Uday; Domeniconi, Carlotta; De Jong, Kenneth

2018-01-01

Many real-world problems involve massive amounts of data. Under these circumstances learning algorithms often become prohibitively expensive, making scalability a pressing issue to be addressed. A common approach is to perform sampling to reduce the size of the dataset and enable efficient learning. Alternatively, one customizes learning algorithms to achieve scalability. In either case, the key challenge is to obtain algorithmic efficiency without compromising the quality of the results. In this article we discuss a meta-learning algorithm (PSBML) that combines concepts from spatially structured evolutionary algorithms (SSEAs) with concepts from ensemble and boosting methodologies to achieve the desired scalability property. We present both theoretical and empirical analyses which show that PSBML preserves a critical property of boosting, specifically, convergence to a distribution centered around the margin. We then present additional empirical analyses showing that this meta-level algorithm provides a general and effective framework that can be used in combination with a variety of learning classifiers. We perform extensive experiments to investigate the trade-off achieved between scalability and accuracy, and robustness to noise, on both synthetic and real-world data. These empirical results corroborate our theoretical analysis, and demonstrate the potential of PSBML in achieving scalability without sacrificing accuracy.

Enhancing Scalability and Efficiency of the TOUGH2_MP for LinuxClusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Keni; Wu, Yu-Shu

2006-04-17

TOUGH2{_}MP, the parallel version TOUGH2 code, has been enhanced by implementing more efficient communication schemes. This enhancement is achieved through reducing the amount of small-size messages and the volume of large messages. The message exchange speed is further improved by using non-blocking communications for both linear and nonlinear iterations. In addition, we have modified the AZTEC parallel linear-equation solver to nonblocking communication. Through the improvement of code structuring and bug fixing, the new version code is now more stable, while demonstrating similar or even better nonlinear iteration converging speed than the original TOUGH2 code. As a result, the new versionmore » of TOUGH2{_}MP is improved significantly in its efficiency. In this paper, the scalability and efficiency of the parallel code are demonstrated by solving two large-scale problems. The testing results indicate that speedup of the code may depend on both problem size and complexity. In general, the code has excellent scalability in memory requirement as well as computing time.« less

Efficient and Scalable Graph Similarity Joins in MapReduce

PubMed Central

Chen, Yifan; Zhang, Weiming; Tang, Jiuyang

2014-01-01

Along with the emergence of massive graph-modeled data, it is of great importance to investigate graph similarity joins due to their wide applications for multiple purposes, including data cleaning, and near duplicate detection. This paper considers graph similarity joins with edit distance constraints, which return pairs of graphs such that their edit distances are no larger than a given threshold. Leveraging the MapReduce programming model, we propose MGSJoin, a scalable algorithm following the filtering-verification framework for efficient graph similarity joins. It relies on counting overlapping graph signatures for filtering out nonpromising candidates. With the potential issue of too many key-value pairs in the filtering phase, spectral Bloom filters are introduced to reduce the number of key-value pairs. Furthermore, we integrate the multiway join strategy to boost the verification, where a MapReduce-based method is proposed for GED calculation. The superior efficiency and scalability of the proposed algorithms are demonstrated by extensive experimental results. PMID:25121135

Efficient and scalable graph similarity joins in MapReduce.

PubMed

Chen, Yifan; Zhao, Xiang; Xiao, Chuan; Zhang, Weiming; Tang, Jiuyang

2014-01-01

Along with the emergence of massive graph-modeled data, it is of great importance to investigate graph similarity joins due to their wide applications for multiple purposes, including data cleaning, and near duplicate detection. This paper considers graph similarity joins with edit distance constraints, which return pairs of graphs such that their edit distances are no larger than a given threshold. Leveraging the MapReduce programming model, we propose MGSJoin, a scalable algorithm following the filtering-verification framework for efficient graph similarity joins. It relies on counting overlapping graph signatures for filtering out nonpromising candidates. With the potential issue of too many key-value pairs in the filtering phase, spectral Bloom filters are introduced to reduce the number of key-value pairs. Furthermore, we integrate the multiway join strategy to boost the verification, where a MapReduce-based method is proposed for GED calculation. The superior efficiency and scalability of the proposed algorithms are demonstrated by extensive experimental results.

Low-power, transparent optical network interface for high bandwidth off-chip interconnects.

PubMed

Liboiron-Ladouceur, Odile; Wang, Howard; Garg, Ajay S; Bergman, Keren

2009-04-13

The recent emergence of multicore architectures and chip multiprocessors (CMPs) has accelerated the bandwidth requirements in high-performance processors for both on-chip and off-chip interconnects. For next generation computing clusters, the delivery of scalable power efficient off-chip communications to each compute node has emerged as a key bottleneck to realizing the full computational performance of these systems. The power dissipation is dominated by the off-chip interface and the necessity to drive high-speed signals over long distances. We present a scalable photonic network interface approach that fully exploits the bandwidth capacity offered by optical interconnects while offering significant power savings over traditional E/O and O/E approaches. The power-efficient interface optically aggregates electronic serial data streams into a multiple WDM channel packet structure at time-of-flight latencies. We demonstrate a scalable optical network interface with 70% improvement in power efficiency for a complete end-to-end PCI Express data transfer.

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Seal, Sudip K

2011-01-01

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post-facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks make it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction-diffusion simulation model of epidemic propagation is presented to facilitate in dramatically increasing the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallelmore » execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene / P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes exceeding several hundreds of millions of individuals in the largest cases are successfully exercised to verify model scalability.« less

Graphene oxide-based efficient and scalable solar desalination under one sun with a confined 2D water path

PubMed Central

Li, Xiuqiang; Xu, Weichao; Tang, Mingyao; Zhou, Lin; Zhu, Bin; Zhu, Shining; Zhu, Jia

2016-01-01

Because it is able to produce desalinated water directly using solar energy with minimum carbon footprint, solar steam generation and desalination is considered one of the most important technologies to address the increasingly pressing global water scarcity. Despite tremendous progress in the past few years, efficient solar steam generation and desalination can only be achieved for rather limited water quantity with the assistance of concentrators and thermal insulation, not feasible for large-scale applications. The fundamental paradox is that the conventional design of direct absorber−bulk water contact ensures efficient energy transfer and water supply but also has intrinsic thermal loss through bulk water. Here, enabled by a confined 2D water path, we report an efficient (80% under one-sun illumination) and effective (four orders salinity decrement) solar desalination device. More strikingly, because of minimized heat loss, high efficiency of solar desalination is independent of the water quantity and can be maintained without thermal insulation of the container. A foldable graphene oxide film, fabricated by a scalable process, serves as efficient solar absorbers (>94%), vapor channels, and thermal insulators. With unique structure designs fabricated by scalable processes and high and stable efficiency achieved under normal solar illumination independent of water quantity without any supporting systems, our device represents a concrete step for solar desalination to emerge as a complementary portable and personalized clean water solution. PMID:27872280

Graphene oxide-based efficient and scalable solar desalination under one sun with a confined 2D water path.

PubMed

Li, Xiuqiang; Xu, Weichao; Tang, Mingyao; Zhou, Lin; Zhu, Bin; Zhu, Shining; Zhu, Jia

2016-12-06

Because it is able to produce desalinated water directly using solar energy with minimum carbon footprint, solar steam generation and desalination is considered one of the most important technologies to address the increasingly pressing global water scarcity. Despite tremendous progress in the past few years, efficient solar steam generation and desalination can only be achieved for rather limited water quantity with the assistance of concentrators and thermal insulation, not feasible for large-scale applications. The fundamental paradox is that the conventional design of direct absorber-bulk water contact ensures efficient energy transfer and water supply but also has intrinsic thermal loss through bulk water. Here, enabled by a confined 2D water path, we report an efficient (80% under one-sun illumination) and effective (four orders salinity decrement) solar desalination device. More strikingly, because of minimized heat loss, high efficiency of solar desalination is independent of the water quantity and can be maintained without thermal insulation of the container. A foldable graphene oxide film, fabricated by a scalable process, serves as efficient solar absorbers (>94%), vapor channels, and thermal insulators. With unique structure designs fabricated by scalable processes and high and stable efficiency achieved under normal solar illumination independent of water quantity without any supporting systems, our device represents a concrete step for solar desalination to emerge as a complementary portable and personalized clean water solution.

Volumetric Medical Image Coding: An Object-based, Lossy-to-lossless and Fully Scalable Approach

PubMed Central

Danyali, Habibiollah; Mertins, Alfred

2011-01-01

In this article, an object-based, highly scalable, lossy-to-lossless 3D wavelet coding approach for volumetric medical image data (e.g., magnetic resonance (MR) and computed tomography (CT)) is proposed. The new method, called 3DOBHS-SPIHT, is based on the well-known set partitioning in the hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. The 3D input data is grouped into groups of slices (GOS) and each GOS is encoded and decoded as a separate unit. The symmetric tree definition of the original 3DSPIHT is improved by introducing a new asymmetric tree structure. While preserving the compression efficiency, the new tree structure allows for a small size of each GOS, which not only reduces memory consumption during the encoding and decoding processes, but also facilitates more efficient random access to certain segments of slices. To achieve more compression efficiency, the algorithm only encodes the main object of interest in each 3D data set, which can have any arbitrary shape, and ignores the unnecessary background. The experimental results on some MR data sets show the good performance of the 3DOBHS-SPIHT algorithm for multi-resolution lossy-to-lossless coding. The compression efficiency, full scalability, and object-based features of the proposed approach, beside its lossy-to-lossless coding support, make it a very attractive candidate for volumetric medical image information archiving and transmission applications. PMID:22606653

Algorithmic Coordination in Robotic Networks

DTIC Science & Technology

2010-11-29

appropriate performance, robustness and scalability properties for various task allocation , surveillance, and information gathering applications is...networking, we envision designing and analyzing algorithms with appropriate performance, robustness and scalability properties for various task ...distributed algorithms for target assignments; based on the classic auction algorithms in static networks, we intend to design efficient algorithms in worst

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2 21 = 2,097,152 MPI processes on the IBMmore » BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.« less

Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

NASA Astrophysics Data System (ADS)

Garrido-Cantos, Rosario; De Cock, Jan; Martínez, Jose Luis; Van Leuven, Sebastian; Cuenca, Pedro; Garrido, Antonio

2013-12-01

Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

Health Statistics NSW: getting the right balance between privacy and small numbers in a web-based reporting system.

PubMed

Scandol, James P; Moore, Helen A

2012-01-01

Health Statistics NSW is a new web-based application developed by the Centre for Epidemiology and Research at the NSW Ministry of Health. The application is designed to be an efficient vehicle for the timely delivery of health statistics to a diverse audience including the general public, health planners, researchers, students and policy analysts. The development and implementation of this web application required the consideration of a series of competing demands such as: the public interest in providing health data while maintaining the privacy interests of the individuals whose health is being reported; reporting data at spatial scales of relevance to health planners while maintaining the statistical integrity of any inferences drawn; the use of hardware and software systems which are publicly accessible, scalable and robust, while ensuring high levels of security. These three competing demands and the relationships between them are discussed in the context of Health Statistics NSW.

Platform for efficient switching between multiple devices in the intensive care unit.

PubMed

De Backere, F; Vanhove, T; Dejonghe, E; Feys, M; Herinckx, T; Vankelecom, J; Decruyenaere, J; De Turck, F

2015-01-01

This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Handheld computers, such as tablets and smartphones, are becoming more and more accessible in the clinical care setting and in Intensive Care Units (ICUs). By making the most useful and appropriate data available on multiple devices and facilitate the switching between those devices, staff members can efficiently integrate them in their workflow, allowing for faster and more accurate decisions. This paper addresses the design of a platform for the efficient switching between multiple devices in the ICU. The key functionalities of the platform are the integration of the platform into the workflow of the medical staff and providing tailored and dynamic information at the point of care. The platform is designed based on a 3-tier architecture with a focus on extensibility, scalability and an optimal user experience. After identification to a device using Near Field Communication (NFC), the appropriate medical information will be shown on the selected device. The visualization of the data is adapted to the type of the device. A web-centric approach was used to enable extensibility and portability. A prototype of the platform was thoroughly evaluated. The scalability, performance and user experience were evaluated. Performance tests show that the response time of the system scales linearly with the amount of data. Measurements with up to 20 devices have shown no performance loss due to the concurrent use of multiple devices. The platform provides a scalable and responsive solution to enable the efficient switching between multiple devices. Due to the web-centric approach new devices can easily be integrated. The performance and scalability of the platform have been evaluated and it was shown that the response time and scalability of the platform was within an acceptable range.

Efficient scalable solid-state neutron detector.

PubMed

Moses, Daniel

2015-06-01

We report on scalable solid-state neutron detector system that is specifically designed to yield high thermal neutron detection sensitivity. The basic detector unit in this system is made of a (6)Li foil coupled to two crystalline silicon diodes. The theoretical intrinsic efficiency of a detector-unit is 23.8% and that of detector element comprising a stack of five detector-units is 60%. Based on the measured performance of this detector-unit, the performance of a detector system comprising a planar array of detector elements, scaled to encompass effective area of 0.43 m(2), is estimated to yield the minimum absolute efficiency required of radiological portal monitors used in homeland security.

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data

PubMed Central

Gogoshin, Grigoriy; Boerwinkle, Eric

2017-01-01

Abstract Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology—type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types—single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc. PMID:27681505

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data.

PubMed

Gogoshin, Grigoriy; Boerwinkle, Eric; Rodin, Andrei S

2017-04-01

Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology-type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types-single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc.

Scalable software-defined optical networking with high-performance routing and wavelength assignment algorithms.

PubMed

Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin

2015-10-19

The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study.

Embedded DCT and wavelet methods for fine granular scalable video: analysis and comparison

NASA Astrophysics Data System (ADS)

van der Schaar-Mitrea, Mihaela; Chen, Yingwei; Radha, Hayder

2000-04-01

Video transmission over bandwidth-varying networks is becoming increasingly important due to emerging applications such as streaming of video over the Internet. The fundamental obstacle in designing such systems resides in the varying characteristics of the Internet (i.e. bandwidth variations and packet-loss patterns). In MPEG-4, a new SNR scalability scheme, called Fine-Granular-Scalability (FGS), is currently under standardization, which is able to adapt in real-time (i.e. at transmission time) to Internet bandwidth variations. The FGS framework consists of a non-scalable motion-predicted base-layer and an intra-coded fine-granular scalable enhancement layer. For example, the base layer can be coded using a DCT-based MPEG-4 compliant, highly efficient video compression scheme. Subsequently, the difference between the original and decoded base-layer is computed, and the resulting FGS-residual signal is intra-frame coded with an embedded scalable coder. In order to achieve high coding efficiency when compressing the FGS enhancement layer, it is crucial to analyze the nature and characteristics of residual signals common to the SNR scalability framework (including FGS). In this paper, we present a thorough analysis of SNR residual signals by evaluating its statistical properties, compaction efficiency and frequency characteristics. The signal analysis revealed that the energy compaction of the DCT and wavelet transforms is limited and the frequency characteristic of SNR residual signals decay rather slowly. Moreover, the blockiness artifacts of the low bit-rate coded base-layer result in artificial high frequencies in the residual signal. Subsequently, a variety of wavelet and embedded DCT coding techniques applicable to the FGS framework are evaluated and their results are interpreted based on the identified signal properties. As expected from the theoretical signal analysis, the rate-distortion performances of the embedded wavelet and DCT-based coders are very similar. However, improved results can be obtained for the wavelet coder by deblocking the base- layer prior to the FGS residual computation. Based on the theoretical analysis and our measurements, we can conclude that for an optimal complexity versus coding-efficiency trade- off, only limited wavelet decomposition (e.g. 2 stages) needs to be performed for the FGS-residual signal. Also, it was observed that the good rate-distortion performance of a coding technique for a certain image type (e.g. natural still-images) does not necessarily translate into similarly good performance for signals with different visual characteristics and statistical properties.

Scalable Implementation of Finite Elements by NASA _ Implicit (ScIFEi)

NASA Technical Reports Server (NTRS)

Warner, James E.; Bomarito, Geoffrey F.; Heber, Gerd; Hochhalter, Jacob D.

2016-01-01

Scalable Implementation of Finite Elements by NASA (ScIFEN) is a parallel finite element analysis code written in C++. ScIFEN is designed to provide scalable solutions to computational mechanics problems. It supports a variety of finite element types, nonlinear material models, and boundary conditions. This report provides an overview of ScIFEi (\\Sci-Fi"), the implicit solid mechanics driver within ScIFEN. A description of ScIFEi's capabilities is provided, including an overview of the tools and features that accompany the software as well as a description of the input and output le formats. Results from several problems are included, demonstrating the efficiency and scalability of ScIFEi by comparing to finite element analysis using a commercial code.

An efficient and provable secure revocable identity-based encryption scheme.

PubMed

Wang, Changji; Li, Yuan; Xia, Xiaonan; Zheng, Kangjia

2014-01-01

Revocation functionality is necessary and crucial to identity-based cryptosystems. Revocable identity-based encryption (RIBE) has attracted a lot of attention in recent years, many RIBE schemes have been proposed in the literature but shown to be either insecure or inefficient. In this paper, we propose a new scalable RIBE scheme with decryption key exposure resilience by combining Lewko and Waters' identity-based encryption scheme and complete subtree method, and prove our RIBE scheme to be semantically secure using dual system encryption methodology. Compared to existing scalable and semantically secure RIBE schemes, our proposed RIBE scheme is more efficient in term of ciphertext size, public parameters size and decryption cost at price of a little looser security reduction. To the best of our knowledge, this is the first construction of scalable and semantically secure RIBE scheme with constant size public system parameters.

A comprehensive study of MPI parallelism in three-dimensional discrete element method (DEM) simulation of complex-shaped granular particles

NASA Astrophysics Data System (ADS)

Yan, Beichuan; Regueiro, Richard A.

2018-02-01

A three-dimensional (3D) DEM code for simulating complex-shaped granular particles is parallelized using message-passing interface (MPI). The concepts of link-block, ghost/border layer, and migration layer are put forward for design of the parallel algorithm, and theoretical scalability function of 3-D DEM scalability and memory usage is derived. Many performance-critical implementation details are managed optimally to achieve high performance and scalability, such as: minimizing communication overhead, maintaining dynamic load balance, handling particle migrations across block borders, transmitting C++ dynamic objects of particles between MPI processes efficiently, eliminating redundant contact information between adjacent MPI processes. The code executes on multiple US Department of Defense (DoD) supercomputers and tests up to 2048 compute nodes for simulating 10 million three-axis ellipsoidal particles. Performance analyses of the code including speedup, efficiency, scalability, and granularity across five orders of magnitude of simulation scale (number of particles) are provided, and they demonstrate high speedup and excellent scalability. It is also discovered that communication time is a decreasing function of the number of compute nodes in strong scaling measurements. The code's capability of simulating a large number of complex-shaped particles on modern supercomputers will be of value in both laboratory studies on micromechanical properties of granular materials and many realistic engineering applications involving granular materials.

Equalizer: a scalable parallel rendering framework.

PubMed

Eilemann, Stefan; Makhinya, Maxim; Pajarola, Renato

2009-01-01

Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantages over previous approaches, present example configurations and usage scenarios as well as scalability results.

Two-dimensional photonic crystal slab nanocavities on bulk single-crystal diamond

NASA Astrophysics Data System (ADS)

Wan, Noel H.; Mouradian, Sara; Englund, Dirk

2018-04-01

Color centers in diamond are promising spin qubits for quantum computing and quantum networking. In photon-mediated entanglement distribution schemes, the efficiency of the optical interface ultimately determines the scalability of such systems. Nano-scale optical cavities coupled to emitters constitute a robust spin-photon interface that can increase spontaneous emission rates and photon extraction efficiencies. In this work, we introduce the fabrication of 2D photonic crystal slab nanocavities with high quality factors and cubic wavelength mode volumes—directly in bulk diamond. This planar platform offers scalability and considerably expands the toolkit for classical and quantum nanophotonics in diamond.

GapMap: Enabling Comprehensive Autism Resource Epidemiology

PubMed Central

Albert, Nikhila; Schwartz, Jessey; Du, Michael

2017-01-01

Background For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. Objective The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. Methods We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. Results The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. Conclusions This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates. PMID:28473303

GapMap: Enabling Comprehensive Autism Resource Epidemiology.

PubMed

Albert, Nikhila; Daniels, Jena; Schwartz, Jessey; Du, Michael; Wall, Dennis P

2017-05-04

For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates. ©Nikhila Albert, Jena Daniels, Jessey Schwartz, Michael Du, Dennis P Wall. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 04.05.2017.

Analysis of scalability of high-performance 3D image processing platform for virtual colonoscopy

NASA Astrophysics Data System (ADS)

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli

2014-03-01

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. For this purpose, we previously developed a software platform for high-performance 3D medical image processing, called HPC 3D-MIP platform, which employs increasingly available and affordable commodity computing systems such as the multicore, cluster, and cloud computing systems. To achieve scalable high-performance computing, the platform employed size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D-MIP algorithms, supported task scheduling for efficient load distribution and balancing, and consisted of a layered parallel software libraries that allow image processing applications to share the common functionalities. We evaluated the performance of the HPC 3D-MIP platform by applying it to computationally intensive processes in virtual colonoscopy. Experimental results showed a 12-fold performance improvement on a workstation with 12-core CPUs over the original sequential implementation of the processes, indicating the efficiency of the platform. Analysis of performance scalability based on the Amdahl's law for symmetric multicore chips showed the potential of a high performance scalability of the HPC 3DMIP platform when a larger number of cores is available.

Scuba: scalable kernel-based gene prioritization.

PubMed

Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

2018-01-25

The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

XPRESS: eXascale PRogramming Environment and System Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brightwell, Ron; Sterling, Thomas; Koniges, Alice

The XPRESS Project is one of four major projects of the DOE Office of Science Advanced Scientific Computing Research X-stack Program initiated in September, 2012. The purpose of XPRESS is to devise an innovative system software stack to enable practical and useful exascale computing around the end of the decade with near-term contributions to efficient and scalable operation of trans-Petaflops performance systems in the next two to three years; both for DOE mission-critical applications. To this end, XPRESS directly addresses critical challenges in computing of efficiency, scalability, and programmability through introspective methods of dynamic adaptive resource management and task scheduling.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce.

PubMed

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2013-11-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS - a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing.

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

NASA Astrophysics Data System (ADS)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.

Ceramic high temperature receiver design and tests

NASA Technical Reports Server (NTRS)

Davis, S. B.

1982-01-01

The High Temperature Solar Thermal Receiver, which was tested a Edwards AFB, CA during the winter of 1980-1981, evolved from technologies developed over a five year period of work. This receiver was tested at the Army Solar Furnace at White Sands, NM in 1976. The receiver, was tested successfully at 1768 deg F and showed thermal efficiencies of 85%. The results were sufficiently promising to lead ERDA to fund our development and test of a 250 kW receiver to measure the efficiency of an open cavity receiver atop a central tower of a heliostat field. This receiver was required to be design scalable to 10, 50, and 100 MW-electric sizes to show applicability to central power tower receivers. That receiver employed rectagular silicon carbide panels and vertical stanchions to achieve scalability. The construction was shown to be fully scalable; and the receiver was operated at temperatures up to 2000 deg F to achieve the performance goals of the experiment during tests at the GIT advanced components test facility during the fall of 1978.

MarFS, Version 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inman, Jeffrey; Bonnie, David; Broomfield, Matthew

There is a sea (mar is Spanish for sea) of data out there that needs to be handled efficiently. Object Stores are filling the hole of managing large amounts of data efficiently. However, in many cases, and our HPC case in particular, we need a traditional file (POSIX) interface to this data as HPC I/O models have not moved to object interfaces, such as Amazon S3, CDMI, etc.Eventually Object Store providers may deliver file interfaces to their object stores, but at this point those interfaces are not ready to do the job that we need done. MarFS will glue togethermore » two existing scalable components: a file system's scalable metadata component that provides the file interface; and existing scalable object stores (from one or more providers). There will be utilities to do work that is not critical to be done in real-time so that MarFS can manage the space used by objects and allocated to individual users.« less

ExSTraCS 2.0: Description and Evaluation of a Scalable Learning Classifier System.

PubMed

Urbanowicz, Ryan J; Moore, Jason H

2015-09-01

Algorithmic scalability is a major concern for any machine learning strategy in this age of 'big data'. A large number of potentially predictive attributes is emblematic of problems in bioinformatics, genetic epidemiology, and many other fields. Previously, ExS-TraCS was introduced as an extended Michigan-style supervised learning classifier system that combined a set of powerful heuristics to successfully tackle the challenges of classification, prediction, and knowledge discovery in complex, noisy, and heterogeneous problem domains. While Michigan-style learning classifier systems are powerful and flexible learners, they are not considered to be particularly scalable. For the first time, this paper presents a complete description of the ExS-TraCS algorithm and introduces an effective strategy to dramatically improve learning classifier system scalability. ExSTraCS 2.0 addresses scalability with (1) a rule specificity limit, (2) new approaches to expert knowledge guided covering and mutation mechanisms, and (3) the implementation and utilization of the TuRF algorithm for improving the quality of expert knowledge discovery in larger datasets. Performance over a complex spectrum of simulated genetic datasets demonstrated that these new mechanisms dramatically improve nearly every performance metric on datasets with 20 attributes and made it possible for ExSTraCS to reliably scale up to perform on related 200 and 2000-attribute datasets. ExSTraCS 2.0 was also able to reliably solve the 6, 11, 20, 37, 70, and 135 multiplexer problems, and did so in similar or fewer learning iterations than previously reported, with smaller finite training sets, and without using building blocks discovered from simpler multiplexer problems. Furthermore, ExS-TraCS usability was made simpler through the elimination of previously critical run parameters.

Developing a scalable inert gas ion thruster

NASA Technical Reports Server (NTRS)

James, E.; Ramsey, W.; Steiner, G.

1982-01-01

Analytical studies to identify and then design a high performance scalable ion thruster operating with either argon or xenon for use in large space systems are presented. The magnetoelectrostatic containment concept is selected for its efficient ion generation capabilities. The iterative nature of the bounding magnetic fields allows the designer to scale both the diameter and length, so that the thruster can be adapted to spacecraft growth over time. Three different thruster assemblies (conical, hexagonal and hemispherical) are evaluated for a 12 cm diameter thruster and performance mapping of the various thruster configurations shows that conical discharge chambers produce the most efficient discharge operation, achieving argon efficiencies of 50-80% mass utilization at 240-310 eV/ion and xenon efficiencies of 60-97% at 240-280 eV/ion. Preliminary testing of the large 30 cm thruster, using argon propellant, indicates a 35% improvement over the 12 cm thruster in mass utilization efficiency. Since initial performance is found to be better than projected, a larger 50 cm thruster is already in the development stage.

Mining algorithm for association rules in big data based on Hadoop

NASA Astrophysics Data System (ADS)

Fu, Chunhua; Wang, Xiaojing; Zhang, Lijun; Qiao, Liying

2018-04-01

In order to solve the problem that the traditional association rules mining algorithm has been unable to meet the mining needs of large amount of data in the aspect of efficiency and scalability, take FP-Growth as an example, the algorithm is realized in the parallelization based on Hadoop framework and Map Reduce model. On the basis, it is improved using the transaction reduce method for further enhancement of the algorithm's mining efficiency. The experiment, which consists of verification of parallel mining results, comparison on efficiency between serials and parallel, variable relationship between mining time and node number and between mining time and data amount, is carried out in the mining results and efficiency by Hadoop clustering. Experiments show that the paralleled FP-Growth algorithm implemented is able to accurately mine frequent item sets, with a better performance and scalability. It can be better to meet the requirements of big data mining and efficiently mine frequent item sets and association rules from large dataset.

Scalable Management of Enterprise and Data-Center Networks

DTIC Science & Technology

2011-09-01

To the best of our knowledge , there is no systematic and efficient solution for handling overlapping wildcard rules in network-wide flow- management ...and D. Maltz, “Unraveling the complexity of network management ,” in NSDI, 2009. [4] P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan , “A...Scalable Management of Enterprise and Data-Center Networks Minlan Yu A Dissertation Presented to the Faculty of Princeton University in Candidacy for

Schottky solar cell using few-layered transition metal dichalcogenides toward large-scale fabrication of semitransparent and flexible power generator.

PubMed

Akama, Toshiki; Okita, Wakana; Nagai, Reito; Li, Chao; Kaneko, Toshiro; Kato, Toshiaki

2017-09-20

Few-layered transition metal dichalcogenides (TMDs) are known as true two-dimensional materials, with excellent semiconducting properties and strong light-matter interaction. Thus, TMDs are attractive materials for semitransparent and flexible solar cells for use in various applications. Hoewver, despite the recent progress, the development of a scalable method to fabricate semitransparent and flexible solar cells with mono- or few-layered TMDs remains a crucial challenge. Here, we show easy and scalable fabrication of a few-layered TMD solar cell using a Schottky-type configuration to obtain a power conversion efficiency (PCE) of approximately 0.7%, which is the highest value reported with few-layered TMDs. Clear power generation was also observed for a device fabricated on a large SiO 2 and flexible substrate, demonstrating that our method has high potential for scalable production. In addition, systematic investigation revealed that the PCE and external quantum efficiency (EQE) strongly depended on the type of photogenerated excitons (A, B, and C) because of different carrier dynamics. Because high solar cell performance along with excellent scalability can be achieved through the proposed process, our fabrication method will contribute to accelerating the industrial use of TMDs as semitransparent and flexible solar cells.

Scalability enhancement of AODV using local link repairing

NASA Astrophysics Data System (ADS)

Jain, Jyoti; Gupta, Roopam; Bandhopadhyay, T. K.

2014-09-01

Dynamic change in the topology of an ad hoc network makes it difficult to design an efficient routing protocol. Scalability of an ad hoc network is also one of the important criteria of research in this field. Most of the research works in ad hoc network focus on routing and medium access protocols and produce simulation results for limited-size networks. Ad hoc on-demand distance vector (AODV) is one of the best reactive routing protocols. In this article, modified routing protocols based on local link repairing of AODV are proposed. Method of finding alternate routes for next-to-next node is proposed in case of link failure. These protocols are beacon-less, means periodic hello message is removed from the basic AODV to improve scalability. Few control packet formats have been changed to accommodate suggested modification. Proposed protocols are simulated to investigate scalability performance and compared with basic AODV protocol. This also proves that local link repairing of proposed protocol improves scalability of the network. From simulation results, it is clear that scalability performance of routing protocol is improved because of link repairing method. We have tested protocols for different terrain area with approximate constant node densities and different traffic load.

Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak.

PubMed

Pearce, Madison E; Alikhan, Nabil-Fareed; Dallman, Timothy J; Zhou, Zhemin; Grant, Kathie; Maiden, Martin C J

2018-06-02

Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions. Copyright © 2018. Published by Elsevier B.V.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janjusic, Tommy; Kartsaklis, Christos

Memory scalability is an enduring problem and bottleneck that plagues many parallel codes. Parallel codes designed for High Performance Systems are typically designed over the span of several, and in some instances 10+, years. As a result, optimization practices which were appropriate for earlier systems may no longer be valid and thus require careful optimization consideration. Specifically, parallel codes whose memory footprint is a function of their scalability must be carefully considered for future exa-scale systems. In this paper we present a methodology and tool to study the memory scalability of parallel codes. Using our methodology we evaluate an applicationmore » s memory footprint as a function of scalability, which we coined memory efficiency, and describe our results. In particular, using our in-house tools we can pinpoint the specific application components which contribute to the application s overall memory foot-print (application data- structures, libraries, etc.).« less

celerite: Scalable 1D Gaussian Processes in C++, Python, and Julia

NASA Astrophysics Data System (ADS)

Foreman-Mackey, Daniel; Agol, Eric; Ambikasaran, Sivaram; Angus, Ruth

2017-09-01

celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.

Scalable load balancing for massively parallel distributed Monte Carlo particle transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, M. J.; Brantley, P. S.; Joy, K. I.

2013-07-01

In order to run computer simulations efficiently on massively parallel computers with hundreds of thousands or millions of processors, care must be taken that the calculation is load balanced across the processors. Examining the workload of every processor leads to an unscalable algorithm, with run time at least as large as O(N), where N is the number of processors. We present a scalable load balancing algorithm, with run time 0(log(N)), that involves iterated processor-pair-wise balancing steps, ultimately leading to a globally balanced workload. We demonstrate scalability of the algorithm up to 2 million processors on the Sequoia supercomputer at Lawrencemore » Livermore National Laboratory. (authors)« less

Medusa: A Scalable MR Console Using USB

PubMed Central

Stang, Pascal P.; Conolly, Steven M.; Santos, Juan M.; Pauly, John M.; Scott, Greig C.

2012-01-01

MRI pulse sequence consoles typically employ closed proprietary hardware, software, and interfaces, making difficult any adaptation for innovative experimental technology. Yet MRI systems research is trending to higher channel count receivers, transmitters, gradient/shims, and unique interfaces for interventional applications. Customized console designs are now feasible for researchers with modern electronic components, but high data rates, synchronization, scalability, and cost present important challenges. Implementing large multi-channel MR systems with efficiency and flexibility requires a scalable modular architecture. With Medusa, we propose an open system architecture using the Universal Serial Bus (USB) for scalability, combined with distributed processing and buffering to address the high data rates and strict synchronization required by multi-channel MRI. Medusa uses a modular design concept based on digital synthesizer, receiver, and gradient blocks, in conjunction with fast programmable logic for sampling and synchronization. Medusa is a form of synthetic instrument, being reconfigurable for a variety of medical/scientific instrumentation needs. The Medusa distributed architecture, scalability, and data bandwidth limits are presented, and its flexibility is demonstrated in a variety of novel MRI applications. PMID:21954200

A framework for scalable parameter estimation of gene circuit models using structural information.

PubMed

Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

2013-07-01

Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce

PubMed Central

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2016-01-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS – a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing. PMID:27617325

3D Kirchhoff depth migration algorithm: A new scalable approach for parallelization on multicore CPU based cluster

NASA Astrophysics Data System (ADS)

Rastogi, Richa; Londhe, Ashutosh; Srivastava, Abhishek; Sirasala, Kirannmayi M.; Khonde, Kiran

2017-03-01

In this article, a new scalable 3D Kirchhoff depth migration algorithm is presented on state of the art multicore CPU based cluster. Parallelization of 3D Kirchhoff depth migration is challenging due to its high demand of compute time, memory, storage and I/O along with the need of their effective management. The most resource intensive modules of the algorithm are traveltime calculations and migration summation which exhibit an inherent trade off between compute time and other resources. The parallelization strategy of the algorithm largely depends on the storage of calculated traveltimes and its feeding mechanism to the migration process. The presented work is an extension of our previous work, wherein a 3D Kirchhoff depth migration application for multicore CPU based parallel system had been developed. Recently, we have worked on improving parallel performance of this application by re-designing the parallelization approach. The new algorithm is capable to efficiently migrate both prestack and poststack 3D data. It exhibits flexibility for migrating large number of traces within the available node memory and with minimal requirement of storage, I/O and inter-node communication. The resultant application is tested using 3D Overthrust data on PARAM Yuva II, which is a Xeon E5-2670 based multicore CPU cluster with 16 cores/node and 64 GB shared memory. Parallel performance of the algorithm is studied using different numerical experiments and the scalability results show striking improvement over its previous version. An impressive 49.05X speedup with 76.64% efficiency is achieved for 3D prestack data and 32.00X speedup with 50.00% efficiency for 3D poststack data, using 64 nodes. The results also demonstrate the effectiveness and robustness of the improved algorithm with high scalability and efficiency on a multicore CPU cluster.

A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

PubMed

Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

2014-03-01

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor

PubMed Central

Holliday, Sarah; Ashraf, Raja Shahid; Wadsworth, Andrew; Baran, Derya; Yousaf, Syeda Amber; Nielsen, Christian B.; Tan, Ching-Hong; Dimitrov, Stoichko D.; Shang, Zhengrong; Gasparini, Nicola; Alamoudi, Maha; Laquai, Frédéric; Brabec, Christoph J.; Salleo, Alberto; Durrant, James R.; McCulloch, Iain

2016-01-01

Solution-processed organic photovoltaics (OPV) offer the attractive prospect of low-cost, light-weight and environmentally benign solar energy production. The highest efficiency OPV at present use low-bandgap donor polymers, many of which suffer from problems with stability and synthetic scalability. They also rely on fullerene-based acceptors, which themselves have issues with cost, stability and limited spectral absorption. Here we present a new non-fullerene acceptor that has been specifically designed to give improved performance alongside the wide bandgap donor poly(3-hexylthiophene), a polymer with significantly better prospects for commercial OPV due to its relative scalability and stability. Thanks to the well-matched optoelectronic and morphological properties of these materials, efficiencies of 6.4% are achieved which is the highest reported for fullerene-free P3HT devices. In addition, dramatically improved air stability is demonstrated relative to other high-efficiency OPV, showing the excellent potential of this new material combination for future technological applications. PMID:27279376

Scalable and efficient separation of hydrogen isotopes using graphene-based electrochemical pumping

NASA Astrophysics Data System (ADS)

Lozada-Hidalgo, M.; Zhang, S.; Hu, S.; Esfandiar, A.; Grigorieva, I. V.; Geim, A. K.

2017-05-01

Thousands of tons of isotopic mixtures are processed annually for heavy-water production and tritium decontamination. The existing technologies remain extremely energy intensive and require large capital investments. New approaches are needed to reduce the industry's footprint. Recently, micrometre-size crystals of graphene are shown to act as efficient sieves for hydrogen isotopes pumped through graphene electrochemically. Here we report a fully-scalable approach, using graphene obtained by chemical vapour deposition, which allows a proton-deuteron separation factor of around 8, despite cracks and imperfections. The energy consumption is projected to be orders of magnitude smaller with respect to existing technologies. A membrane based on 30 m2 of graphene, a readily accessible amount, could provide a heavy-water output comparable to that of modern plants. Even higher efficiency is expected for tritium separation. With no fundamental obstacles for scaling up, the technology's simplicity, efficiency and green credentials call for consideration by the nuclear and related industries.

The novel high-performance 3-D MT inverse solver

NASA Astrophysics Data System (ADS)

Kruglyakov, Mikhail; Geraskin, Alexey; Kuvshinov, Alexey

2016-04-01

We present novel, robust, scalable, and fast 3-D magnetotelluric (MT) inverse solver. The solver is written in multi-language paradigm to make it as efficient, readable and maintainable as possible. Separation of concerns and single responsibility concepts go through implementation of the solver. As a forward modelling engine a modern scalable solver extrEMe, based on contracting integral equation approach, is used. Iterative gradient-type (quasi-Newton) optimization scheme is invoked to search for (regularized) inverse problem solution, and adjoint source approach is used to calculate efficiently the gradient of the misfit. The inverse solver is able to deal with highly detailed and contrasting models, allows for working (separately or jointly) with any type of MT responses, and supports massive parallelization. Moreover, different parallelization strategies implemented in the code allow optimal usage of available computational resources for a given problem statement. To parameterize an inverse domain the so-called mask parameterization is implemented, which means that one can merge any subset of forward modelling cells in order to account for (usually) irregular distribution of observation sites. We report results of 3-D numerical experiments aimed at analysing the robustness, performance and scalability of the code. In particular, our computational experiments carried out at different platforms ranging from modern laptops to HPC Piz Daint (6th supercomputer in the world) demonstrate practically linear scalability of the code up to thousands of nodes.

Scalability improvements to NRLMOL for DFT calculations of large molecules

NASA Astrophysics Data System (ADS)

Diaz, Carlos Manuel

Advances in high performance computing (HPC) have provided a way to treat large, computationally demanding tasks using thousands of processors. With the development of more powerful HPC architectures, the need to create efficient and scalable code has grown more important. Electronic structure calculations are valuable in understanding experimental observations and are routinely used for new materials predictions. For the electronic structure calculations, the memory and computation time are proportional to the number of atoms. Memory requirements for these calculations scale as N2, where N is the number of atoms. While the recent advances in HPC offer platforms with large numbers of cores, the limited amount of memory available on a given node and poor scalability of the electronic structure code hinder their efficient usage of these platforms. This thesis will present some developments to overcome these bottlenecks in order to study large systems. These developments, which are implemented in the NRLMOL electronic structure code, involve the use of sparse matrix storage formats and the use of linear algebra using sparse and distributed matrices. These developments along with other related development now allow ground state density functional calculations using up to 25,000 basis functions and the excited state calculations using up to 17,000 basis functions while utilizing all cores on a node. An example on a light-harvesting triad molecule is described. Finally, future plans to further improve the scalability will be presented.

Scalable and expressive medical terminologies.

PubMed

Mays, E; Weida, R; Dionne, R; Laker, M; White, B; Liang, C; Oles, F J

1996-01-01

The K-Rep system, based on description logic, is used to represent and reason with large and expressive controlled medical terminologies. Expressive concept descriptions incorporate semantically precise definitions composed using logical operators, together with important non-semantic information such as synonyms and codes. Examples are drawn from our experience with K-Rep in modeling the InterMed laboratory terminology and also developing a large clinical terminology now in production use at Kaiser-Permanente. System-level scalability of performance is achieved through an object-oriented database system which efficiently maps persistent memory to virtual memory. Equally important is conceptual scalability-the ability to support collaborative development, organization, and visualization of a substantial terminology as it evolves over time. K-Rep addresses this need by logically completing concept definitions and automatically classifying concepts in a taxonomy via subsumption inferences. The K-Rep system includes a general-purpose GUI environment for terminology development and browsing, a custom interface for formulary term maintenance, a C+2 application program interface, and a distributed client-server mode which provides lightweight clients with efficient run-time access to K-Rep by means of a scripting language.

A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

NASA Astrophysics Data System (ADS)

Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2017-10-01

Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.

An efficient and scalable deformable model for virtual reality-based medical applications.

PubMed

Choi, Kup-Sze; Sun, Hanqiu; Heng, Pheng-Ann

2004-09-01

Modeling of tissue deformation is of great importance to virtual reality (VR)-based medical simulations. Considerable effort has been dedicated to the development of interactively deformable virtual tissues. In this paper, an efficient and scalable deformable model is presented for virtual-reality-based medical applications. It considers deformation as a localized force transmittal process which is governed by algorithms based on breadth-first search (BFS). The computational speed is scalable to facilitate real-time interaction by adjusting the penetration depth. Simulated annealing (SA) algorithms are developed to optimize the model parameters by using the reference data generated with the linear static finite element method (FEM). The mechanical behavior and timing performance of the model have been evaluated. The model has been applied to simulate the typical behavior of living tissues and anisotropic materials. Integration with a haptic device has also been achieved on a generic personal computer (PC) platform. The proposed technique provides a feasible solution for VR-based medical simulations and has the potential for multi-user collaborative work in virtual environment.

Recyclable organic solar cells on cellulose nanocrystal substrates

PubMed Central

Zhou, Yinhua; Fuentes-Hernandez, Canek; Khan, Talha M.; Liu, Jen-Chieh; Hsu, James; Shim, Jae Won; Dindar, Amir; Youngblood, Jeffrey P.; Moon, Robert J.; Kippelen, Bernard

2013-01-01

Solar energy is potentially the largest source of renewable energy at our disposal, but significant advances are required to make photovoltaic technologies economically viable and, from a life-cycle perspective, environmentally friendly, and consequently scalable. Cellulose nanomaterials are emerging high-value nanoparticles extracted from plants that are abundant, renewable, and sustainable. Here, we report on the first demonstration of efficient polymer solar cells fabricated on optically transparent cellulose nanocrystal (CNC) substrates. The solar cells fabricated on the CNC substrates display good rectification in the dark and reach a power conversion efficiency of 2.7%. In addition, we demonstrate that these solar cells can be easily separated and recycled into their major components using low-energy processes at room temperature, opening the door for a truly recyclable solar cell technology. Efficient and easily recyclable organic solar cells on CNC substrates are expected to be an attractive technology for sustainable, scalable, and environmentally-friendly energy production. PMID:23524333

Thermally efficient and highly scalable In2Se3 nanowire phase change memory

NASA Astrophysics Data System (ADS)

Jin, Bo; Kang, Daegun; Kim, Jungsik; Meyyappan, M.; Lee, Jeong-Soo

2013-04-01

The electrical characteristics of nonvolatile In2Se3 nanowire phase change memory are reported. Size-dependent memory switching behavior was observed in nanowires of varying diameters and the reduction in set/reset threshold voltage was as low as 3.45 V/6.25 V for a 60 nm nanowire, which is promising for highly scalable nanowire memory applications. Also, size-dependent thermal resistance of In2Se3 nanowire memory cells was estimated with values as high as 5.86×1013 and 1.04×106 K/W for a 60 nm nanowire memory cell in amorphous and crystalline phases, respectively. Such high thermal resistances are beneficial for improvement of thermal efficiency and thus reduction in programming power consumption based on Fourier's law. The evaluation of thermal resistance provides an avenue to develop thermally efficient memory cell architecture.

Deterministic binary vectors for efficient automated indexing of MEDLINE/PubMed abstracts.

PubMed

Wahle, Manuel; Widdows, Dominic; Herskovic, Jorge R; Bernstam, Elmer V; Cohen, Trevor

2012-01-01

The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI.

Deterministic Binary Vectors for Efficient Automated Indexing of MEDLINE/PubMed Abstracts

PubMed Central

Wahle, Manuel; Widdows, Dominic; Herskovic, Jorge R.; Bernstam, Elmer V.; Cohen, Trevor

2012-01-01

The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI. PMID:23304369

Recyclable organic solar cells on cellulose nanocrystal substrates.

PubMed

Zhou, Yinhua; Fuentes-Hernandez, Canek; Khan, Talha M; Liu, Jen-Chieh; Hsu, James; Shim, Jae Won; Dindar, Amir; Youngblood, Jeffrey P; Moon, Robert J; Kippelen, Bernard

2013-01-01

Solar energy is potentially the largest source of renewable energy at our disposal, but significant advances are required to make photovoltaic technologies economically viable and, from a life-cycle perspective, environmentally friendly, and consequently scalable. Cellulose nanomaterials are emerging high-value nanoparticles extracted from plants that are abundant, renewable, and sustainable. Here, we report on the first demonstration of efficient polymer solar cells fabricated on optically transparent cellulose nanocrystal (CNC) substrates. The solar cells fabricated on the CNC substrates display good rectification in the dark and reach a power conversion efficiency of 2.7%. In addition, we demonstrate that these solar cells can be easily separated and recycled into their major components using low-energy processes at room temperature, opening the door for a truly recyclable solar cell technology. Efficient and easily recyclable organic solar cells on CNC substrates are expected to be an attractive technology for sustainable, scalable, and environmentally-friendly energy production.

Hierarchical MFMO Circuit Modules for an Energy-Efficient SDR DBF

NASA Astrophysics Data System (ADS)

Mar, Jeich; Kuo, Chi-Cheng; Wu, Shin-Ru; Lin, You-Rong

The hierarchical multi-function matrix operation (MFMO) circuit modules are designed using coordinate rotations digital computer (CORDIC) algorithm for realizing the intensive computation of matrix operations. The paper emphasizes that the designed hierarchical MFMO circuit modules can be used to develop a power-efficient software-defined radio (SDR) digital beamformer (DBF). The formulas of the processing time for the scalable MFMO circuit modules implemented in field programmable gate array (FPGA) are derived to allocate the proper logic resources for the hardware reconfiguration. The hierarchical MFMO circuit modules are scalable to the changing number of array branches employed for the SDR DBF to achieve the purpose of power saving. The efficient reuse of the common MFMO circuit modules in the SDR DBF can also lead to energy reduction. Finally, the power dissipation and reconfiguration function in the different modes of the SDR DBF are observed from the experiment results.

Development of noSQL data storage for the ATLAS PanDA Monitoring System

NASA Astrophysics Data System (ADS)

Potekhin, M.; ATLAS Collaboration

2012-06-01

For several years the PanDA Workload Management System has been the basis for distributed production and analysis for the ATLAS experiment at the LHC. Since the start of data taking PanDA usage has ramped up steadily, typically exceeding 500k completed jobs/day by June 2011. The associated monitoring data volume has been rising as well, to levels that present a new set of challenges in the areas of database scalability and monitoring system performance and efficiency. These challenges are being met with a R&D effort aimed at implementing a scalable and efficient monitoring data storage based on a noSQL solution (Cassandra). We present our motivations for using this technology, as well as data design and the techniques used for efficient indexing of the data. We also discuss the hardware requirements as they were determined by testing with actual data and realistic loads.

Hamiltonian Monte Carlo acceleration using surrogate functions with random bases.

PubMed

Zhang, Cheng; Shahbaba, Babak; Zhao, Hongkai

2017-11-01

For big data analysis, high computational cost for Bayesian methods often limits their applications in practice. In recent years, there have been many attempts to improve computational efficiency of Bayesian inference. Here we propose an efficient and scalable computational technique for a state-of-the-art Markov chain Monte Carlo methods, namely, Hamiltonian Monte Carlo. The key idea is to explore and exploit the structure and regularity in parameter space for the underlying probabilistic model to construct an effective approximation of its geometric properties. To this end, we build a surrogate function to approximate the target distribution using properly chosen random bases and an efficient optimization process. The resulting method provides a flexible, scalable, and efficient sampling algorithm, which converges to the correct target distribution. We show that by choosing the basis functions and optimization process differently, our method can be related to other approaches for the construction of surrogate functions such as generalized additive models or Gaussian process models. Experiments based on simulated and real data show that our approach leads to substantially more efficient sampling algorithms compared to existing state-of-the-art methods.

Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics.

PubMed

Kelly, Benjamin J; Fitch, James R; Hu, Yangqiu; Corsmeier, Donald J; Zhong, Huachun; Wetzel, Amy N; Nordquist, Russell D; Newsom, David L; White, Peter

2015-01-20

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

Scalable, full-colour and controllable chromotropic plasmonic printing

PubMed Central

Xue, Jiancai; Zhou, Zhang-Kai; Wei, Zhiqiang; Su, Rongbin; Lai, Juan; Li, Juntao; Li, Chao; Zhang, Tengwei; Wang, Xue-Hua

2015-01-01

Plasmonic colour printing has drawn wide attention as a promising candidate for the next-generation colour-printing technology. However, an efficient approach to realize full colour and scalable fabrication is still lacking, which prevents plasmonic colour printing from practical applications. Here we present a scalable and full-colour plasmonic printing approach by combining conjugate twin-phase modulation with a plasmonic broadband absorber. More importantly, our approach also demonstrates controllable chromotropic capability, that is, the ability of reversible colour transformations. This chromotropic capability affords enormous potentials in building functionalized prints for anticounterfeiting, special label, and high-density data encryption storage. With such excellent performances in functional colour applications, this colour-printing approach could pave the way for plasmonic colour printing in real-world commercial utilization. PMID:26567803

Scalable, full-colour and controllable chromotropic plasmonic printing.

PubMed

Xue, Jiancai; Zhou, Zhang-Kai; Wei, Zhiqiang; Su, Rongbin; Lai, Juan; Li, Juntao; Li, Chao; Zhang, Tengwei; Wang, Xue-Hua

2015-11-16

Plasmonic colour printing has drawn wide attention as a promising candidate for the next-generation colour-printing technology. However, an efficient approach to realize full colour and scalable fabrication is still lacking, which prevents plasmonic colour printing from practical applications. Here we present a scalable and full-colour plasmonic printing approach by combining conjugate twin-phase modulation with a plasmonic broadband absorber. More importantly, our approach also demonstrates controllable chromotropic capability, that is, the ability of reversible colour transformations. This chromotropic capability affords enormous potentials in building functionalized prints for anticounterfeiting, special label, and high-density data encryption storage. With such excellent performances in functional colour applications, this colour-printing approach could pave the way for plasmonic colour printing in real-world commercial utilization.

Proxy-equation paradigm: A strategy for massively parallel asynchronous computations

NASA Astrophysics Data System (ADS)

Mittal, Ankita; Girimaji, Sharath

2017-09-01

Massively parallel simulations of transport equation systems call for a paradigm change in algorithm development to achieve efficient scalability. Traditional approaches require time synchronization of processing elements (PEs), which severely restricts scalability. Relaxing synchronization requirement introduces error and slows down convergence. In this paper, we propose and develop a novel "proxy equation" concept for a general transport equation that (i) tolerates asynchrony with minimal added error, (ii) preserves convergence order and thus, (iii) expected to scale efficiently on massively parallel machines. The central idea is to modify a priori the transport equation at the PE boundaries to offset asynchrony errors. Proof-of-concept computations are performed using a one-dimensional advection (convection) diffusion equation. The results demonstrate the promise and advantages of the present strategy.

Enhancement of Beaconless Location-Based Routing with Signal Strength Assistance for Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Chen, Guowei; Itoh, Kenichi; Sato, Takuro

Routing in Ad-hoc networks is unreliable due to the mobility of the nodes. Location-based routing protocols, unlike other protocols which rely on flooding, excel in network scalability. Furthermore, new location-based routing protocols, like, e. g. BLR [1], IGF [2], & CBF [3] have been proposed, with the feature of not requiring beacons in MAC-layer, which improve more in terms of scalability. Such beaconless routing protocols can work efficiently in dense network areas. However, these protocols' algorithms have no ability to avoid from routing into sparse areas. In this article, historical signal strength has been added as a factor into the BLR algorithm, which avoids routing into sparse area, and consequently improves the global routing efficiency.

Multipulse addressing of a Raman quantum memory: configurable beam splitting and efficient readout.

PubMed

Reim, K F; Nunn, J; Jin, X-M; Michelberger, P S; Champion, T F M; England, D G; Lee, K C; Kolthammer, W S; Langford, N K; Walmsley, I A

2012-06-29

Quantum memories are vital to the scalability of photonic quantum information processing (PQIP), since the storage of photons enables repeat-until-success strategies. On the other hand, the key element of all PQIP architectures is the beam splitter, which allows us to coherently couple optical modes. Here, we show how to combine these crucial functionalities by addressing a Raman quantum memory with multiple control pulses. The result is a coherent optical storage device with an extremely large time bandwidth product, that functions as an array of dynamically configurable beam splitters, and that can be read out with arbitrarily high efficiency. Networks of such devices would allow fully scalable PQIP, with applications in quantum computation, long distance quantum communications and quantum metrology.

Toxicology and Epidemiology: Improving the Science with a Framework for Combining Toxicological and Epidemiological Evidence to Establish Causal Inference

PubMed Central

Adami, Hans-Olov; Berry, Sir Colin L.; Breckenridge, Charles B.; Smith, Lewis L.; Swenberg, James A.; Trichopoulos, Dimitrios; Weiss, Noel S.; Pastoor, Timothy P.

2011-01-01

Historically, toxicology has played a significant role in verifying conclusions drawn on the basis of epidemiological findings. Agents that were suggested to have a role in human diseases have been tested in animals to firmly establish a causative link. Bacterial pathogens are perhaps the oldest examples, and tobacco smoke and lung cancer and asbestos and mesothelioma provide two more recent examples. With the advent of toxicity testing guidelines and protocols, toxicology took on a role that was intended to anticipate or predict potential adverse effects in humans, and epidemiology, in many cases, served a role in verifying or negating these toxicological predictions. The coupled role of epidemiology and toxicology in discerning human health effects by environmental agents is obvious, but there is currently no systematic and transparent way to bring the data and analysis of the two disciplines together in a way that provides a unified view on an adverse causal relationship between an agent and a disease. In working to advance the interaction between the fields of toxicology and epidemiology, we propose here a five-step “Epid-Tox” process that would focus on: (1) collection of all relevant studies, (2) assessment of their quality, (3) evaluation of the weight of evidence, (4) assignment of a scalable conclusion, and (5) placement on a causal relationship grid. The causal relationship grid provides a clear view of how epidemiological and toxicological data intersect, permits straightforward conclusions with regard to a causal relationship between agent and effect, and can show how additional data can influence conclusions of causality. PMID:21561883

Scalable Production Method for Graphene Oxide Water Vapor Separation Membranes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fifield, Leonard S.; Shin, Yongsoon; Liu, Wei

ABSTRACT Membranes for selective water vapor separation were assembled from graphene oxide suspension using techniques compatible with high volume industrial production. The large-diameter graphene oxide flake suspensions were synthesized from graphite materials via relatively efficient chemical oxidation steps with attention paid to maintaining flake size and achieving high graphene oxide concentrations. Graphene oxide membranes produced using scalable casting methods exhibited water vapor flux and water/nitrogen selectivity performance meeting or exceeding that of membranes produced using vacuum-assisted laboratory techniques. (PNNL-SA-117497)

Fully programmable and scalable optical switching fabric for petabyte data center.

PubMed

Zhu, Zhonghua; Zhong, Shan; Chen, Li; Chen, Kai

2015-02-09

We present a converged EPS and OCS switching fabric for data center networks (DCNs) based on a distributed optical switching architecture leveraging both WDM & SDM technologies. The architecture is topology adaptive, well suited to dynamic and diverse *-cast traffic patterns. Compared to a typical folded-Clos network, the new architecture is more readily scalable to future multi-Petabyte data centers with 1000 + racks while providing a higher link bandwidth, reducing transceiver count by 50%, and improving cabling efficiency by more than 90%.

Scalable, Stereocontrolled Total Syntheses of (±)–Axinellamines A and B

PubMed Central

Su, Shun; Rodriguez, Rodrigo A.; Baran, Phil S.

2011-01-01

The development of a simple, efficient, scalable, and stereocontrolled synthesis of a common intermediate en route to the axinellamines, massadines, and palau’amine is reported. This completely new route was utilized to prepare the axinellamines on a gram scale. In a more general sense, three distinct and enabling methodological advances were made during these studies: 1. ethylene glycol-assisted Pauson-Khand cycloaddition reaction, 2. a Zn/In-mediated Barbier type reaction, and 3. a TfNH2-assisted chlorination-spirocyclization. PMID:21846138

A Systems Approach to Scalable Transportation Network Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S

2006-01-01

Emerging needs in transportation network modeling and simulation are raising new challenges with respect to scal-ability of network size and vehicular traffic intensity, speed of simulation for simulation-based optimization, and fidel-ity of vehicular behavior for accurate capture of event phe-nomena. Parallel execution is warranted to sustain the re-quired detail, size and speed. However, few parallel simulators exist for such applications, partly due to the challenges underlying their development. Moreover, many simulators are based on time-stepped models, which can be computationally inefficient for the purposes of modeling evacuation traffic. Here an approach is presented to de-signing a simulator with memory andmore » speed efficiency as the goals from the outset, and, specifically, scalability via parallel execution. The design makes use of discrete event modeling techniques as well as parallel simulation meth-ods. Our simulator, called SCATTER, is being developed, incorporating such design considerations. Preliminary per-formance results are presented on benchmark road net-works, showing scalability to one million vehicles simu-lated on one processor.« less

Progress toward scalable tomography of quantum maps using twirling-based methods and information hierarchies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lopez, Cecilia C.; Theoretische Physik, Universitaet des Saarlandes, D-66041 Saarbruecken; Departament de Fisica, Universitat Autonoma de Barcelona, E-08193 Bellaterra

2010-06-15

We present in a unified manner the existing methods for scalable partial quantum process tomography. We focus on two main approaches: the one presented in Bendersky et al. [Phys. Rev. Lett. 100, 190403 (2008)] and the ones described, respectively, in Emerson et al. [Science 317, 1893 (2007)] and Lopez et al. [Phys. Rev. A 79, 042328 (2009)], which can be combined together. The methods share an essential feature: They are based on the idea that the tomography of a quantum map can be efficiently performed by studying certain properties of a twirling of such a map. From this perspective, inmore » this paper we present extensions, improvements, and comparative analyses of the scalable methods for partial quantum process tomography. We also clarify the significance of the extracted information, and we introduce interesting and useful properties of the {chi}-matrix representation of quantum maps that can be used to establish a clearer path toward achieving full tomography of quantum processes in a scalable way.« less

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

An O(N) and parallel approach to integral problems by a kernel-independent fast multipole method: Application to polarization and magnetization of interacting particles

NASA Astrophysics Data System (ADS)

Jiang, Xikai; Li, Jiyuan; Zhao, Xujun; Qin, Jian; Karpeev, Dmitry; Hernandez-Ortiz, Juan; de Pablo, Juan J.; Heinonen, Olle

2016-08-01

Large classes of materials systems in physics and engineering are governed by magnetic and electrostatic interactions. Continuum or mesoscale descriptions of such systems can be cast in terms of integral equations, whose direct computational evaluation requires O(N2) operations, where N is the number of unknowns. Such a scaling, which arises from the many-body nature of the relevant Green's function, has precluded wide-spread adoption of integral methods for solution of large-scale scientific and engineering problems. In this work, a parallel computational approach is presented that relies on using scalable open source libraries and utilizes a kernel-independent Fast Multipole Method (FMM) to evaluate the integrals in O(N) operations, with O(N) memory cost, thereby substantially improving the scalability and efficiency of computational integral methods. We demonstrate the accuracy, efficiency, and scalability of our approach in the context of two examples. In the first, we solve a boundary value problem for a ferroelectric/ferromagnetic volume in free space. In the second, we solve an electrostatic problem involving polarizable dielectric bodies in an unbounded dielectric medium. The results from these test cases show that our proposed parallel approach, which is built on a kernel-independent FMM, can enable highly efficient and accurate simulations and allow for considerable flexibility in a broad range of applications.

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

An O( N) and parallel approach to integral problems by a kernel-independent fast multipole method: Application to polarization and magnetization of interacting particles

DOE PAGES

Jiang, Xikai; Li, Jiyuan; Zhao, Xujun; ...

2016-08-10

Large classes of materials systems in physics and engineering are governed by magnetic and electrostatic interactions. Continuum or mesoscale descriptions of such systems can be cast in terms of integral equations, whose direct computational evaluation requires O( N 2) operations, where N is the number of unknowns. Such a scaling, which arises from the many-body nature of the relevant Green's function, has precluded wide-spread adoption of integral methods for solution of large-scale scientific and engineering problems. In this work, a parallel computational approach is presented that relies on using scalable open source libraries and utilizes a kernel-independent Fast Multipole Methodmore » (FMM) to evaluate the integrals in O( N) operations, with O( N) memory cost, thereby substantially improving the scalability and efficiency of computational integral methods. We demonstrate the accuracy, efficiency, and scalability of our approach in the context of two examples. In the first, we solve a boundary value problem for a ferroelectric/ferromagnetic volume in free space. In the second, we solve an electrostatic problem involving polarizable dielectric bodies in an unbounded dielectric medium. Lastly, the results from these test cases show that our proposed parallel approach, which is built on a kernel-independent FMM, can enable highly efficient and accurate simulations and allow for considerable flexibility in a broad range of applications.« less

A look at scalable dense linear algebra libraries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dongarra, J.J.; Van de Geijn, R.A.; Walker, D.W.

1992-01-01

We discuss the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object- oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization aremore » presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.« less

A look at scalable dense linear algebra libraries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dongarra, J.J.; Van de Geijn, R.A.; Walker, D.W.

1992-08-01

We discuss the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object- oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization aremore » presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.« less

DiPOLE: a scalable laser architecture for pumping multi-Hz PW systems

NASA Astrophysics Data System (ADS)

Ertel, Klaus; Banerjee, Saumyabrata; Mason, Paul D.; Phillips, P. Jonathan; Greenhalgh, R. Justin S.; Hernandez-Gomez, Cristina; Collier, John L.

2013-05-01

DiPOLE is a concept for a large aperture gas-cooled cryogenic multislab DPSSL amplifier based on ceramic Yb:YAG. It is designed to amplify ns-pulses at multi-Hz repetition rates and is scalable up the kJ-level. The concept was first tested on a small scale prototype which has so far produced 7.4 J at 10 Hz, with the aim of reaching 10 J at an optical-to-optical efficiency of 25 %. The design of an additional amplifier stage producing 100 J at 10 Hz is underway. When used to pump short-pulse Ti:S or OPCPA systems, PW peak power levels can be produced at repetition rates and efficiencies that lie orders of magnitude above what is achievable today.

High temperature semiconductor diode laser pumps for high energy laser applications

NASA Astrophysics Data System (ADS)

Campbell, Jenna; Semenic, Tadej; Guinn, Keith; Leisher, Paul O.; Bhunia, Avijit; Mashanovitch, Milan; Renner, Daniel

2018-02-01

Existing thermal management technologies for diode laser pumps place a significant load on the size, weight and power consumption of High Power Solid State and Fiber Laser systems, thus making current laser systems very large, heavy, and inefficient in many important practical applications. To mitigate this thermal management burden, it is desirable for diode pumps to operate efficiently at high heat sink temperatures. In this work, we have developed a scalable cooling architecture, based on jet-impingement technology with industrial coolant, for efficient cooling of diode laser bars. We have demonstrated 60% electrical-to-optical efficiency from a 9xx nm two-bar laser stack operating with propylene-glycolwater coolant, at 50 °C coolant temperature. To our knowledge, this is the highest efficiency achieved from a diode stack using 50 °C industrial fluid coolant. The output power is greater than 100 W per bar. Stacks with additional laser bars are currently in development, as this cooler architecture is scalable to a 1 kW system. This work will enable compact and robust fiber-coupled diode pump modules for high energy laser applications.

Facile and Scalable Fabrication of Highly Efficient Lead Iodide Perovskite Thin-Film Solar Cells in Air Using Gas Pump Method.

PubMed

Ding, Bin; Gao, Lili; Liang, Lusheng; Chu, Qianqian; Song, Xiaoxuan; Li, Yan; Yang, Guanjun; Fan, Bin; Wang, Mingkui; Li, Chengxin; Li, Changjiu

2016-08-10

Control of the perovskite film formation process to produce high-quality organic-inorganic metal halide perovskite thin films with uniform morphology, high surface coverage, and minimum pinholes is of great importance to highly efficient solar cells. Herein, we report on large-area light-absorbing perovskite films fabrication with a new facile and scalable gas pump method. By decreasing the total pressure in the evaporation environment, the gas pump method can significantly enhance the solvent evaporation rate by 8 times faster and thereby produce an extremely dense, uniform, and full-coverage perovskite thin film. The resulting planar perovskite solar cells can achieve an impressive power conversion efficiency up to 19.00% with an average efficiency of 17.38 ± 0.70% for 32 devices with an area of 5 × 2 mm, 13.91% for devices with a large area up to 1.13 cm(2). The perovskite films can be easily fabricated in air conditions with a relative humidity of 45-55%, which definitely has a promising prospect in industrial application of large-area perovskite solar panels.

An efficient and scalable pipeline for epitope tagging in mammalian stem cells using Cas9 ribonucleoprotein

PubMed Central

Dewari, Pooran Singh; Southgate, Benjamin; Mccarten, Katrina; Monogarov, German; O'Duibhir, Eoghan; Quinn, Niall; Tyrer, Ashley; Leitner, Marie-Christin; Plumb, Colin; Kalantzaki, Maria; Blin, Carla; Finch, Rebecca; Bressan, Raul Bardini; Morrison, Gillian; Jacobi, Ashley M; Behlke, Mark A; von Kriegsheim, Alex; Tomlinson, Simon; Krijgsveld, Jeroen

2018-01-01

CRISPR/Cas9 can be used for precise genetic knock-in of epitope tags into endogenous genes, simplifying experimental analysis of protein function. However, Cas9-assisted epitope tagging in primary mammalian cell cultures is often inefficient and reliant on plasmid-based selection strategies. Here, we demonstrate improved knock-in efficiencies of diverse tags (V5, 3XFLAG, Myc, HA) using co-delivery of Cas9 protein pre-complexed with two-part synthetic modified RNAs (annealed crRNA:tracrRNA) and single-stranded oligodeoxynucleotide (ssODN) repair templates. Knock-in efficiencies of ~5–30%, were achieved without selection in embryonic stem (ES) cells, neural stem (NS) cells, and brain-tumor-derived stem cells. Biallelic-tagged clonal lines were readily derived and used to define Olig2 chromatin-bound interacting partners. Using our novel web-based design tool, we established a 96-well format pipeline that enabled V5-tagging of 60 different transcription factors. This efficient, selection-free and scalable epitope tagging pipeline enables systematic surveys of protein expression levels, subcellular localization, and interactors across diverse mammalian stem cells. PMID:29638216

Nonepitaxial Thin-Film InP for Scalable and Efficient Photocathodes.

PubMed

Hettick, Mark; Zheng, Maxwell; Lin, Yongjing; Sutter-Fella, Carolin M; Ager, Joel W; Javey, Ali

2015-06-18

To date, some of the highest performance photocathodes of a photoelectrochemical (PEC) cell have been shown with single-crystalline p-type InP wafers, exhibiting half-cell solar-to-hydrogen conversion efficiencies of over 14%. However, the high cost of single-crystalline InP wafers may present a challenge for future large-scale industrial deployment. Analogous to solar cells, a thin-film approach could address the cost challenges by utilizing the benefits of the InP material while decreasing the use of expensive materials and processes. Here, we demonstrate this approach, using the newly developed thin-film vapor-liquid-solid (TF-VLS) nonepitaxial growth method combined with an atomic-layer deposition protection process to create thin-film InP photocathodes with large grain size and high performance, in the first reported solar device configuration generated by materials grown with this technique. Current-voltage measurements show a photocurrent (29.4 mA/cm(2)) and onset potential (630 mV) approaching single-crystalline wafers and an overall power conversion efficiency of 11.6%, making TF-VLS InP a promising photocathode for scalable and efficient solar hydrogen generation.

Managing Asthma in Low-Income, Underrepresented Minority, and Other Disadvantaged Pediatric Populations: Closing the Gap.

PubMed

Louisias, Margee; Phipatanakul, Wanda

2017-09-15

In this article, we review current understanding of the epidemiology and etiology of disparities in asthma. We also highlight current and emerging literature on solutions to tackle disparities while underscoring gaps and pressing future directions. Tailored, multicomponent approaches including the home, school, and clinician-based interventions show great promise. Managing asthma in disadvantaged populations can be challenging as they tend to have disproportionately worse outcomes due to a multitude of factors. However, multifaceted, innovative interventions that are sustainable and scalable are key to improving outcomes.

Scalable imprinting of shape-specific polymeric nanocarriers using a release layer of switchable water solubility.

PubMed

Agarwal, Rachit; Singh, Vikramjit; Jurney, Patrick; Shi, Li; Sreenivasan, S V; Roy, Krishnendu

2012-03-27

There is increasing interest in fabricating shape-specific polymeric nano- and microparticles for efficient delivery of drugs and imaging agents. The size and shape of these particles could significantly influence their transport properties and play an important role in in vivo biodistribution, targeting, and cellular uptake. Nanoimprint lithography methods, such as jet-and-flash imprint lithography (J-FIL), provide versatile top-down processes to fabricate shape-specific, biocompatible nanoscale hydrogels that can deliver therapeutic and diagnostic molecules in response to disease-specific cues. However, the key challenges in top-down fabrication of such nanocarriers are scalable imprinting with biological and biocompatible materials, ease of particle-surface modification using both aqueous and organic chemistry as well as simple yet biocompatible harvesting. Here we report that a biopolymer-based sacrificial release layer in combination with improved nanocarrier-material formulation can address these challenges. The sacrificial layer improves scalability and ease of imprint-surface modification due to its switchable solubility through simple ion exchange between monovalent and divalent cations. This process enables large-scale bionanoimprinting and efficient, one-step harvesting of hydrogel nanoparticles in both water- and organic-based imprint solutions. © 2012 American Chemical Society

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoginath, Srikanth B.; Perumalla, Kalyan S.

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a largemore » parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.« less

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

DOE PAGES

Yoginath, Srikanth B.; Perumalla, Kalyan S.

2018-01-31

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a largemore » parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.« less

A distributed-memory approximation algorithm for maximum weight perfect bipartite matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Buluc, Aydin; Li, Xiaoye S.

We design and implement an efficient parallel approximation algorithm for the problem of maximum weight perfect matching in bipartite graphs, i.e. the problem of finding a set of non-adjacent edges that covers all vertices and has maximum weight. This problem differs from the maximum weight matching problem, for which scalable approximation algorithms are known. It is primarily motivated by finding good pivots in scalable sparse direct solvers before factorization where sequential implementations of maximum weight perfect matching algorithms, such as those available in MC64, are widely used due to the lack of scalable alternatives. To overcome this limitation, we proposemore » a fully parallel distributed memory algorithm that first generates a perfect matching and then searches for weightaugmenting cycles of length four in parallel and iteratively augments the matching with a vertex disjoint set of such cycles. For most practical problems the weights of the perfect matchings generated by our algorithm are very close to the optimum. An efficient implementation of the algorithm scales up to 256 nodes (17,408 cores) on a Cray XC40 supercomputer and can solve instances that are too large to be handled by a single node using the sequential algorithm.« less

Scalable Coding of Plenoptic Images by Using a Sparse Set and Disparities.

PubMed

Li, Yun; Sjostrom, Marten; Olsson, Roger; Jennehag, Ulf

2016-01-01

One of the light field capturing techniques is the focused plenoptic capturing. By placing a microlens array in front of the photosensor, the focused plenoptic cameras capture both spatial and angular information of a scene in each microlens image and across microlens images. The capturing results in a significant amount of redundant information, and the captured image is usually of a large resolution. A coding scheme that removes the redundancy before coding can be of advantage for efficient compression, transmission, and rendering. In this paper, we propose a lossy coding scheme to efficiently represent plenoptic images. The format contains a sparse image set and its associated disparities. The reconstruction is performed by disparity-based interpolation and inpainting, and the reconstructed image is later employed as a prediction reference for the coding of the full plenoptic image. As an outcome of the representation, the proposed scheme inherits a scalable structure with three layers. The results show that plenoptic images are compressed efficiently with over 60 percent bit rate reduction compared with High Efficiency Video Coding intra coding, and with over 20 percent compared with an High Efficiency Video Coding block copying mode.

Manyscale Computing for Sensor Processing in Support of Space Situational Awareness

NASA Astrophysics Data System (ADS)

Schmalz, M.; Chapman, W.; Hayden, E.; Sahni, S.; Ranka, S.

2014-09-01

Increasing image and signal data burden associated with sensor data processing in support of space situational awareness implies continuing computational throughput growth beyond the petascale regime. In addition to growing applications data burden and diversity, the breadth, diversity and scalability of high performance computing architectures and their various organizations challenge the development of a single, unifying, practicable model of parallel computation. Therefore, models for scalable parallel processing have exploited architectural and structural idiosyncrasies, yielding potential misapplications when legacy programs are ported among such architectures. In response to this challenge, we have developed a concise, efficient computational paradigm and software called Manyscale Computing to facilitate efficient mapping of annotated application codes to heterogeneous parallel architectures. Our theory, algorithms, software, and experimental results support partitioning and scheduling of application codes for envisioned parallel architectures, in terms of work atoms that are mapped (for example) to threads or thread blocks on computational hardware. Because of the rigor, completeness, conciseness, and layered design of our manyscale approach, application-to-architecture mapping is feasible and scalable for architectures at petascales, exascales, and above. Further, our methodology is simple, relying primarily on a small set of primitive mapping operations and support routines that are readily implemented on modern parallel processors such as graphics processing units (GPUs) and hybrid multi-processors (HMPs). In this paper, we overview the opportunities and challenges of manyscale computing for image and signal processing in support of space situational awareness applications. We discuss applications in terms of a layered hardware architecture (laboratory > supercomputer > rack > processor > component hierarchy). Demonstration applications include performance analysis and results in terms of execution time as well as storage, power, and energy consumption for bus-connected and/or networked architectures. The feasibility of the manyscale paradigm is demonstrated by addressing four principal challenges: (1) architectural/structural diversity, parallelism, and locality, (2) masking of I/O and memory latencies, (3) scalability of design as well as implementation, and (4) efficient representation/expression of parallel applications. Examples will demonstrate how manyscale computing helps solve these challenges efficiently on real-world computing systems.

Scalable UWB photonic generator based on the combination of doublet pulses.

PubMed

Moreno, Vanessa; Rius, Manuel; Mora, José; Muriel, Miguel A; Capmany, José

2014-06-30

We propose and experimentally demonstrate a scalable and reconfigurable optical scheme to generate high order UWB pulses. Firstly, various ultra wideband doublets are created through a process of phase-to-intensity conversion by means of a phase modulation and a dispersive media. In a second stage, doublets are combined in an optical processing unit that allows the reconfiguration of UWB high order pulses. Experimental results both in time and frequency domains are presented showing good performance related to the fractional bandwidth and spectral efficiency parameters.

Design and evaluation of Nemesis, a scalable, low-latency, message-passing communication subsystem.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buntinas, D.; Mercier, G.; Gropp, W.

2005-12-02

This paper presents a new low-level communication subsystem called Nemesis. Nemesis has been designed and implemented to be scalable and efficient both in the intranode communication context using shared-memory and in the internode communication case using high-performance networks and is natively multimethod-enabled. Nemesis has been integrated in MPICH2 as a CH3 channel and delivers better performance than other dedicated communication channels in MPICH2. Furthermore, the resulting MPICH2 architecture outperforms other MPI implementations in point-to-point benchmarks.

Large Scale Frequent Pattern Mining using MPI One-Sided Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vishnu, Abhinav; Agarwal, Khushbu

In this paper, we propose a work-stealing runtime --- Library for Work Stealing LibWS --- using MPI one-sided model for designing scalable FP-Growth --- {\\em de facto} frequent pattern mining algorithm --- on large scale systems. LibWS provides locality efficient and highly scalable work-stealing techniques for load balancing on a variety of data distributions. We also propose a novel communication algorithm for FP-growth data exchange phase, which reduces the communication complexity from state-of-the-art O(p) to O(f + p/f) for p processes and f frequent attributed-ids. FP-Growth is implemented using LibWS and evaluated on several work distributions and support counts. Anmore » experimental evaluation of the FP-Growth on LibWS using 4096 processes on an InfiniBand Cluster demonstrates excellent efficiency for several work distributions (87\\% efficiency for Power-law and 91% for Poisson). The proposed distributed FP-Tree merging algorithm provides 38x communication speedup on 4096 cores.« less

A universal quantum information processor for scalable quantum communication and networks

PubMed Central

Yang, Xihua; Xue, Bolin; Zhang, Junxiang; Zhu, Shiyao

2014-01-01

Entanglement provides an essential resource for quantum computation, quantum communication, and quantum networks. How to conveniently and efficiently realize the generation, distribution, storage, retrieval, and control of multipartite entanglement is the basic requirement for realistic quantum information processing. Here, we present a theoretical proposal to efficiently and conveniently achieve a universal quantum information processor (QIP) via atomic coherence in an atomic ensemble. The atomic coherence, produced through electromagnetically induced transparency (EIT) in the Λ-type configuration, acts as the QIP and has full functions of quantum beam splitter, quantum frequency converter, quantum entangler, and quantum repeater. By employing EIT-based nondegenerate four-wave mixing processes, the generation, exchange, distribution, and manipulation of light-light, atom-light, and atom-atom multipartite entanglement can be efficiently and flexibly achieved in a deterministic way with only coherent light fields. This method greatly facilitates the operations in quantum information processing, and holds promising applications in realistic scalable quantum communication and quantum networks. PMID:25316514

On gate stack scalability of double-gate negative-capacitance FET with ferroelectric HfO2 for energy efficient sub-0.2 V operation

NASA Astrophysics Data System (ADS)

Jang, Kyungmin; Saraya, Takuya; Kobayashi, Masaharu; Hiramoto, Toshiro

2018-02-01

We have investigated the gate stack scalability and energy efficiency of double-gate negative-capacitance FET (DGNCFET) with a CMOS-compatible ferroelectric HfO2 (FE:HfO2). Analytic model-based simulation is conducted to investigate the impacts of ferroelectric characteristic of FE:HfO2 and gate stack thickness on the I on/I off ratio of DGNCFET. DGNCFET has wider design window for the gate stack where higher I on/I off ratio can be achieved than DG classical MOSFET. Under a process-induced constraint with sub-10 nm gate length (L g), FE:HfO2-based DGNCFET still has a design point for high I on/I off ratio. With an optimized gate stack thickness for sub-10 nm L g, FE:HfO2-based DGNCFET has 2.5× higher energy efficiency than DG classical MOSFET even at ultralow operation voltage of sub-0.2 V.

Scalable Robust Principal Component Analysis Using Grassmann Averages.

PubMed

Hauberg, Sren; Feragen, Aasa; Enficiaud, Raffi; Black, Michael J

2016-11-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA are not scalable. We note that in a zero-mean dataset, each observation spans a one-dimensional subspace, giving a point on the Grassmann manifold. We show that the average subspace corresponds to the leading principal component for Gaussian data. We provide a simple algorithm for computing this Grassmann Average ( GA), and show that the subspace estimate is less sensitive to outliers than PCA for general distributions. Because averages can be efficiently computed, we immediately gain scalability. We exploit robust averaging to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. The resulting Trimmed Grassmann Average ( TGA) is appropriate for computer vision because it is robust to pixel outliers. The algorithm has linear computational complexity and minimal memory requirements. We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie; a task beyond any current method. Source code is available online.

: A Scalable and Transparent System for Simulating MPI Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S

2010-01-01

is a scalable, transparent system for experimenting with the execution of parallel programs on simulated computing platforms. The level of simulated detail can be varied for application behavior as well as for machine characteristics. Unique features of are repeatability of execution, scalability to millions of simulated (virtual) MPI ranks, scalability to hundreds of thousands of host (real) MPI ranks, portability of the system to a variety of host supercomputing platforms, and the ability to experiment with scientific applications whose source-code is available. The set of source-code interfaces supported by is being expanded to support a wider set of applications, andmore » MPI-based scientific computing benchmarks are being ported. In proof-of-concept experiments, has been successfully exercised to spawn and sustain very large-scale executions of an MPI test program given in source code form. Low slowdowns are observed, due to its use of purely discrete event style of execution, and due to the scalability and efficiency of the underlying parallel discrete event simulation engine, sik. In the largest runs, has been executed on up to 216,000 cores of a Cray XT5 supercomputer, successfully simulating over 27 million virtual MPI ranks, each virtual rank containing its own thread context, and all ranks fully synchronized by virtual time.« less

A scalable parallel black oil simulator on distributed memory parallel computers

NASA Astrophysics Data System (ADS)

Wang, Kun; Liu, Hui; Chen, Zhangxin

2015-11-01

This paper presents our work on developing a parallel black oil simulator for distributed memory computers based on our in-house parallel platform. The parallel simulator is designed to overcome the performance issues of common simulators that are implemented for personal computers and workstations. The finite difference method is applied to discretize the black oil model. In addition, some advanced techniques are employed to strengthen the robustness and parallel scalability of the simulator, including an inexact Newton method, matrix decoupling methods, and algebraic multigrid methods. A new multi-stage preconditioner is proposed to accelerate the solution of linear systems from the Newton methods. Numerical experiments show that our simulator is scalable and efficient, and is capable of simulating extremely large-scale black oil problems with tens of millions of grid blocks using thousands of MPI processes on parallel computers.

Generation of scalable terahertz radiation from cylindrically focused two-color laser pulses in air

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuk, D.; Yoo, Y. J.; Rosenthal, E. W.

2016-03-21

We demonstrate scalable terahertz (THz) generation by focusing terawatt, two-color laser pulses in air with a cylindrical lens. This focusing geometry creates a two-dimensional air plasma sheet, which yields two diverging THz lobe profiles in the far field. This setup can avoid plasma-induced laser defocusing and subsequent THz saturation, previously observed with spherical lens focusing of high-power laser pulses. By expanding the plasma source into a two-dimensional sheet, cylindrical focusing can lead to scalable THz generation. This scheme provides an energy conversion efficiency of 7 × 10{sup −4}, ∼7 times better than spherical lens focusing. The diverging THz lobes are refocused withmore » a combination of cylindrical and parabolic mirrors to produce strong THz fields (>21 MV/cm) at the focal point.« less

Scalable isosurface visualization of massive datasets on commodity off-the-shelf clusters

PubMed Central

Bajaj, Chandrajit

2009-01-01

Tomographic imaging and computer simulations are increasingly yielding massive datasets. Interactive and exploratory visualizations have rapidly become indispensable tools to study large volumetric imaging and simulation data. Our scalable isosurface visualization framework on commodity off-the-shelf clusters is an end-to-end parallel and progressive platform, from initial data access to the final display. Interactive browsing of extracted isosurfaces is made possible by using parallel isosurface extraction, and rendering in conjunction with a new specialized piece of image compositing hardware called Metabuffer. In this paper, we focus on the back end scalability by introducing a fully parallel and out-of-core isosurface extraction algorithm. It achieves scalability by using both parallel and out-of-core processing and parallel disks. It statically partitions the volume data to parallel disks with a balanced workload spectrum, and builds I/O-optimal external interval trees to minimize the number of I/O operations of loading large data from disk. We also describe an isosurface compression scheme that is efficient for progress extraction, transmission and storage of isosurfaces. PMID:19756231

Scalable Domain Decomposed Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

O'Brien, Matthew Joseph

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.

Topochemical approach to efficiently produce main-chain poly(bile acid)s with high molecular weights.

PubMed

Li, Weina; Li, Xuesong; Zhu, Wei; Li, Changxu; Xu, Dan; Ju, Yong; Li, Guangtao

2011-07-21

Based on a topochemical approach, a strategy for efficiently producing main-chain poly(bile acid)s in the solid state was developed. This strategy allows for facile and scalable synthesis of main-chain poly(bile acid)s not only with high molecular weights, but also with quantitative conversions and yields.

A scalable diffraction-based scanning 3D colour video display as demonstrated by using tiled gratings and a vertical diffuser.

PubMed

Jia, Jia; Chen, Jhensi; Yao, Jun; Chu, Daping

2017-03-17

A high quality 3D display requires a high amount of optical information throughput, which needs an appropriate mechanism to distribute information in space uniformly and efficiently. This study proposes a front-viewing system which is capable of managing the required amount of information efficiently from a high bandwidth source and projecting 3D images with a decent size and a large viewing angle at video rate in full colour. It employs variable gratings to support a high bandwidth distribution. This concept is scalable and the system can be made compact in size. A horizontal parallax only (HPO) proof-of-concept system is demonstrated by projecting holographic images from a digital micro mirror device (DMD) through rotational tiled gratings before they are realised on a vertical diffuser for front-viewing.

Simplified Parallel Domain Traversal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson III, David J

2011-01-01

Many data-intensive scientific analysis techniques require global domain traversal, which over the years has been a bottleneck for efficient parallelization across distributed-memory architectures. Inspired by MapReduce and other simplified parallel programming approaches, we have designed DStep, a flexible system that greatly simplifies efficient parallelization of domain traversal techniques at scale. In order to deliver both simplicity to users as well as scalability on HPC platforms, we introduce a novel two-tiered communication architecture for managing and exploiting asynchronous communication loads. We also integrate our design with advanced parallel I/O techniques that operate directly on native simulation output. We demonstrate DStep bymore » performing teleconnection analysis across ensemble runs of terascale atmospheric CO{sub 2} and climate data, and we show scalability results on up to 65,536 IBM BlueGene/P cores.« less

Scalable randomized benchmarking of non-Clifford gates

NASA Astrophysics Data System (ADS)

Cross, Andrew; Magesan, Easwar; Bishop, Lev; Smolin, John; Gambetta, Jay

Randomized benchmarking is a widely used experimental technique to characterize the average error of quantum operations. Benchmarking procedures that scale to enable characterization of n-qubit circuits rely on efficient procedures for manipulating those circuits and, as such, have been limited to subgroups of the Clifford group. However, universal quantum computers require additional, non-Clifford gates to approximate arbitrary unitary transformations. We define a scalable randomized benchmarking procedure over n-qubit unitary matrices that correspond to protected non-Clifford gates for a class of stabilizer codes. We present efficient methods for representing and composing group elements, sampling them uniformly, and synthesizing corresponding poly (n) -sized circuits. The procedure provides experimental access to two independent parameters that together characterize the average gate fidelity of a group element. We acknowledge support from ARO under Contract W911NF-14-1-0124.

On-chip, photon-number-resolving, telecommunication-band detectors for scalable photonic information processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerrits, Thomas; Lita, Adriana E.; Calkins, Brice

Integration is currently the only feasible route toward scalable photonic quantum processing devices that are sufficiently complex to be genuinely useful in computing, metrology, and simulation. Embedded on-chip detection will be critical to such devices. We demonstrate an integrated photon-number-resolving detector, operating in the telecom band at 1550 nm, employing an evanescently coupled design that allows it to be placed at arbitrary locations within a planar circuit. Up to five photons are resolved in the guided optical mode via absorption from the evanescent field into a tungsten transition-edge sensor. The detection efficiency is 7.2{+-}0.5 %. The polarization sensitivity of themore » detector is also demonstrated. Detailed modeling of device designs shows a clear and feasible route to reaching high detection efficiencies.« less

Power Conservation through Energy Efficient Routing in Wireless Sensor Networks.

PubMed

Kandris, Dionisis; Tsioumas, Panagiotis; Tzes, Anthony; Nikolakopoulos, George; Vergados, Dimitrios D

2009-01-01

The power awareness issue is the primary concern within the domain of Wireless Sensor Networks (WSNs). Most power dissipation ocurrs during communication, thus routing protocols in WSNs mainly aim at power conservation. Moreover, a routing protocol should be scalable, so that its effectiveness does not degrade as the network size increases. In response to these issues, this work describes the development of an efficient routing protocol, named SHPER (Scaling Hierarchical Power Efficient Routing).

Scalable implementation of boson sampling with trapped ions.

PubMed

Shen, C; Zhang, Z; Duan, L-M

2014-02-07

Boson sampling solves a classically intractable problem by sampling from a probability distribution given by matrix permanents. We propose a scalable implementation of boson sampling using local transverse phonon modes of trapped ions to encode the bosons. The proposed scheme allows deterministic preparation and high-efficiency readout of the bosons in the Fock states and universal mode mixing. With the state-of-the-art trapped ion technology, it is feasible to realize boson sampling with tens of bosons by this scheme, which would outperform the most powerful classical computers and constitute an effective disproof of the famous extended Church-Turing thesis.

Extensions under development for the HEVC standard

NASA Astrophysics Data System (ADS)

Sullivan, Gary J.

2013-09-01

This paper discusses standardization activities for extending the capabilities of the High Efficiency Video Coding (HEVC) standard - the first edition of which was completed in early 2013. These near-term extensions are focused on three areas: range extensions (such as enhanced chroma formats, monochrome video, and increased bit depth), bitstream scalability extensions for spatial and fidelity scalability, and 3D video extensions (including stereoscopic/multi-view coding, and probably also depth map coding and combinations thereof). Standardization extensions on each of these topics will be completed by mid-2014, and further work beyond that timeframe is also discussed.

BCYCLIC: A parallel block tridiagonal matrix cyclic solver

NASA Astrophysics Data System (ADS)

Hirshman, S. P.; Perumalla, K. S.; Lynch, V. E.; Sanchez, R.

2010-09-01

A block tridiagonal matrix is factored with minimal fill-in using a cyclic reduction algorithm that is easily parallelized. Storage of the factored blocks allows the application of the inverse to multiple right-hand sides which may not be known at factorization time. Scalability with the number of block rows is achieved with cyclic reduction, while scalability with the block size is achieved using multithreaded routines (OpenMP, GotoBLAS) for block matrix manipulation. This dual scalability is a noteworthy feature of this new solver, as well as its ability to efficiently handle arbitrary (non-powers-of-2) block row and processor numbers. Comparison with a state-of-the art parallel sparse solver is presented. It is expected that this new solver will allow many physical applications to optimally use the parallel resources on current supercomputers. Example usage of the solver in magneto-hydrodynamic (MHD), three-dimensional equilibrium solvers for high-temperature fusion plasmas is cited.

High-speed and high-fidelity system and method for collecting network traffic

DOEpatents

Weigle, Eric H [Los Alamos, NM

2010-08-24

A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

Perspective: The future of quantum dot photonic integrated circuits

NASA Astrophysics Data System (ADS)

Norman, Justin C.; Jung, Daehwan; Wan, Yating; Bowers, John E.

2018-03-01

Direct epitaxial integration of III-V materials on Si offers substantial manufacturing cost and scalability advantages over heterogeneous integration. The challenge is that epitaxial growth introduces high densities of crystalline defects that limit device performance and lifetime. Quantum dot lasers, amplifiers, modulators, and photodetectors epitaxially grown on Si are showing promise for achieving low-cost, scalable integration with silicon photonics. The unique electrical confinement properties of quantum dots provide reduced sensitivity to the crystalline defects that result from III-V/Si growth, while their unique gain dynamics show promise for improved performance and new functionalities relative to their quantum well counterparts in many devices. Clear advantages for using quantum dot active layers for lasers and amplifiers on and off Si have already been demonstrated, and results for quantum dot based photodetectors and modulators look promising. Laser performance on Si is improving rapidly with continuous-wave threshold currents below 1 mA, injection efficiencies of 87%, and output powers of 175 mW at 20 °C. 1500-h reliability tests at 35 °C showed an extrapolated mean-time-to-failure of more than ten million hours. This represents a significant stride toward efficient, scalable, and reliable III-V lasers on on-axis Si substrates for photonic integrate circuits that are fully compatible with complementary metal-oxide-semiconductor (CMOS) foundries.

MOLAR: Modular Linux and Adaptive Runtime Support for HEC OS/R Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frank Mueller

2009-02-05

MOLAR is a multi-institution research effort that concentrates on adaptive, reliable,and efficient operating and runtime system solutions for ultra-scale high-end scientific computing on the next generation of supercomputers. This research addresses the challenges outlined by the FAST-OS - forum to address scalable technology for runtime and operating systems --- and HECRTF --- high-end computing revitalization task force --- activities by providing a modular Linux and adaptable runtime support for high-end computing operating and runtime systems. The MOLAR research has the following goals to address these issues. (1) Create a modular and configurable Linux system that allows customized changes based onmore » the requirements of the applications, runtime systems, and cluster management software. (2) Build runtime systems that leverage the OS modularity and configurability to improve efficiency, reliability, scalability, ease-of-use, and provide support to legacy and promising programming models. (3) Advance computer reliability, availability and serviceability (RAS) management systems to work cooperatively with the OS/R to identify and preemptively resolve system issues. (4) Explore the use of advanced monitoring and adaptation to improve application performance and predictability of system interruptions. The overall goal of the research conducted at NCSU is to develop scalable algorithms for high-availability without single points of failure and without single points of control.« less

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Energy-Efficient BOP-Based Beacon Transmission Scheduling in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Eui-Jik; Youm, Sungkwan; Choi, Hyo-Hyun

Many applications in wireless sensor networks (WSNs) require the energy efficiency and scalability. Although IEEE 802.15.4/Zigbee which is being considered as general technology for WSNs enables the low duty-cycling with time synchronization of all the nodes in network, it still suffer from its low scalability due to the beacon frame collision. Recently, various algorithms to resolve this problem are proposed. However, their manners to implement are somewhat ambiguous and the degradation of energy/communication efficiency is serious by the additional overhead. This paper describes an Energy-efficient BOP-based Beacon transmission Scheduling (EBBS) algorithm. EBBS is the centralized approach, in which a resource-sufficient node called as Topology Management Center (TMC) allocates the time slots to transmit a beacon frame to the nodes and manages the active/sleep schedules of them. We also propose EBBS with Adaptive BOPL (EBBS-AB), to adjust the duration to transmit beacon frames in every beacon interval, adaptively. Simulation results show that by using the proposed algorithm, the energy efficiency and the throughput of whole network can be significantly improved. EBBS-AB is also more effective for the network performance when the nodes are uniformly deployed on the sensor field rather than the case of random topologies.

Geometric Design of Scalable Forward Scatterers for Optimally Efficient Solar Transformers.

PubMed

Kim, Hye-Na; Vahidinia, Sanaz; Holt, Amanda L; Sweeney, Alison M; Yang, Shu

2017-11-01

It will be ideal to deliver equal, optimally efficient "doses" of sunlight to all cells in a photobioreactor system, while simultaneously utilizing the entire solar resource. Backed by the numerical scattering simulation and optimization, here, the design, synthesis, and characterization of the synthetic iridocytes that recapitulated the salient forward-scattering behavior of the Tridacnid clam system are reported, which presents the first geometric solution to allow narrow, precise forward redistribution of flux, utilizing the solar resource at the maximum quantum efficiency possible in living cells. The synthetic iridocytes are composed of silica nanoparticles in microspheres embedded in gelatin, both are low refractive index materials and inexpensive. They show wavelength selectivity, have little loss (the back-scattering intensity is reduced to less than ≈0.01% of the forward-scattered intensity), and narrow forward scattering cone similar to giant clams. Moreover, by comparing experiments and theoretical calculation, it is confirmed that the nonuniformity of the scatter sizes is a "feature not a bug" of the design, allowing for efficient, forward redistribution of solar flux in a micrometer-scaled paradigm. This method is environmentally benign, inexpensive, and scalable to produce optical components that will find uses in efficiency-limited solar conversion technologies, heat sinks, and biofuel production. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards a Cloud Based Smart Traffic Management Framework

NASA Astrophysics Data System (ADS)

Rahimi, M. M.; Hakimpour, F.

2017-09-01

Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

[Implementation of a community tele-epidemiological surveillance system using information and communication technologies in Paraguay].

PubMed

Galván, Pedro; Cane, Virgilio; Samudio, Margarita; Cabello, Agueda; Cabral, Margarita; Basogain, Xavier; Rivas, Ronald; Hilario, Enrique

2014-01-01

Report preliminary results of the application of the BONIS system in community tele-epidemiological surveillance in Paraguay. A study of viability and implementation carried out in the Family Health Unit located in Bañado Sur in the city of Asunción by the Paraguay River. The system automatically records personal data and symptoms of individuals who make telephone reports, and suspected cases of dengue are classified and prioritized. This information goes to community agents for follow-up and to specialists in charge of epidemiological surveillance. From April 2010 to August 2011, 1 028 calls to the system were logged. Of 157 reported cases of fever, home visits were made to 140 (89.2%); of these, fever and headache or body ache were confirmed in 52 (37.1%) cases, and headache or body ache without fever in 58 (41.4%) cases. Community agents referred 49 (35.0%) of them for medical consultation and blood tests, and they took blood samples in the homes of 19; of these, 56 (82.3%) were positive for dengue and 12 (17.4%) for influenza. Paraguay has a low-cost community tele-epidemiological surveillance system based on information and communication technologies and open-source software, which is scalable to other health symptoms and disorders of interest. To enable its acceptance and application, education programs should be developed to strengthen the management and promotion of community health.

3D-printed components for quantum devices.

PubMed

Saint, R; Evans, W; Zhou, Y; Barrett, T; Fromhold, T M; Saleh, E; Maskery, I; Tuck, C; Wildman, R; Oručević, F; Krüger, P

2018-05-30

Recent advances in the preparation, control and measurement of atomic gases have led to new insights into the quantum world and unprecedented metrological sensitivities, e.g. in measuring gravitational forces and magnetic fields. The full potential of applying such capabilities to areas as diverse as biomedical imaging, non-invasive underground mapping, and GPS-free navigation can only be realised with the scalable production of efficient, robust and portable devices. We introduce additive manufacturing as a production technique of quantum device components with unrivalled design freedom and rapid prototyping. This provides a step change in efficiency, compactness and facilitates systems integration. As a demonstrator we present an ultrahigh vacuum compatible ultracold atom source dissipating less than ten milliwatts of electrical power during field generation to produce large samples of cold rubidium gases. This disruptive technology opens the door to drastically improved integrated structures, which will further reduce size and assembly complexity in scalable series manufacture of bespoke portable quantum devices.

A Cluster-Based Framework for the Security of Medical Sensor Environments

NASA Astrophysics Data System (ADS)

Klaoudatou, Eleni; Konstantinou, Elisavet; Kambourakis, Georgios; Gritzalis, Stefanos

The adoption of Wireless Sensor Networks (WSNs) in the healthcare sector poses many security issues, mainly because medical information is considered particularly sensitive. The security mechanisms employed are expected to be more efficient in terms of energy consumption and scalability in order to cope with the constrained capabilities of WSNs and patients’ mobility. Towards this goal, cluster-based medical WSNs can substantially improve efficiency and scalability. In this context, we have proposed a general framework for cluster-based medical environments on top of which security mechanisms can rely. This framework fully covers the varying needs of both in-hospital environments and environments formed ad hoc for medical emergencies. In this paper, we further elaborate on the security of our proposed solution. We specifically focus on key establishment mechanisms and investigate the group key agreement protocols that can best fit in our framework.

Algorithmically scalable block preconditioner for fully implicit shallow-water equations in CAM-SE

DOE PAGES

Lott, P. Aaron; Woodward, Carol S.; Evans, Katherine J.

2014-10-19

Performing accurate and efficient numerical simulation of global atmospheric climate models is challenging due to the disparate length and time scales over which physical processes interact. Implicit solvers enable the physical system to be integrated with a time step commensurate with processes being studied. The dominant cost of an implicit time step is the ancillary linear system solves, so we have developed a preconditioner aimed at improving the efficiency of these linear system solves. Our preconditioner is based on an approximate block factorization of the linearized shallow-water equations and has been implemented within the spectral element dynamical core within themore » Community Atmospheric Model (CAM-SE). Furthermore, in this paper we discuss the development and scalability of the preconditioner for a suite of test cases with the implicit shallow-water solver within CAM-SE.« less

QML-AiNet: An immune network approach to learning qualitative differential equation models

PubMed Central

Pang, Wei; Coghill, George M.

2015-01-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG. PMID:25648212

Scalable Background-Limited Polarization-Sensitive Detectors for mm-wave Applications

NASA Technical Reports Server (NTRS)

Rostem, Karwan; Ali, Aamir; Appel, John W.; Bennett, Charles L.; Chuss, David T.; Colazo, Felipe A.; Crowe, Erik; Denis, Kevin L.; Essinger-Hileman, Tom; Marriage, Tobias A.;

QML-AiNet: An immune network approach to learning qualitative differential equation models.

PubMed

Pang, Wei; Coghill, George M

2015-02-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG.

A scalable diffraction-based scanning 3D colour video display as demonstrated by using tiled gratings and a vertical diffuser

PubMed Central

Jia, Jia; Chen, Jhensi; Yao, Jun; Chu, Daping

2017-01-01

A high quality 3D display requires a high amount of optical information throughput, which needs an appropriate mechanism to distribute information in space uniformly and efficiently. This study proposes a front-viewing system which is capable of managing the required amount of information efficiently from a high bandwidth source and projecting 3D images with a decent size and a large viewing angle at video rate in full colour. It employs variable gratings to support a high bandwidth distribution. This concept is scalable and the system can be made compact in size. A horizontal parallax only (HPO) proof-of-concept system is demonstrated by projecting holographic images from a digital micro mirror device (DMD) through rotational tiled gratings before they are realised on a vertical diffuser for front-viewing. PMID:28304371

Evaluating Discovery Services Architectures in the Context of the Internet of Things

NASA Astrophysics Data System (ADS)

Polytarchos, Elias; Eliakis, Stelios; Bochtis, Dimitris; Pramatari, Katerina

As the "Internet of Things" is expected to grow rapidly in the following years, the need to develop and deploy efficient and scalable Discovery Services in this context is very important for its success. Thus, the ability to evaluate and compare the performance of different Discovery Services architectures is vital if we want to allege that a given design is better at meeting requirements of a specific application. The purpose of this chapter is to provide a paradigm for the evaluation of different Discovery Services for the Internet of Things in terms of efficiency, scalability and performance through the use of simulations. The methodology presented uses the application of Discovery Services to a supply chain with the Service Lookup Service Discovery Service using OMNeT++, an open source network simulation suite. Then, we delve into the simulation design and the details of our findings.

Multi-Center Traffic Management Advisor Operational Field Test Results

NASA Technical Reports Server (NTRS)

Farley, Todd; Landry, Steven J.; Hoang, Ty; Nickelson, Monicarol; Levin, Kerry M.; Rowe, Dennis W.

2005-01-01

The Multi-Center Traffic Management Advisor (McTMA) is a research prototype system which seeks to bring time-based metering into the mainstream of air traffic control (ATC) operations. Time-based metering is an efficient alternative to traditional air traffic management techniques such as distance-based spacing (miles-in-trail spacing) and managed arrival reservoirs (airborne holding). While time-based metering has demonstrated significant benefit in terms of arrival throughput and arrival delay, its use to date has been limited to arrival operations at just nine airports nationally. Wide-scale adoption of time-based metering has been hampered, in part, by the limited scalability of metering automation. In order to realize the full spectrum of efficiency benefits possible with time-based metering, a much more modular, scalable time-based metering capability is required. With its distributed metering architecture, multi-center TMA offers such a capability.

Design and implementation of scalable tape archiver

NASA Technical Reports Server (NTRS)

Nemoto, Toshihiro; Kitsuregawa, Masaru; Takagi, Mikio

1996-01-01

In order to reduce costs, computer manufacturers try to use commodity parts as much as possible. Mainframes using proprietary processors are being replaced by high performance RISC microprocessor-based workstations, which are further being replaced by the commodity microprocessor used in personal computers. Highly reliable disks for mainframes are also being replaced by disk arrays, which are complexes of disk drives. In this paper we try to clarify the feasibility of a large scale tertiary storage system composed of 8-mm tape archivers utilizing robotics. In the near future, the 8-mm tape archiver will be widely used and become a commodity part, since recent rapid growth of multimedia applications requires much larger storage than disk drives can provide. We designed a scalable tape archiver which connects as many 8-mm tape archivers (element archivers) as possible. In the scalable archiver, robotics can exchange a cassette tape between two adjacent element archivers mechanically. Thus, we can build a large scalable archiver inexpensively. In addition, a sophisticated migration mechanism distributes frequently accessed tapes (hot tapes) evenly among all of the element archivers, which improves the throughput considerably. Even with the failures of some tape drives, the system dynamically redistributes hot tapes to the other element archivers which have live tape drives. Several kinds of specially tailored huge archivers are on the market, however, the 8-mm tape scalable archiver could replace them. To maintain high performance in spite of high access locality when a large number of archivers are attached to the scalable archiver, it is necessary to scatter frequently accessed cassettes among the element archivers and to use the tape drives efficiently. For this purpose, we introduce two cassette migration algorithms, foreground migration and background migration. Background migration transfers cassettes between element archivers to redistribute frequently accessed cassettes, thus balancing the load of each archiver. Background migration occurs the robotics are idle. Both migration algorithms are based on access frequency and space utility of each element archiver. To normalize these parameters according to the number of drives in each element archiver, it is possible to maintain high performance even if some tape drives fail. We found that the foreground migration is efficient at reducing access response time. Beside the foreground migration, the background migration makes it possible to track the transition of spatial access locality quickly.

Final Report from The University of Texas at Austin for DEGAS: Dynamic Global Address Space programming environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erez, Mattan; Yelick, Katherine; Sarkar, Vivek

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. Our approach is to provide an efficient and scalable programming model that can be adapted to application needs through the use of dynamic runtime features and domain-specific languages for computational kernels. We address the following technical challenges: Programmability: Rich set of programming constructs based on a Hierarchical Partitioned Global Address Space (HPGAS) model, demonstrated in UPC++. Scalability: Hierarchical locality control, lightweight communication (extended GASNet), and ef- ficient synchronization mechanisms (Phasers). Performance Portability:more » Just-in-time specialization (SEJITS) for generating hardware-specific code and scheduling libraries for domain-specific adaptive runtimes (Habanero). Energy Efficiency: Communication-optimal code generation to optimize energy efficiency by re- ducing data movement. Resilience: Containment Domains for flexible, domain-specific resilience, using state capture mechanisms and lightweight, asynchronous recovery mechanisms. Interoperability: Runtime and language interoperability with MPI and OpenMP to encourage broad adoption.« less

Perovskite ink with wide processing window for scalable high-efficiency solar cells

DOE PAGES

Yang, Mengjin; Li, Zhen; Reese, Matthew O.; ...

2017-03-20

Perovskite solar cells have made tremendous progress using laboratory-scale spin-coating methods in the past few years owing to advances in controls of perovskite film deposition. However, devices made via scalable methods are still lagging behind state-of-the-art spin-coated devices because of the complicated nature of perovskite crystallization from a precursor state. Here we demonstrate a chlorine-containing methylammonium lead iodide precursor formulation along with solvent tuning to enable a wide precursor-processing window (up to ~8 min) and a rapid grain growth rate (as short as ~1 min). Coupled with antisolvent extraction, this precursor ink delivers high-quality perovskite films with large-scale uniformity. Themore » ink can be used by both spin-coating and blade-coating methods with indistinguishable film morphology and device performance. Using a blade-coated absorber, devices with 0.12-cm 2 and 1.2-cm 2 areas yield average efficiencies of 18.55% and 17.33%, respectively. As a result, we further demonstrate a 12.6-cm 2 four-cell module (88% geometric fill factor) with 13.3% stabilized active-area efficiency output.« less

Thermal engineering of FAPbI3 perovskite material via radiative thermal annealing and in situ XRD

PubMed Central

Pool, Vanessa L.; Dou, Benjia; Van Campen, Douglas G.; Klein-Stockert, Talysa R.; Barnes, Frank S.; Shaheen, Sean E.; Ahmad, Md I.; van Hest, Maikel F. A. M.; Toney, Michael F.

2017-01-01

Lead halide perovskites have emerged as successful optoelectronic materials with high photovoltaic power conversion efficiencies and low material cost. However, substantial challenges remain in the scalability, stability and fundamental understanding of the materials. Here we present the application of radiative thermal annealing, an easily scalable processing method for synthesizing formamidinium lead iodide (FAPbI3) perovskite solar absorbers. Devices fabricated from films formed via radiative thermal annealing have equivalent efficiencies to those annealed using a conventional hotplate. By coupling results from in situ X-ray diffraction using a radiative thermal annealing system with device performances, we mapped the processing phase space of FAPbI3 and corresponding device efficiencies. Our map of processing-structure-performance space suggests the commonly used FAPbI3 annealing time, 10 min at 170 °C, can be significantly reduced to 40 s at 170 °C without affecting the photovoltaic performance. The Johnson-Mehl-Avrami model was used to determine the activation energy for decomposition of FAPbI3 into PbI2. PMID:28094249

Development of noSQL data storage for the ATLAS PanDA Monitoring System

NASA Astrophysics Data System (ADS)

Ito, H.; Potekhin, M.; Wenaus, T.

2012-12-01

For several years the PanDA Workload Management System has been the basis for distributed production and analysis for the ATLAS experiment at the LHC. Since the start of data taking PanDA usage has ramped up steadily, typically exceeding 500k completed jobs/day by June 2011. The associated monitoring data volume has been rising as well, to levels that present a new set of challenges in the areas of database scalability and monitoring system performance and efficiency. These challenges are being met with an R&D effort aimed at implementing a scalable and efficient monitoring data storage based on a noSQL solution (Cassandra). We present our motivations for using this technology, as well as data design and the techniques used for efficient indexing of the data. We also discuss the hardware requirements as they were determined by testing with actual data and realistic rate of queries. In conclusion, we present our experience with operating a Cassandra cluster over an extended period of time and with data load adequate for planned application.

Thermal engineering of FAPbI 3 perovskite material via radiative thermal annealing and in situ XRD

DOE PAGES

Pool, Vanessa L.; Dou, Benjia; Van Campen, Douglas G.; ...

2017-01-17

Lead halide perovskites have emerged as successful optoelectronic materials with high photovoltaic power conversion efficiencies and low material cost. However, substantial challenges remain in the scalability, stability and fundamental understanding of the materials. Here we present the application of radiative thermal annealing, an easily scalable processing method for synthesizing formamidinium lead iodide (FAPbI 3) perovskite solar absorbers. Devices fabricated from films formed via radiative thermal annealing have equivalent efficiencies to those annealed using a conventional hotplate. By coupling results from in situ X-ray diffraction using a radiative thermal annealing system with device performances, we mapped the processing phase space ofmore » FAPbI 3 and corresponding device efficiencies. Our map of processing-structure-performance space suggests the commonly used FAPbI 3 annealing time, 10 min at 170 degrees C, can be significantly reduced to 40 s at 170 degrees C without affecting the photovoltaic performance. Lastly, the Johnson-Mehl-Avrami model was used to determine the activation energy for decomposition of FAPbI 3 into PbI 2.« less

Perovskite ink with wide processing window for scalable high-efficiency solar cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Mengjin; Li, Zhen; Reese, Matthew O.

Perovskite solar cells have made tremendous progress using laboratory-scale spin-coating methods in the past few years owing to advances in controls of perovskite film deposition. However, devices made via scalable methods are still lagging behind state-of-the-art spin-coated devices because of the complicated nature of perovskite crystallization from a precursor state. Here we demonstrate a chlorine-containing methylammonium lead iodide precursor formulation along with solvent tuning to enable a wide precursor-processing window (up to ~8 min) and a rapid grain growth rate (as short as ~1 min). Coupled with antisolvent extraction, this precursor ink delivers high-quality perovskite films with large-scale uniformity. Themore » ink can be used by both spin-coating and blade-coating methods with indistinguishable film morphology and device performance. Using a blade-coated absorber, devices with 0.12-cm 2 and 1.2-cm 2 areas yield average efficiencies of 18.55% and 17.33%, respectively. As a result, we further demonstrate a 12.6-cm 2 four-cell module (88% geometric fill factor) with 13.3% stabilized active-area efficiency output.« less

Efficient and Scalable Cross-Matching of (Very) Large Catalogs

NASA Astrophysics Data System (ADS)

Pineau, F.-X.; Boch, T.; Derriere, S.

2011-07-01

Whether it be for building multi-wavelength datasets from independent surveys, studying changes in objects luminosities, or detecting moving objects (stellar proper motions, asteroids), cross-catalog matching is a technique widely used in astronomy. The need for efficient, reliable and scalable cross-catalog matching is becoming even more pressing with forthcoming projects which will produce huge catalogs in which astronomers will dig for rare objects, perform statistical analysis and classification, or real-time transients detection. We have developed a formalism and the corresponding technical framework to address the challenge of fast cross-catalog matching. Our formalism supports more than simple nearest-neighbor search, and handles elliptical positional errors. Scalability is improved by partitioning the sky using the HEALPix scheme, and processing independently each sky cell. The use of multi-threaded two-dimensional kd-trees adapted to managing equatorial coordinates enables efficient neighbor search. The whole process can run on a single computer, but could also use clusters of machines to cross-match future very large surveys such as GAIA or LSST in reasonable times. We already achieve performances where the 2MASS (˜470M sources) and SDSS DR7 (˜350M sources) can be matched on a single machine in less than 10 minutes. We aim at providing astronomers with a catalog cross-matching service, available on-line and leveraging on the catalogs present in the VizieR database. This service will allow users both to access pre-computed cross-matches across some very large catalogs, and to run customized cross-matching operations. It will also support VO protocols for synchronous or asynchronous queries.

From Field Notes to Data Portal - A Scalable Data QA/QC Framework for Tower Networks: Progress and Preliminary Results

NASA Astrophysics Data System (ADS)

Sturtevant, C.; Hackley, S.; Lee, R.; Holling, G.; Bonarrigo, S.

2017-12-01

Quality assurance and control (QA/QC) is one of the most important yet challenging aspects of producing research-quality data. Data quality issues are multi-faceted, including sensor malfunctions, unmet theoretical assumptions, and measurement interference from humans or the natural environment. Tower networks such as Ameriflux, ICOS, and NEON continue to grow in size and sophistication, yet tools for robust, efficient, scalable QA/QC have lagged. Quality control remains a largely manual process heavily relying on visual inspection of data. In addition, notes of measurement interference are often recorded on paper without an explicit pathway to data flagging. As such, an increase in network size requires a near-proportional increase in personnel devoted to QA/QC, quickly stressing the human resources available. We present a scalable QA/QC framework in development for NEON that combines the efficiency and standardization of automated checks with the power and flexibility of human review. This framework includes fast-response monitoring of sensor health, a mobile application for electronically recording maintenance activities, traditional point-based automated quality flagging, and continuous monitoring of quality outcomes and longer-term holistic evaluations. This framework maintains the traceability of quality information along the entirety of the data generation pipeline, and explicitly links field reports of measurement interference to quality flagging. Preliminary results show that data quality can be effectively monitored and managed for a multitude of sites with a small group of QA/QC staff. Several components of this framework are open-source, including a R-Shiny application for efficiently monitoring, synthesizing, and investigating data quality issues.

Bringing the CMS distributed computing system into scalable operations

NASA Astrophysics Data System (ADS)

Belforte, S.; Fanfani, A.; Fisk, I.; Flix, J.; Hernández, J. M.; Kress, T.; Letts, J.; Magini, N.; Miccio, V.; Sciabà, A.

2010-04-01

Establishing efficient and scalable operations of the CMS distributed computing system critically relies on the proper integration, commissioning and scale testing of the data and workload management tools, the various computing workflows and the underlying computing infrastructure, located at more than 50 computing centres worldwide and interconnected by the Worldwide LHC Computing Grid. Computing challenges periodically undertaken by CMS in the past years with increasing scale and complexity have revealed the need for a sustained effort on computing integration and commissioning activities. The Processing and Data Access (PADA) Task Force was established at the beginning of 2008 within the CMS Computing Program with the mandate of validating the infrastructure for organized processing and user analysis including the sites and the workload and data management tools, validating the distributed production system by performing functionality, reliability and scale tests, helping sites to commission, configure and optimize the networking and storage through scale testing data transfers and data processing, and improving the efficiency of accessing data across the CMS computing system from global transfers to local access. This contribution reports on the tools and procedures developed by CMS for computing commissioning and scale testing as well as the improvements accomplished towards efficient, reliable and scalable computing operations. The activities include the development and operation of load generators for job submission and data transfers with the aim of stressing the experiment and Grid data management and workload management systems, site commissioning procedures and tools to monitor and improve site availability and reliability, as well as activities targeted to the commissioning of the distributed production, user analysis and monitoring systems.

Scalable, cGMP-compatible purification of extracellular vesicles carrying bioactive human heterodimeric IL-15/lactadherin complexes

PubMed Central

Watson, Dionysios C.; Yung, Bryant C.; Bergamaschi, Cristina; Chowdhury, Bhabadeb; Bear, Jenifer; Stellas, Dimitris; Morales-Kastresana, Aizea; Jones, Jennifer C.; Felber, Barbara K.; Chen, Xiaoyuan; Pavlakis, George N.

2018-01-01

ABSTRACT The development of extracellular vesicles (EV) for therapeutic applications is contingent upon the establishment of reproducible, scalable, and high-throughput methods for the production and purification of clinical grade EV. Methods including ultracentrifugation (U/C), ultrafiltration, immunoprecipitation, and size-exclusion chromatography (SEC) have been employed to isolate EV, each facing limitations such as efficiency, particle purity, lengthy processing time, and/or sample volume. We developed a cGMP-compatible method for the scalable production, concentration, and isolation of EV through a strategy involving bioreactor culture, tangential flow filtration (TFF), and preparative SEC. We applied this purification method for the isolation of engineered EV carrying multiple complexes of a novel human immunostimulatory cytokine-fusion protein, heterodimeric IL-15 (hetIL-15)/lactadherin. HEK293 cells stably expressing the fusion cytokine were cultured in a hollow-fibre bioreactor. Conditioned medium was collected and EV were isolated comparing three procedures: U/C, SEC, or TFF + SEC. SEC demonstrated comparable particle recovery, size distribution, and hetIL-15 density as U/C purification. Relative to U/C, SEC preparations achieved a 100-fold reduction in ferritin concentration, a major protein-complex contaminant. Comparative proteomics suggested that SEC additionally decreased the abundance of cytoplasmic proteins not associated with EV. Combination of TFF and SEC allowed for bulk processing of large starting volumes, and resulted in bioactive EV, without significant loss in particle yield or changes in size, morphology, and hetIL-15/lactadherin density. Taken together, the combination of bioreactor culture with TFF + SEC comprises a scalable, efficient method for the production of highly purified, bioactive EV carrying hetIL-15/lactadherin, which may be useful in targeted cancer immunotherapy approaches. PMID:29535850

VPLS: an effective technology for building scalable transparent LAN services

NASA Astrophysics Data System (ADS)

Dong, Ximing; Yu, Shaohua

2005-02-01

Virtual Private LAN Service (VPLS) is generating considerable interest with enterprises and service providers as it offers multipoint transparent LAN service (TLS) over MPLS networks. This paper describes an effective technology - VPLS, which links virtual switch instances (VSIs) through MPLS to form an emulated Ethernet switch and build Scalable Transparent Lan Services. It first focuses on the architecture of VPLS with Ethernet bridging technique at the edge and MPLS at the core, then it tries to elucidate the data forwarding mechanism within VPLS domain, including learning and aging MAC addresses on a per LSP basis, flooding of unknown frames and replication for unknown, multicast, and broadcast frames. The loop-avoidance mechanism, known as split horizon forwarding, is also analyzed. Another important aspect of VPLS service is its basic operation, including autodiscovery and signaling, is discussed. From the perspective of efficiency and scalability the paper compares two important signaling mechanism, BGP and LDP, which are used to set up a PW between the PEs and bind the PWs to a particular VSI. With the extension of VPLS and the increase of full mesh of PWs between PE devices (n*(n-1)/2 PWs in all, a n2 complete problem), VPLS instance could have a large number of remote PE associations, resulting in an inefficient use of network bandwidth and system resources as the ingress PE has to replicate each frame and append MPLS labels for remote PE. So the latter part of this paper focuses on the scalability issue: the Hierarchical VPLS. Within the architecture of HVPLS, this paper addresses two ways to cope with a possibly large number of MAC addresses, which make VPLS operate more efficiently.

Scalable Active Optical Access Network Using Variable High-Speed PLZT Optical Switch/Splitter

NASA Astrophysics Data System (ADS)

Ashizawa, Kunitaka; Sato, Takehiro; Tokuhashi, Kazumasa; Ishii, Daisuke; Okamoto, Satoru; Yamanaka, Naoaki; Oki, Eiji

This paper proposes a scalable active optical access network using high-speed Plumbum Lanthanum Zirconate Titanate (PLZT) optical switch/splitter. The Active Optical Network, called ActiON, using PLZT switching technology has been presented to increase the number of subscribers and the maximum transmission distance, compared to the Passive Optical Network (PON). ActiON supports the multicast slot allocation realized by running the PLZT switch elements in the splitter mode, which forces the switch to behave as an optical splitter. However, the previous ActiON creates a tradeoff between the network scalability and the power loss experienced by the optical signal to each user. It does not use the optical power efficiently because the optical power is simply divided into 0.5 to 0.5 without considering transmission distance from OLT to each ONU. The proposed network adopts PLZT switch elements in the variable splitter mode, which controls the split ratio of the optical power considering the transmission distance from OLT to each ONU, in addition to PLZT switch elements in existing two modes, the switching mode and the splitter mode. The proposed network introduces the flexible multicast slot allocation according to the transmission distance from OLT to each user and the number of required users using three modes, while keeping the advantages of ActiON, which are to support scalable and secure access services. Numerical results show that the proposed network dramatically reduces the required number of slots and supports high bandwidth efficiency services and extends the coverage of access network, compared to the previous ActiON, and the required computation time for selecting multicast users is less than 30msec, which is acceptable for on-demand broadcast services.

Scalable splitting algorithms for big-data interferometric imaging in the SKA era

NASA Astrophysics Data System (ADS)

Onose, Alexandru; Carrillo, Rafael E.; Repetti, Audrey; McEwen, Jason D.; Thiran, Jean-Philippe; Pesquet, Jean-Christophe; Wiaux, Yves

2016-11-01

In the context of next-generation radio telescopes, like the Square Kilometre Array (SKA), the efficient processing of large-scale data sets is extremely important. Convex optimization tasks under the compressive sensing framework have recently emerged and provide both enhanced image reconstruction quality and scalability to increasingly larger data sets. We focus herein mainly on scalability and propose two new convex optimization algorithmic structures able to solve the convex optimization tasks arising in radio-interferometric imaging. They rely on proximal splitting and forward-backward iterations and can be seen, by analogy, with the CLEAN major-minor cycle, as running sophisticated CLEAN-like iterations in parallel in multiple data, prior, and image spaces. Both methods support any convex regularization function, in particular, the well-studied ℓ1 priors promoting image sparsity in an adequate domain. Tailored for big-data, they employ parallel and distributed computations to achieve scalability, in terms of memory and computational requirements. One of them also exploits randomization, over data blocks at each iteration, offering further flexibility. We present simulation results showing the feasibility of the proposed methods as well as their advantages compared to state-of-the-art algorithmic solvers. Our MATLAB code is available online on GitHub.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes.

PubMed

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme.

High Efficiency, 100 mJ per pulse, Nd:YAG Oscillator Optimized for Space-Based Earth and Planetary Remote Sensing

NASA Technical Reports Server (NTRS)

Coyle, D. Barry; Stysley, Paul R.; Poulios, Demetrios; Fredrickson, Robert M.; Kay, Richard B.; Cory, Kenneth C.

2014-01-01

We report on a newly solid state laser transmitter, designed and packaged for Earth and planetary space-based remote sensing applications for high efficiency, low part count, high pulse energy scalability/stability, and long life. Finally, we have completed a long term operational test which surpassed 2 Billion pulses with no measured decay in pulse energy.

Efficient generation of perfluoroalkyl radicals from sodium perfluoroalkanesulfinates and a hypervalent iodine(iii) reagent: mild, metal-free synthesis of perfluoroalkylated organic molecules.

PubMed

Sakamoto, Ryu; Kashiwagi, Hirotaka; Selvakumar, Sermadurai; Moteki, Shin A; Maruoka, Keiji

2016-07-06

This article describes an efficient method for the introduction of perfluoroalkyl groups into N-acrylamides, 2-isocyanides, olefins, and other heterocycles using perfluoroalkyl radicals that were generated from the reaction between sodium perfluoroalkanesulfinates and a hypervalent iodine(iii) reagent. This approach represents a simple, scalable perfluoroalkylation method under mild and metal-free conditions.

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

Cancer Epidemiology Data Repository (CEDR)

Cancer.gov

In an effort to broaden access and facilitate efficient data sharing, the Epidemiology and Genomics Research Program (EGRP) has created the Cancer Epidemiology Data Repository (CEDR), a centralized, controlled-access database, where Investigators can deposit individual-level de-identified observational cancer datasets.

Gossip-Based Broadcast

NASA Astrophysics Data System (ADS)

Leitão, João; Pereira, José; Rodrigues, Luís

Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives on large scale peer-to-peer networks. Epidemic protocols are scalable because they distribute the load among all nodes in the system and resilient because they have an intrinsic level of redundancy that masks node and network failures. This chapter provides an introduction to gossip-based broadcast on large-scale unstructured peer-to-peer overlay networks: it surveys the main results in the field, discusses techniques to build and maintain the overlays that support efficient dissemination strategies, and provides an in-depth discussion and experimental evaluation of two concrete protocols, named HyParView and Plumtree.

A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks

PubMed Central

Yin, Junming; Ho, Qirong; Xing, Eric P.

2014-01-01

We propose a scalable approach for making inference about latent spaces of large networks. With a succinct representation of networks as a bag of triangular motifs, a parsimonious statistical model, and an efficient stochastic variational inference algorithm, we are able to analyze real networks with over a million vertices and hundreds of latent roles on a single machine in a matter of hours, a setting that is out of reach for many existing methods. When compared to the state-of-the-art probabilistic approaches, our method is several orders of magnitude faster, with competitive or improved accuracy for latent space recovery and link prediction. PMID:25400487

Service-oriented workflow to efficiently and automatically fulfill products in a highly individualized web and mobile environment

NASA Astrophysics Data System (ADS)

Qiao, Mu

2015-03-01

Service Oriented Architecture1 (SOA) is widely used in building flexible and scalable web sites and services. In most of the web or mobile photo book and gifting business space, the products ordered are highly variable without a standard template that one can substitute texts or images from similar to that of commercial variable data printing. In this paper, the author describes a SOA workflow in a multi-sites, multi-product lines fulfillment system where three major challenges are addressed: utilization of hardware and equipment, highly automation with fault recovery, and highly scalable and flexible with order volume fluctuation.

Scalable nuclear density functional theory with Sky3D

NASA Astrophysics Data System (ADS)

Afibuzzaman, Md; Schuetrumpf, Bastian; Aktulga, Hasan Metin

2018-02-01

In nuclear astrophysics, quantum simulations of large inhomogeneous dense systems as they appear in the crusts of neutron stars present big challenges. The number of particles in a simulation with periodic boundary conditions is strongly limited due to the immense computational cost of the quantum methods. In this paper, we describe techniques for an efficient and scalable parallel implementation of Sky3D, a nuclear density functional theory solver that operates on an equidistant grid. Presented techniques allow Sky3D to achieve good scaling and high performance on a large number of cores, as demonstrated through detailed performance analysis on a Cray XC40 supercomputer.

A cost-effective high-throughput metabarcoding approach powerful enough to genotype ~44 000 year-old rodent remains from Northern Africa.

PubMed

Guimaraes, S; Pruvost, M; Daligault, J; Stoetzel, E; Bennett, E A; Côté, N M-L; Nicolas, V; Lalis, A; Denys, C; Geigl, E-M; Grange, T

2017-05-01

We present a cost-effective metabarcoding approach, aMPlex Torrent, which relies on an improved multiplex PCR adapted to highly degraded DNA, combining barcoding and next-generation sequencing to simultaneously analyse many heterogeneous samples. We demonstrate the strength of these improvements by generating a phylochronology through the genotyping of ancient rodent remains from a Moroccan cave whose stratigraphy covers the last 120 000 years. Rodents are important for epidemiology, agronomy and ecological investigations and can act as bioindicators for human- and/or climate-induced environmental changes. Efficient and reliable genotyping of ancient rodent remains has the potential to deliver valuable phylogenetic and paleoecological information. The analysis of multiple ancient skeletal remains of very small size with poor DNA preservation, however, requires a sensitive high-throughput method to generate sufficient data. We show this approach to be particularly adapted at accessing this otherwise difficult taxonomic and genetic resource. As a highly scalable, lower cost and less labour-intensive alternative to targeted sequence capture approaches, we propose the aMPlex Torrent strategy to be a useful tool for the genetic analysis of multiple degraded samples in studies involving ecology, archaeology, conservation and evolutionary biology. © 2016 John Wiley & Sons Ltd.

High-performance biocomputing for simulating the spread of contagion over large contact networks

PubMed Central

2012-01-01

Background Many important biological problems can be modeled as contagion diffusion processes over interaction networks. This article shows how the EpiSimdemics interaction-based simulation system can be applied to the general contagion diffusion problem. Two specific problems, computational epidemiology and human immune system modeling, are given as examples. We then show how the graphics processing unit (GPU) within each compute node of a cluster can effectively be used to speed-up the execution of these types of problems. Results We show that a single GPU can accelerate the EpiSimdemics computation kernel by a factor of 6 and the entire application by a factor of 3.3, compared to the execution time on a single core. When 8 CPU cores and 2 GPU devices are utilized, the speed-up of the computational kernel increases to 9.5. When combined with effective techniques for inter-node communication, excellent scalability can be achieved without significant loss of accuracy in the results. Conclusions We show that interaction-based simulation systems can be used to model disparate and highly relevant problems in biology. We also show that offloading some of the work to GPUs in distributed interaction-based simulations can be an effective way to achieve increased intra-node efficiency. PMID:22537298

Highly Flexible and Efficient Solar Steam Generation Device.

PubMed

Chen, Chaoji; Li, Yiju; Song, Jianwei; Yang, Zhi; Kuang, Yudi; Hitz, Emily; Jia, Chao; Gong, Amy; Jiang, Feng; Zhu, J Y; Yang, Bao; Xie, Jia; Hu, Liangbing

2017-08-01

Solar steam generation with subsequent steam recondensation has been regarded as one of the most promising techniques to utilize the abundant solar energy and sea water or other unpurified water through water purification, desalination, and distillation. Although tremendous efforts have been dedicated to developing high-efficiency solar steam generation devices, challenges remain in terms of the relatively low efficiency, complicated fabrications, high cost, and inability to scale up. Here, inspired by the water transpiration behavior of trees, the use of carbon nanotube (CNT)-modified flexible wood membrane (F-Wood/CNTs) is demonstrated as a flexible, portable, recyclable, and efficient solar steam generation device for low-cost and scalable solar steam generation applications. Benefitting from the unique structural merits of the F-Wood/CNTs membrane-a black CNT-coated hair-like surface with excellent light absorbability, wood matrix with low thermal conductivity, hierarchical micro- and nanochannels for water pumping and escaping, solar steam generation device based on the F-Wood/CNTs membrane demonstrates a high efficiency of 81% at 10 kW cm -2 , representing one of the highest values ever-reported. The nature-inspired design concept in this study is straightforward and easily scalable, representing one of the most promising solutions for renewable and portable solar energy generation and other related phase-change applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Surpassing 10% Efficiency Benchmark for Nonfullerene Organic Solar Cells by Scalable Coating in Air from Single Nonhalogenated Solvent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ye, Long; Xiong, Yuan; Zhang, Qianqian

The commercialization of nonfullerene organic solar cells (OSCs) relies critically on the response under typical operating conditions (for instance, temperature, humidity) and the ability of scale-up. Despite the rapid increase in power conversion efficiency (PCE) of spin-coated devices fabricated in a protective atmosphere, the device efficiencies of printed nonfullerene OSC devices by blade-coating are still lower than 6%. This slow progress significantly limits the practical printing of high-performance nonfullerene OSCs. Here, a new and stable nonfullerene combination was introduced by pairing a commercially available nonfluorinated acceptor IT-M with the polymeric donor FTAZ. Over 12%-efficiency can be achieved in spincoated FTAZ:IT-Mmore » devices using a single halogen-free solvent. More importantly, chlorinefree, in air blade-coating of FTAZ:IT-M is able to yield a PCE of nearly 11%, despite a humidity of ~50%. X-ray scattering results reveal that large π-π coherence lengths, high degree of faceon orientation with respect to the substrate, and small domain spacings of ~20 nm are closely correlated with such high device performance. Our material system and approach yields the highest reported performance for nonfullerene OSC devices by a coating technique approximating scalable fabrication methods and holds great promise for the development of low-cost, low-toxicity, and high-efficiency OSCs by high-throughput production.« less

Zinc oxide nanoleaves: A scalable disperser-assisted sonochemical approach for synthesis and an antibacterial application.

PubMed

Gupta, Anadi; Srivastava, Rohit

2018-03-01

Current study reports a new and highly scalable method for the synthesis of novel structure Zinc oxide nanoleaves (ZnO-NLs) using disperser-assisted sonochemical approach. The synthesis was carried out in different batches from 50mL to 1L to ensure the scalability of the method which produced almost similar results. The use of high speed (9000rpm) mechanical dispersion while bath sonication (200W, 33kHz) yield 4.4g of ZnO-NLs powder in 1L batch reaction within 2h (>96% yield). The ZnO-NLs shows an excellent thermal stability even at a higher temperature (900°C) and high surface area. The high antibacterial activity of ZnO-NLs against diseases causing Gram-positive bacteria Staphylococcus aureus shows a reduction in CFU, morphological changes like eight times reduction in cell size, cell burst, and cellular leakage at 200µg/mL concentration. This study provides an efficient, cost-effective and an environmental friendly approach for the synthesis of ZnO-NLs at industrial scale as well as new technique to increase the efficiency of the existing sonochemical method. We envisage that this method can be applied to various fields where ZnO is significantly consumed like rubber manufacturing, ceramic industry and medicine. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel high-fidelity realistic explosion damage simulation for urban environments

NASA Astrophysics Data System (ADS)

Liu, Xiaoqing; Yadegar, Jacob; Zhu, Youding; Raju, Chaitanya; Bhagavathula, Jaya

2010-04-01

Realistic building damage simulation has a significant impact in modern modeling and simulation systems especially in diverse panoply of military and civil applications where these simulation systems are widely used for personnel training, critical mission planning, disaster management, etc. Realistic building damage simulation should incorporate accurate physics-based explosion models, rubble generation, rubble flyout, and interactions between flying rubble and their surrounding entities. However, none of the existing building damage simulation systems sufficiently faithfully realize the criteria of realism required for effective military applications. In this paper, we present a novel physics-based high-fidelity and runtime efficient explosion simulation system to realistically simulate destruction to buildings. In the proposed system, a family of novel blast models is applied to accurately and realistically simulate explosions based on static and/or dynamic detonation conditions. The system also takes account of rubble pile formation and applies a generic and scalable multi-component based object representation to describe scene entities and highly scalable agent-subsumption architecture and scheduler to schedule clusters of sequential and parallel events. The proposed system utilizes a highly efficient and scalable tetrahedral decomposition approach to realistically simulate rubble formation. Experimental results demonstrate that the proposed system has the capability to realistically simulate rubble generation, rubble flyout and their primary and secondary impacts on surrounding objects including buildings, constructions, vehicles and pedestrians in clusters of sequential and parallel damage events.

Scalable High-Efficiency Thin Crystalline Silicon Photovoltaic Cells Enabled by Light-Trapping Nanostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Gang; Branham, Matthew S.; Hsu, Wei-Chun

2014-09-02

This report summarizes the research activities of the Chen group at MIT over the last two years pertaining to our research effort developing and proving light-trapping designs for ultrathin crystalline silicon solar cells. We present a new world record efficiency for a sub-20-micron crystalline silicon device, as well as details on the combined photonic/electronic transport simulation we developed for photovoltaic applications.

Wide-area technologies and services in the Trans-Pacific High Data Rate (HDR) satellite communications experiments

NASA Technical Reports Server (NTRS)

Hsu, E.; Hung, C.; Kadowaki, N.; Yoshimura, N.; Takahashi, T.; Shopbell, P.; Walker, G.; Wellnitz, D.; Gary, P.; Clark, G.;

Highly Efficient and Uniform 1 cm2 Perovskite Solar Cells with an Electrochemically Deposited NiOx Hole-Extraction Layer.

PubMed

Park, Ik Jae; Kang, Gyeongho; Park, Min Ah; Kim, Ju Seong; Seo, Se Won; Kim, Dong Hoe; Zhu, Kai; Park, Taiho; Kim, Jin Young

2017-06-22

Given that the highest certified conversion efficiency of the organic-inorganic perovskite solar cell (PSC) already exceeds 22 %, which is even higher than that of the polycrystalline silicon solar cell, the significance of new scalable processes that can be utilized for preparing large-area devices and their commercialization is rapidly increasing. From this perspective, the electrodeposition method is one of the most suitable processes for preparing large-area devices because it is an already commercialized process with proven controllability and scalability. Here, a highly uniform NiO x layer prepared by electrochemical deposition is reported as an efficient hole-extraction layer of a p-i-n-type planar PSC with a large active area of >1 cm 2 . It is demonstrated that the increased surface roughness of the NiO x layer, achieved by controlling the deposition current density, facilitates the hole extraction at the interface between perovskite and NiO x , and thus increases the fill factor and the conversion efficiency. The electrochemically deposited NiO x layer also exhibits extremely uniform thickness and morphology, leading to highly efficient and uniform large-area PSCs. As a result, the p-i-n-type planar PSC with an area of 1.084 cm 2 exhibits a stable conversion efficiency of 17.0 % (19.2 % for 0.1 cm 2 ) without showing hysteresis effects. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly Efficient and Uniform 1 cm 2 Perovskite Solar Cells with an Electrochemically Deposited NiO x Hole-Extraction Layer

DOE PAGES

Park, Ik Jae; Kang, Gyeongho; Park, Min Ah; ...

2017-05-10

Here, given that the highest certified conversion efficiency of the organic-inorganic perovskite solar cell (PSC) already exceeds 22%, which is even higher than that of the polycrystalline silicon solar cell, the significance of new scalable processes that can be utilized for preparing large-area devices and their commercialization is rapidly increasing. From this perspective, the electrodeposition method is one of the most suitable processes for preparing large-area devices because it is an already commercialized process with proven controllability and scalability. Here, a highly uniform NiO x layer prepared by electrochemical deposition is reported as an efficient hole-extraction layer of a p-i-n-typemore » planar PSC with a large active area of >1 cm 2. It is demonstrated that the increased surface roughness of the NiO x layer, achieved by controlling the deposition current density, facilitates the hole extraction at the interface between perovskite and NiO x, and thus increases the fill factor and the conversion efficiency. The electrochemically deposited NiO x layer also exhibits extremely uniform thickness and morphology, leading to highly efficient and uniform large-area PSCs. As a result, the p-i-n-type planar PSC with an area of 1.084 cm 2 exhibits a stable conversion efficiency of 17.0% (19.2% for 0.1 cm 2) without showing hysteresis effects.« less

Developing a scalable artificial photosynthesis technology through nanomaterials by design

NASA Astrophysics Data System (ADS)

Lewis, Nathan S.

2016-12-01

An artificial photosynthetic system that directly produces fuels from sunlight could provide an approach to scalable energy storage and a technology for the carbon-neutral production of high-energy-density transportation fuels. A variety of designs are currently being explored to create a viable artificial photosynthetic system, and the most technologically advanced systems are based on semiconducting photoelectrodes. Here, I discuss the development of an approach that is based on an architecture, first conceived around a decade ago, that combines arrays of semiconducting microwires with flexible polymeric membranes. I highlight the key steps that have been taken towards delivering a fully functional solar fuels generator, which have exploited advances in nanotechnology at all hierarchical levels of device construction, and include the discovery of earth-abundant electrocatalysts for fuel formation and materials for the stabilization of light absorbers. Finally, I consider the remaining scientific and engineering challenges facing the fulfilment of an artificial photosynthetic system that is simultaneously safe, robust, efficient and scalable.

SFT: Scalable Fault Tolerance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrini, Fabrizio; Nieplocha, Jarek; Tipparaju, Vinod

2006-04-15

In this paper we will present a new technology that we are currently developing within the SFT: Scalable Fault Tolerance FastOS project which seeks to implement fault tolerance at the operating system level. Major design goals include dynamic reallocation of resources to allow continuing execution in the presence of hardware failures, very high scalability, high efficiency (low overhead), and transparency—requiring no changes to user applications. Our technology is based on a global coordination mechanism, that enforces transparent recovery lines in the system, and TICK, a lightweight, incremental checkpointing software architecture implemented as a Linux kernel module. TICK is completely user-transparentmore » and does not require any changes to user code or system libraries; it is highly responsive: an interrupt, such as a timer interrupt, can trigger a checkpoint in as little as 2.5μs; and it supports incremental and full checkpoints with minimal overhead—less than 6% with full checkpointing to disk performed as frequently as once per minute.« less

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework

PubMed Central

2012-01-01

Background For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. Results We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. Conclusion The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources. PMID:23216909

Scalable quantum computing based on stationary spin qubits in coupled quantum dots inside double-sided optical microcavities

NASA Astrophysics Data System (ADS)

Wei, Hai-Rui; Deng, Fu-Guo

2014-12-01

Quantum logic gates are the key elements in quantum computing. Here we investigate the possibility of achieving a scalable and compact quantum computing based on stationary electron-spin qubits, by using the giant optical circular birefringence induced by quantum-dot spins in double-sided optical microcavities as a result of cavity quantum electrodynamics. We design the compact quantum circuits for implementing universal and deterministic quantum gates for electron-spin systems, including the two-qubit CNOT gate and the three-qubit Toffoli gate. They are compact and economic, and they do not require additional electron-spin qubits. Moreover, our devices have good scalability and are attractive as they both are based on solid-state quantum systems and the qubits are stationary. They are feasible with the current experimental technology, and both high fidelity and high efficiency can be achieved when the ratio of the side leakage to the cavity decay is low.

Scalable quantum computing based on stationary spin qubits in coupled quantum dots inside double-sided optical microcavities.

PubMed

Wei, Hai-Rui; Deng, Fu-Guo

2014-12-18

Quantum logic gates are the key elements in quantum computing. Here we investigate the possibility of achieving a scalable and compact quantum computing based on stationary electron-spin qubits, by using the giant optical circular birefringence induced by quantum-dot spins in double-sided optical microcavities as a result of cavity quantum electrodynamics. We design the compact quantum circuits for implementing universal and deterministic quantum gates for electron-spin systems, including the two-qubit CNOT gate and the three-qubit Toffoli gate. They are compact and economic, and they do not require additional electron-spin qubits. Moreover, our devices have good scalability and are attractive as they both are based on solid-state quantum systems and the qubits are stationary. They are feasible with the current experimental technology, and both high fidelity and high efficiency can be achieved when the ratio of the side leakage to the cavity decay is low.

Scalable real space pseudopotential density functional codes for materials in the exascale regime

NASA Astrophysics Data System (ADS)

Lena, Charles; Chelikowsky, James; Schofield, Grady; Biller, Ariel; Kronik, Leeor; Saad, Yousef; Deslippe, Jack

Real-space pseudopotential density functional theory has proven to be an efficient method for computing the properties of matter in many different states and geometries, including liquids, wires, slabs, and clusters with and without spin polarization. Fully self-consistent solutions using this approach have been routinely obtained for systems with thousands of atoms. Yet, there are many systems of notable larger sizes where quantum mechanical accuracy is desired, but scalability proves to be a hindrance. Such systems include large biological molecules, complex nanostructures, or mismatched interfaces. We will present an overview of our new massively parallel algorithms, which offer improved scalability in preparation for exascale supercomputing. We will illustrate these algorithms by considering the electronic structure of a Si nanocrystal exceeding 104 atoms. Support provided by the SciDAC program, Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences. Grant Numbers DE-SC0008877 (Austin) and DE-FG02-12ER4 (Berkeley).

SP-100 - The national space reactor power system program in response to future needs

NASA Astrophysics Data System (ADS)

Armijo, J. S.; Josloff, A. T.; Bailey, H. S.; Matteo, D. N.

The SP-100 system has been designed to meet comprehensive and demanding NASA/DOD/DOE requirements. The key requirements include: nuclear safety for all mission phases, scalability from 10's to 100's of kWe, reliable performance at full power for seven years of partial power for ten years, survivability in civil or military threat environments, capability to operate autonomously for up to six months, capability to protect payloads from excessive radiation, and compatibility with shuttle and expendable launch vehicles. The authors address of major progress in terms of design, flexibility/scalability, survivability, and development. These areas, with the exception of survivability, are discussed in detail. There has been significant improvement in the generic flight system design with substantial mass savings and simplification that enhance performance and reliability. Design activity has confirmed the scalability and flexibility of the system and the ability to efficiently meet NASA, AF, and SDIO needs. SP-100 development continues to make significant progress in all key technology areas.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

PubMed

Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

2012-12-05

For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes

PubMed Central

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme. PMID:28072851

Large-Scale Parallel Viscous Flow Computations using an Unstructured Multigrid Algorithm

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.

1999-01-01

The development and testing of a parallel unstructured agglomeration multigrid algorithm for steady-state aerodynamic flows is discussed. The agglomeration multigrid strategy uses a graph algorithm to construct the coarse multigrid levels from the given fine grid, similar to an algebraic multigrid approach, but operates directly on the non-linear system using the FAS (Full Approximation Scheme) approach. The scalability and convergence rate of the multigrid algorithm are examined on the SGI Origin 2000 and the Cray T3E. An argument is given which indicates that the asymptotic scalability of the multigrid algorithm should be similar to that of its underlying single grid smoothing scheme. For medium size problems involving several million grid points, near perfect scalability is obtained for the single grid algorithm, while only a slight drop-off in parallel efficiency is observed for the multigrid V- and W-cycles, using up to 128 processors on the SGI Origin 2000, and up to 512 processors on the Cray T3E. For a large problem using 25 million grid points, good scalability is observed for the multigrid algorithm using up to 1450 processors on a Cray T3E, even when the coarsest grid level contains fewer points than the total number of processors.

Reliable Radiation Hybrid Maps: An Efficient Scalable Clustering-based Approach

USDA-ARS?s Scientific Manuscript database

The process of mapping markers from radiation hybrid mapping (RHM) experiments is equivalent to the traveling salesman problem and, thereby, has combinatorial complexity. As an additional problem, experiments typically result in some unreliable markers that reduce the overall quality of the map. We ...

Binary Interval Search: a scalable algorithm for counting interval intersections.

PubMed

Layer, Ryan M; Skadron, Kevin; Robins, Gabriel; Hall, Ira M; Quinlan, Aaron R

2013-01-01

The comparison of diverse genomic datasets is fundamental to understand genome biology. Researchers must explore many large datasets of genome intervals (e.g. genes, sequence alignments) to place their experimental results in a broader context and to make new discoveries. Relationships between genomic datasets are typically measured by identifying intervals that intersect, that is, they overlap and thus share a common genome interval. Given the continued advances in DNA sequencing technologies, efficient methods for measuring statistically significant relationships between many sets of genomic features are crucial for future discovery. We introduce the Binary Interval Search (BITS) algorithm, a novel and scalable approach to interval set intersection. We demonstrate that BITS outperforms existing methods at counting interval intersections. Moreover, we show that BITS is intrinsically suited to parallel computing architectures, such as graphics processing units by illustrating its utility for efficient Monte Carlo simulations measuring the significance of relationships between sets of genomic intervals. https://github.com/arq5x/bits.

Percolator: Scalable Pattern Discovery in Dynamic Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhury, Sutanay; Purohit, Sumit; Lin, Peng

We demonstrate Percolator, a distributed system for graph pattern discovery in dynamic graphs. In contrast to conventional mining systems, Percolator advocates efficient pattern mining schemes that (1) support pattern detection with keywords; (2) integrate incremental and parallel pattern mining; and (3) support analytical queries such as trend analysis. The core idea of Percolator is to dynamically decide and verify a small fraction of patterns and their in- stances that must be inspected in response to buffered updates in dynamic graphs, with a total mining cost independent of graph size. We demonstrate a) the feasibility of incremental pattern mining by walkingmore » through each component of Percolator, b) the efficiency and scalability of Percolator over the sheer size of real-world dynamic graphs, and c) how the user-friendly GUI of Percolator inter- acts with users to support keyword-based queries that detect, browse and inspect trending patterns. We also demonstrate two user cases of Percolator, in social media trend analysis and academic collaboration analysis, respectively.« less

HACC: Extreme Scaling and Performance Across Diverse Architectures

NASA Astrophysics Data System (ADS)

Habib, Salman; Morozov, Vitali; Frontiere, Nicholas; Finkel, Hal; Pope, Adrian; Heitmann, Katrin

2013-11-01

Supercomputing is evolving towards hybrid and accelerator-based architectures with millions of cores. The HACC (Hardware/Hybrid Accelerated Cosmology Code) framework exploits this diverse landscape at the largest scales of problem size, obtaining high scalability and sustained performance. Developed to satisfy the science requirements of cosmological surveys, HACC melds particle and grid methods using a novel algorithmic structure that flexibly maps across architectures, including CPU/GPU, multi/many-core, and Blue Gene systems. We demonstrate the success of HACC on two very different machines, the CPU/GPU system Titan and the BG/Q systems Sequoia and Mira, attaining unprecedented levels of scalable performance. We demonstrate strong and weak scaling on Titan, obtaining up to 99.2% parallel efficiency, evolving 1.1 trillion particles. On Sequoia, we reach 13.94 PFlops (69.2% of peak) and 90% parallel efficiency on 1,572,864 cores, with 3.6 trillion particles, the largest cosmological benchmark yet performed. HACC design concepts are applicable to several other supercomputer applications.

Efficient collective influence maximization in cascading processes with first-order transitions

PubMed Central

Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

2017-01-01

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches. PMID:28349988

Isolation of Human Induced Pluripotent Stem Cell-Derived Dopaminergic Progenitors by Cell Sorting for Successful Transplantation

PubMed Central

Doi, Daisuke; Samata, Bumpei; Katsukawa, Mitsuko; Kikuchi, Tetsuhiro; Morizane, Asuka; Ono, Yuichi; Sekiguchi, Kiyotoshi; Nakagawa, Masato; Parmar, Malin; Takahashi, Jun

2014-01-01

Summary Human induced pluripotent stem cells (iPSCs) can provide a promising source of midbrain dopaminergic (DA) neurons for cell replacement therapy for Parkinson’s disease. However, iPSC-derived donor cells inevitably contain tumorigenic or inappropriate cells. Here, we show that human iPSC-derived DA progenitor cells can be efficiently isolated by cell sorting using a floor plate marker, CORIN. We induced DA neurons using scalable culture conditions on human laminin fragment, and the sorted CORIN+ cells expressed the midbrain DA progenitor markers, FOXA2 and LMX1A. When transplanted into 6-OHDA-lesioned rats, the CORIN+ cells survived and differentiated into midbrain DA neurons in vivo, resulting in significant improvement of the motor behavior, without tumor formation. In particular, the CORIN+ cells in a NURR1+ cell-dominant stage exhibited the best survival and function as DA neurons. Our method is a favorable strategy in terms of scalability, safety, and efficiency and may be advantageous for clinical application. PMID:24672756

Enhanced Condensation Heat Transfer On Patterned Surfaces

NASA Astrophysics Data System (ADS)

Alizadeh-Birjandi, Elaheh; Kavehpour, H. Pirouz

2017-11-01

Transition from film to drop wise condensation can improve the efficiency of thermal management applications and result in considerable savings in investments and operating costs by millions of dollars every year. The current methods available are either hydrophobic coating or nanostructured surfaces. The former has little adhesion to the structure which tends to detach easily under working conditions, the fabrication techniques of the latter are neither cost-effective nor scalable, and both are made with low thermal conductivity materials that would negate the heat transfer enhancement by drop wise condensation. Therefore, the existing technologies have limitations in enhancing vapor-to-liquid condensation. This work focuses on development of surfaces with wettability contrast to boost drop wise condensation, which its overall heat transfer efficiency is 2-3 times film wise condensation, while maintaining high conduction rate through the surface at low manufacturing costs. The variation in interfacial energy is achieved through crafting hydrophobic patterns to the surface of the metal via scalable fabrication techniques. The results of experimental and surface optimization studies are also presented.

Extreme-Scale Stochastic Particle Tracing for Uncertain Unsteady Flow Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Hanqi; He, Wenbin; Seo, Sangmin

2016-11-13

We present an efficient and scalable solution to estimate uncertain transport behaviors using stochastic flow maps (SFM,) for visualizing and analyzing uncertain unsteady flows. SFM computation is extremely expensive because it requires many Monte Carlo runs to trace densely seeded particles in the flow. We alleviate the computational cost by decoupling the time dependencies in SFMs so that we can process adjacent time steps independently and then compose them together for longer time periods. Adaptive refinement is also used to reduce the number of runs for each location. We then parallelize over tasks—packets of particles in our design—to achieve highmore » efficiency in MPI/thread hybrid programming. Such a task model also enables CPU/GPU coprocessing. We show the scalability on two supercomputers, Mira (up to 1M Blue Gene/Q cores) and Titan (up to 128K Opteron cores and 8K GPUs), that can trace billions of particles in seconds.« less

Efficient collective influence maximization in cascading processes with first-order transitions

NASA Astrophysics Data System (ADS)

Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

2017-03-01

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches.

A Distributed Approach to System-Level Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, Indranil

2012-01-01

Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component lifetimes that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative Jack of scalability and efficiency of typical prognostics approaches. In order to address these is ues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resul ting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion.

A novel modular ANN architecture for efficient monitoring of gases/odours in real-time

NASA Astrophysics Data System (ADS)

Mishra, A.; Rajput, N. S.

2018-04-01

Data pre-processing is tremendously used for enhanced classification of gases. However, it suppresses the concentration variances of different gas samples. A classical solution of using single artificial neural network (ANN) architecture is also inefficient and renders degraded quantification. In this paper, a novel modular ANN design has been proposed to provide an efficient and scalable solution in real–time. Here, two separate ANN blocks viz. classifier block and quantifier block have been used to provide efficient and scalable gas monitoring in real—time. The classifier ANN consists of two stages. In the first stage, the Net 1-NDSRT has been trained to transform raw sensor responses into corresponding virtual multi-sensor responses using normalized difference sensor response transformation (NDSRT). These responses have been fed to the second stage (i.e., Net 2-classifier ). The Net 2-classifier has been trained to classify various gas samples to their respective class. Further, the quantifier block has parallel ANN modules, multiplexed to quantify each gas. Therefore, the classifier ANN decides class and quantifier ANN decides the exact quantity of the gas/odor present in the respective sample of that class.

Efficient solar-to-fuels production from a hybrid microbial-water-splitting catalyst system.

PubMed

Torella, Joseph P; Gagliardi, Christopher J; Chen, Janice S; Bediako, D Kwabena; Colón, Brendan; Way, Jeffery C; Silver, Pamela A; Nocera, Daniel G

2015-02-24

Photovoltaic cells have considerable potential to satisfy future renewable-energy needs, but efficient and scalable methods of storing the intermittent electricity they produce are required for the large-scale implementation of solar energy. Current solar-to-fuels storage cycles based on water splitting produce hydrogen and oxygen, which are attractive fuels in principle but confront practical limitations from the current energy infrastructure that is based on liquid fuels. In this work, we report the development of a scalable, integrated bioelectrochemical system in which the bacterium Ralstonia eutropha is used to efficiently convert CO2, along with H2 and O2 produced from water splitting, into biomass and fusel alcohols. Water-splitting catalysis was performed using catalysts that are made of earth-abundant metals and enable low overpotential water splitting. In this integrated setup, equivalent solar-to-biomass yields of up to 3.2% of the thermodynamic maximum exceed that of most terrestrial plants. Moreover, engineering of R. eutropha enabled production of the fusel alcohol isopropanol at up to 216 mg/L, the highest bioelectrochemical fuel yield yet reported by >300%. This work demonstrates that catalysts of biotic and abiotic origin can be interfaced to achieve challenging chemical energy-to-fuels transformations.

A scalable and flexible hybrid energy storage system design and implementation

NASA Astrophysics Data System (ADS)

Kim, Younghyun; Koh, Jason; Xie, Qing; Wang, Yanzhi; Chang, Naehyuck; Pedram, Massoud

2014-06-01

Energy storage systems (ESS) are becoming one of the most important components that noticeably change overall system performance in various applications, ranging from the power grid infrastructure to electric vehicles (EV) and portable electronics. However, a homogeneous ESS is subject to limited characteristics in terms of cost, efficiency, lifetime, etc., by the energy storage technology that comprises the ESS. On the other hand, hybrid ESS (HESS) are a viable solution for a practical ESS with currently available technologies as they have potential to overcome such limitations by exploiting only advantages of heterogeneous energy storage technologies while hiding their drawbacks. However, the HESS concept basically mandates sophisticated design and control to actually make the benefits happen. The HESS architecture should be able to provide controllability of many parts, which are often fixed in homogeneous ESS, and novel management policies should be able to utilize the control features. This paper introduces a complete design practice of a HESS prototype to demonstrate scalability, flexibility, and energy efficiency. It is composed of three heterogenous energy storage elements: lead-acid batteries, lithium-ion batteries, and supercapacitors. We demonstrate a novel system control methodology and enhanced energy efficiency through this design practice.

Advanced Radioisotope Power Systems Segmented Thermoelectric Research

NASA Technical Reports Server (NTRS)

Caillat, Thierry

2004-01-01

Flight times are long; - Need power systems with >15 years life. Mass is at an absolute premium; - Need power systems with high specific power and scalability. 3 orders of magnitude reduction in solar irradiance from Earth to Pluto. Nuclear power sources preferable. The Overall objective is to develop low mass, high efficiency, low-cost Advanced Radioisotope Power System with double the Specific Power and Efficiency over state-of-the-art Radioisotope Thermoelectric Generators (RTGs).

Asynchronous Object Storage with QoS for Scientific and Commercial Big Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brim, Michael J; Dillow, David A; Oral, H Sarp

2013-01-01

This paper presents our design for an asynchronous object storage system intended for use in scientific and commercial big data workloads. Use cases from the target workload do- mains are used to motivate the key abstractions used in the application programming interface (API). The architecture of the Scalable Object Store (SOS), a prototype object stor- age system that supports the API s facilities, is presented. The SOS serves as a vehicle for future research into scalable and resilient big data object storage. We briefly review our research into providing efficient storage servers capable of providing quality of service (QoS) contractsmore » relevant for big data use cases.« less

Experimental Demonstration of a Self-organized Architecture for Emerging Grid Computing Applications on OBS Testbed

NASA Astrophysics Data System (ADS)

Liu, Lei; Hong, Xiaobin; Wu, Jian; Lin, Jintong

As Grid computing continues to gain popularity in the industry and research community, it also attracts more attention from the customer level. The large number of users and high frequency of job requests in the consumer market make it challenging. Clearly, all the current Client/Server(C/S)-based architecture will become unfeasible for supporting large-scale Grid applications due to its poor scalability and poor fault-tolerance. In this paper, based on our previous works [1, 2], a novel self-organized architecture to realize a highly scalable and flexible platform for Grids is proposed. Experimental results show that this architecture is suitable and efficient for consumer-oriented Grids.

Scalable pumping approach for extracting the maximum TEM(00) solar laser power.

PubMed

Liang, Dawei; Almeida, Joana; Vistas, Cláudia R

2014-10-20

A scalable TEM(00) solar laser pumping approach is composed of four pairs of first-stage Fresnel lens-folding mirror collectors, four fused-silica secondary concentrators with light guides of rectangular cross-section for radiation homogenization, four hollow two-dimensional compound parabolic concentrators for further concentration of uniform radiations from the light guides to a 3 mm diameter, 76 mm length Nd:YAG rod within four V-shaped pumping cavities. An asymmetric resonator ensures an efficient large-mode matching between pump light and oscillating laser light. Laser power of 59.1 W TEM(00) is calculated by ZEMAX and LASCAD numerical analysis, revealing 20 times improvement in brightness figure of merit.

COMPREHENSIVE PBPK MODELING APPROACH USING THE EXPOSURE RELATED DOSE ESTIMATING MODEL (ERDEM)

EPA Science Inventory

ERDEM, a complex PBPK modeling system, is the result of the implementation of a comprehensive PBPK modeling approach. ERDEM provides a scalable and user-friendly environment that enables researchers to focus on data input values rather than writing program code. It efficiently ...

Synthesis of chemicals using solar energy with stable photoelectrochemically active heterostructures.

PubMed

Mubeen, Syed; Singh, Nirala; Lee, Joun; Stucky, Galen D; Moskovits, Martin; McFarland, Eric W

2013-05-08

Efficient and cost-effective conversion of solar energy to useful chemicals and fuels could lead to a significant reduction in fossil hydrocarbon use. Artificial systems that use solar energy to produce chemicals have been reported for more than a century. However the most efficient devices demonstrated, based on traditionally fabricated compound semiconductors, have extremely short working lifetimes due to photocorrosion by the electrolyte. Here we report a stable, scalable design and molecular level fabrication strategy to create photoelectrochemically active heterostructure (PAH) units consisting of an efficient semiconductor light absorber in contact with oxidation and reduction electrocatalysts and otherwise protected by alumina. The functional heterostructures are fabricated by layer-by-layer, template-directed, electrochemical synthesis in porous anodic aluminum oxide membranes to produce high density arrays of electronically autonomous, nanostructured, corrosion resistant, photoactive units (~10(9)-10(10) PAHs per cm(2)). Each PAH unit is isolated from its neighbor by the transparent electrically insulating oxide cellular enclosure that makes the overall assembly fault tolerant. When illuminated with visible light, the free floating devices have been demonstrated to produce hydrogen at a stable rate for over 24 h in corrosive hydroiodic acid electrolyte with light as the only input. The quantum efficiency (averaged over the solar spectrum) for absorbed photons-to-hydrogen conversion was 7.4% and solar-to-hydrogen energy efficiency of incident light was 0.9%. The fabrication approach is scalable for commercial manufacturing and readily adaptable to a variety of earth abundant semiconductors which might otherwise be unstable as photoelectrocatalysts.

A novel multiple description scalable coding scheme for mobile wireless video transmission

NASA Astrophysics Data System (ADS)

Zheng, Haifeng; Yu, Lun; Chen, Chang Wen

2005-03-01

We proposed in this paper a novel multiple description scalable coding (MDSC) scheme based on in-band motion compensation temporal filtering (IBMCTF) technique in order to achieve high video coding performance and robust video transmission. The input video sequence is first split into equal-sized groups of frames (GOFs). Within a GOF, each frame is hierarchically decomposed by discrete wavelet transform. Since there is a direct relationship between wavelet coefficients and what they represent in the image content after wavelet decomposition, we are able to reorganize the spatial orientation trees to generate multiple bit-streams and employed SPIHT algorithm to achieve high coding efficiency. We have shown that multiple bit-stream transmission is very effective in combating error propagation in both Internet video streaming and mobile wireless video. Furthermore, we adopt the IBMCTF scheme to remove the redundancy for inter-frames along the temporal direction using motion compensated temporal filtering, thus high coding performance and flexible scalability can be provided in this scheme. In order to make compressed video resilient to channel error and to guarantee robust video transmission over mobile wireless channels, we add redundancy to each bit-stream and apply error concealment strategy for lost motion vectors. Unlike traditional multiple description schemes, the integration of these techniques enable us to generate more than two bit-streams that may be more appropriate for multiple antenna transmission of compressed video. Simulate results on standard video sequences have shown that the proposed scheme provides flexible tradeoff between coding efficiency and error resilience.

Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation.

PubMed

Yigzaw, Kassaye Yitbarek; Michalas, Antonis; Bellika, Johan Gustav

2017-01-03

Techniques have been developed to compute statistics on distributed datasets without revealing private information except the statistical results. However, duplicate records in a distributed dataset may lead to incorrect statistical results. Therefore, to increase the accuracy of the statistical analysis of a distributed dataset, secure deduplication is an important preprocessing step. We designed a secure protocol for the deduplication of horizontally partitioned datasets with deterministic record linkage algorithms. We provided a formal security analysis of the protocol in the presence of semi-honest adversaries. The protocol was implemented and deployed across three microbiology laboratories located in Norway, and we ran experiments on the datasets in which the number of records for each laboratory varied. Experiments were also performed on simulated microbiology datasets and data custodians connected through a local area network. The security analysis demonstrated that the protocol protects the privacy of individuals and data custodians under a semi-honest adversarial model. More precisely, the protocol remains secure with the collusion of up to N - 2 corrupt data custodians. The total runtime for the protocol scales linearly with the addition of data custodians and records. One million simulated records distributed across 20 data custodians were deduplicated within 45 s. The experimental results showed that the protocol is more efficient and scalable than previous protocols for the same problem. The proposed deduplication protocol is efficient and scalable for practical uses while protecting the privacy of patients and data custodians.

Design of Availability-Dependent Distributed Services in Large-Scale Uncooperative Settings

ERIC Educational Resources Information Center

Morales, Ramses Victor

2009-01-01

Thesis Statement: "Availability-dependent global predicates can be efficiently and scalably realized for a class of distributed services, in spite of specific selfish and colluding behaviors, using local and decentralized protocols". Several types of large-scale distributed systems spanning the Internet have to deal with availability variations…

A COMPREHENSIVE APPROACH FOR PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELS USING THE EXPOSURE RELATED DOSE ESTIMATING MODEL (ERDEM) SYSTEM

EPA Science Inventory

The implementation of a comprehensive PBPK modeling approach resulted in ERDEM, a complex PBPK modeling system. ERDEM provides a scalable and user-friendly environment that enables researchers to focus on data input values rather than writing program code. ERDEM efficiently m...

Application of induction heating in food processing and cooking: A Review

USDA-ARS?s Scientific Manuscript database

Induction heating is an electromagnetic heating technology that has several advantages such as high safety, scalability, and high energy efficiency. It has been applied for a long time in metal processing, medical applications, and cooking. However, the application of this technology in the food pro...

A scalable plant-resolving radiative transfer model based on optimized GPU ray tracing

USDA-ARS?s Scientific Manuscript database

A new model for radiative transfer in participating media and its application to complex plant canopies is presented. The goal was to be able to efficiently solve complex canopy-scale radiative transfer problems while also representing sub-plant heterogeneity. In the model, individual leaf surfaces ...

Polymorphous Computing Architectures

DTIC Science & Technology

2007-12-12

provide a multiprocessor implementation. In this work, we introduce the Atomos transactional programming language, which is the first to include...implicit transactions, strong atomicity, and a scalable multiprocessor implementation [47]. Atomos is derived from Java, but replaces its synchronization...and conditional waiting constructs with transactional alternatives. The Atomos conditional waiting proposal is tailored to allow efficient

DIRECT CONVERSION OF MUNICIPAL AND AGRICULTURAL WASTES TO BIODIESEL AND ETHANOL UTILIZING A UNIQUE EXTREMOPHILIC FUNGUS - PHASE I

EPA Science Inventory

Sustainable Bioproducts LLC’s proposed research will further develop an efficient, economical and scalable process for conversion of municipal solid wastes and agricultural wastes to biodiesel and ethanol. The technology is based on use of a novel extremophilic fun...

Improved Method for the Synthesis of β-Carbonyl Silyl-1,3-Dithianes by the Double Conjugate Addition of 1,3-Dithiol to Propargylic Carbonyl Compounds

PubMed Central

Mukherjee, Sumit; Kontokosta, Dimitra; Patil, Aditi; Rallapalli, Sivakumar; Lee, Daesung

2009-01-01

Base-mediated double conjugate addition of 1,3-propane dithiol to various silylated propargylic aldehydes and ketones allows for an efficient and scalable synthesis of β-carbonyl silyl-1,3-dithianes. PMID:19877611

Scalable Energy Efficiency with Resilience for High Performance Computing Systems: A Quantitative Methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, Li; Chen, Zizhong; Song, Shuaiwen

2016-01-18

Energy efficiency and resilience are two crucial challenges for HPC systems to reach exascale. While energy efficiency and resilience issues have been extensively studied individually, little has been done to understand the interplay between energy efficiency and resilience for HPC systems. Decreasing the supply voltage associated with a given operating frequency for processors and other CMOS-based components can significantly reduce power consumption. However, this often raises system failure rates and consequently increases application execution time. In this work, we present an energy saving undervolting approach that leverages the mainstream resilience techniques to tolerate the increased failures caused by undervolting.

Scalable Energy Efficiency with Resilience for High Performance Computing Systems: A Quantitative Methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, Li; Chen, Zizhong; Song, Shuaiwen Leon

2015-11-16

Energy efficiency and resilience are two crucial challenges for HPC systems to reach exascale. While energy efficiency and resilience issues have been extensively studied individually, little has been done to understand the interplay between energy efficiency and resilience for HPC systems. Decreasing the supply voltage associated with a given operating frequency for processors and other CMOS-based components can significantly reduce power consumption. However, this often raises system failure rates and consequently increases application execution time. In this work, we present an energy saving undervolting approach that leverages the mainstream resilience techniques to tolerate the increased failures caused by undervolting.

Particulate Photocatalyst Sheets Based on Carbon Conductor Layer for Efficient Z-Scheme Pure-Water Splitting at Ambient Pressure.

PubMed

Wang, Qian; Hisatomi, Takashi; Suzuki, Yohichi; Pan, Zhenhua; Seo, Jeongsuk; Katayama, Masao; Minegishi, Tsutomu; Nishiyama, Hiroshi; Takata, Tsuyoshi; Seki, Kazuhiko; Kudo, Akihiko; Yamada, Taro; Domen, Kazunari

2017-02-01

Development of sunlight-driven water splitting systems with high efficiency, scalability, and cost-competitiveness is a central issue for mass production of solar hydrogen as a renewable and storable energy carrier. Photocatalyst sheets comprising a particulate hydrogen evolution photocatalyst (HEP) and an oxygen evolution photocatalyst (OEP) embedded in a conductive thin film can realize efficient and scalable solar hydrogen production using Z-scheme water splitting. However, the use of expensive precious metal thin films that also promote reverse reactions is a major obstacle to developing a cost-effective process at ambient pressure. In this study, we present a standalone particulate photocatalyst sheet based on an earth-abundant, relatively inert, and conductive carbon film for efficient Z-scheme water splitting at ambient pressure. A SrTiO 3 :La,Rh/C/BiVO 4 :Mo sheet is shown to achieve unassisted pure-water (pH 6.8) splitting with a solar-to-hydrogen energy conversion efficiency (STH) of 1.2% at 331 K and 10 kPa, while retaining 80% of this efficiency at 91 kPa. The STH value of 1.0% is the highest among Z-scheme pure water splitting operating at ambient pressure. The working mechanism of the photocatalyst sheet is discussed on the basis of band diagram simulation. In addition, the photocatalyst sheet split pure water more efficiently than conventional powder suspension systems and photoelectrochemical parallel cells because H + and OH - concentration overpotentials and an IR drop between the HEP and OEP were effectively suppressed. The proposed carbon-based photocatalyst sheet, which can be used at ambient pressure, is an important alternative to (photo)electrochemical systems for practical solar hydrogen production.

Report of the workshop on evidence-based design of national wildlife health programs

USGS Publications Warehouse

Nguyen, Natalie T.; Duff, J. Paul; Gavier-Widén, Dolores; Grillo, Tiggy; He, Hongxuan; Lee, Hang; Ratanakorn, Parntep; Rijks, Jolianne M.; Ryser-Degiorgis, Marie-Pierre; Sleeman, Jonathan M.; Stephen, Craig; Tana, Toni; Uhart, Marcela; Zimmer , Patrick

2017-05-08

SummaryThis report summarizes a Wildlife Disease Association sponsored workshop held in 2016. The overall objective of the workshop was to use available evidence and selected subject matter expertise to define the essential functions of a National Wildlife Health Program and the resources needed to deliver a robust and reliable program, including the basic infrastructure, workforce, data and information systems, governance, organizational capacity, and essential features, such as wildlife disease surveillance, diagnostic services, and epidemiological investigation. This workshop also provided the means to begin the process of defining the essential attributes of a national wildlife health program that could be scalable and adaptable to each nation’s needs.

Microbially derived biosensors for diagnosis, monitoring and epidemiology.

PubMed

Chang, Hung-Ju; Voyvodic, Peter L; Zúñiga, Ana; Bonnet, Jérôme

2017-09-01

Living cells have evolved to detect and process various signals and can self-replicate, presenting an attractive platform for engineering scalable and affordable biosensing devices. Microbes are perfect candidates: they are inexpensive and easy to manipulate and store. Recent advances in synthetic biology promise to streamline the engineering of microbial biosensors with unprecedented capabilities. Here we review the applications of microbially-derived biosensors with a focus on environmental monitoring and healthcare applications. We also identify critical challenges that need to be addressed in order to translate the potential of synthetic microbial biosensors into large-scale, real-world applications. © 2017 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

DISP: Optimizations towards Scalable MPI Startup

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, Huansong; Pophale, Swaroop S; Gorentla Venkata, Manjunath

2016-01-01

Despite the popularity of MPI for high performance computing, the startup of MPI programs faces a scalability challenge as both the execution time and memory consumption increase drastically at scale. We have examined this problem using the collective modules of Cheetah and Tuned in Open MPI as representative implementations. Previous improvements for collectives have focused on algorithmic advances and hardware off-load. In this paper, we examine the startup cost of the collective module within a communicator and explore various techniques to improve its efficiency and scalability. Accordingly, we have developed a new scalable startup scheme with three internal techniques, namelymore » Delayed Initialization, Module Sharing and Prediction-based Topology Setup (DISP). Our DISP scheme greatly benefits the collective initialization of the Cheetah module. At the same time, it helps boost the performance of non-collective initialization in the Tuned module. We evaluate the performance of our implementation on Titan supercomputer at ORNL with up to 4096 processes. The results show that our delayed initialization can speed up the startup of Tuned and Cheetah by an average of 32.0% and 29.2%, respectively, our module sharing can reduce the memory consumption of Tuned and Cheetah by up to 24.1% and 83.5%, respectively, and our prediction-based topology setup can speed up the startup of Cheetah by up to 80%.« less

High-performance multiprocessor architecture for a 3-D lattice gas model

NASA Technical Reports Server (NTRS)

Lee, F.; Flynn, M.; Morf, M.

1991-01-01

The lattice gas method has recently emerged as a promising discrete particle simulation method in areas such as fluid dynamics. We present a very high-performance scalable multiprocessor architecture, called ALGE, proposed for the simulation of a realistic 3-D lattice gas model, Henon's 24-bit FCHC isometric model. Each of these VLSI processors is as powerful as a CRAY-2 for this application. ALGE is scalable in the sense that it achieves linear speedup for both fixed and increasing problem sizes with more processors. The core computation of a lattice gas model consists of many repetitions of two alternating phases: particle collision and propagation. Functional decomposition by symmetry group and virtual move are the respective keys to efficient implementation of collision and propagation.

High-power fiber-coupled 100W visible spectrum diode lasers for display applications

NASA Astrophysics Data System (ADS)

Unger, Andreas; Küster, Matthias; Köhler, Bernd; Biesenbach, Jens

2013-02-01

Diode lasers in the blue and red spectral range are the most promising light sources for upcoming high-brightness digital projectors in cinemas and large venue displays. They combine improved efficiency, longer lifetime and a greatly improved color space compared to traditional xenon light sources. In this paper we report on high-power visible diode laser sources to serve the demands of this emerging market. A unique electro-optical platform enables scalable fiber coupled sources at 638 nm with an output power of up to 100 W from a 400 μm NA0.22 fiber. For the blue diode laser we demonstrate scalable sources from 5 W to 100 W from a 400 μm NA0.22 fiber.

Scalable software architecture for on-line multi-camera video processing

NASA Astrophysics Data System (ADS)

Camplani, Massimo; Salgado, Luis

2011-03-01

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead.

Bio-inspired silicon nanospikes fabricated by metal-assisted chemical etching for antibacterial surfaces

NASA Astrophysics Data System (ADS)

Hu, Huan; Siu, Vince S.; Gifford, Stacey M.; Kim, Sungcheol; Lu, Minhua; Meyer, Pablo; Stolovitzky, Gustavo A.

2017-12-01

The recently discovered bactericidal properties of nanostructures on wings of insects such as cicadas and dragonflies have inspired the development of similar nanostructured surfaces for antibacterial applications. Since most antibacterial applications require nanostructures covering a considerable amount of area, a practical fabrication method needs to be cost-effective and scalable. However, most reported nanofabrication methods require either expensive equipment or a high temperature process, limiting cost efficiency and scalability. Here, we report a simple, fast, low-cost, and scalable antibacterial surface nanofabrication methodology. Our method is based on metal-assisted chemical etching that only requires etching a single crystal silicon substrate in a mixture of silver nitrate and hydrofluoric acid for several minutes. We experimentally studied the effects of etching time on the morphology of the silicon nanospikes and the bactericidal properties of the resulting surface. We discovered that 6 minutes of etching results in a surface containing silicon nanospikes with optimal geometry. The bactericidal properties of the silicon nanospikes were supported by bacterial plating results, fluorescence images, and scanning electron microscopy images.

Scalable metagenomic taxonomy classification using a reference genome database

PubMed Central

Ames, Sasha K.; Hysom, David A.; Gardner, Shea N.; Lloyd, G. Scott; Gokhale, Maya B.; Allen, Jonathan E.

2013-01-01

Motivation: Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge. Results: A method is presented to shift computational costs to an off-line computation by creating a taxonomy/genome index that supports scalable metagenomic classification. Scalable performance is demonstrated on real and simulated data to show accurate classification in the presence of novel organisms on samples that include viruses, prokaryotes, fungi and protists. Taxonomic classification of the previously published 150 giga-base Tyrolean Iceman dataset was found to take <20 h on a single node 40 core large memory machine and provide new insights on the metagenomic contents of the sample. Availability: Software was implemented in C++ and is freely available at http://sourceforge.net/projects/lmat Contact: allen99@llnl.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23828782

Scalable Fabrication of Integrated Nanophotonic Circuits on Arrays of Thin Single Crystal Diamond Membrane Windows.

PubMed

Piracha, Afaq H; Rath, Patrik; Ganesan, Kumaravelu; Kühn, Stefan; Pernice, Wolfram H P; Prawer, Steven

2016-05-11

Diamond has emerged as a promising platform for nanophotonic, optical, and quantum technologies. High-quality, single crystalline substrates of acceptable size are a prerequisite to meet the demanding requirements on low-level impurities and low absorption loss when targeting large photonic circuits. Here, we describe a scalable fabrication method for single crystal diamond membrane windows that achieves three major goals with one fabrication method: providing high quality diamond, as confirmed by Raman spectroscopy; achieving homogeneously thin membranes, enabled by ion implantation; and providing compatibility with established planar fabrication via lithography and vertical etching. On such suspended diamond membranes we demonstrate a suite of photonic components as building blocks for nanophotonic circuits. Monolithic grating couplers are used to efficiently couple light between photonic circuits and optical fibers. In waveguide coupled optical ring resonators, we find loaded quality factors up to 66 000 at a wavelength of 1560 nm, corresponding to propagation loss below 7.2 dB/cm. Our approach holds promise for the scalable implementation of future diamond quantum photonic technologies and all-diamond photonic metrology tools.

Millimeter-Wave Wireless Power Transfer Technology for Space Applications

NASA Technical Reports Server (NTRS)

Chattopadhyay, Goutam; Manohara, Harish; Mojarradi, Mohammad M.; Vo, Tuan A.; Mojarradi, Hadi; Bae, Sam Y.; Marzwell, Neville

2008-01-01

In this paper we present a new compact, scalable, and low cost technology for efficient receiving of power using RF waves at 94 GHz. This technology employs a highly innovative array of slot antennas that is integrated on substrate composed of gold (Au), silicon (Si), and silicon dioxide (SiO2) layers. The length of the slots and spacing between them are optimized for a highly efficient beam through a 3-D electromagnetic simulation process. Antenna simulation results shows a good beam profile with very low side lobe levels and better than 93% antenna efficiency.

Integrating cancer survivors' experiences into UK cancer registries: design and development of the ePOCS system (electronic Patient-reported Outcomes from Cancer Survivors)

PubMed Central

Ashley, L; Jones, H; Thomas, J; Forman, D; Newsham, A; Morris, E; Johnson, O; Velikova, G; Wright, P

2011-01-01

Background: Understanding the psychosocial challenges of cancer survivorship, and identifying which patients experience ongoing difficulties, is a key priority. The ePOCS (electronic patient-reported outcomes from cancer survivors) project aims to develop and evaluate a cost-efficient, UK-scalable electronic system for collecting patient-reported outcome measures (PROMs), at regular post-diagnostic timepoints, and linking these with clinical data in cancer registries. Methods: A multidisciplinary team developed the system using agile methods. Design entailed process mapping the system's constituent parts, data flows and involved human activities, and undertaking usability testing. Informatics specialists built new technical components, including a web-based questionnaire tool and tracking database, and established component-connecting data flows. Development challenges were overcome, including patient usability and data linkage and security. Results: We have developed a system in which PROMs are completed online, using a secure questionnaire administration tool, accessed via a public-facing website, and the responses are linked and stored with clinical registry data. Patient monitoring and communications are semiautomated via a tracker database, and patient correspondence is primarily Email-based. The system is currently honed for clinician-led hospital-based patient recruitment. Conclusions: A feasibility test study is underway. Although there are possible challenges to sustaining and scaling up ePOCS, the system has potential to support UK epidemiological PROMs collection and clinical data linkage. PMID:22048035

Rare-earth Doped GaN - An Innovative Path Toward Area-scalable Solid-state High Energy Lasers Without Thermal Distortion (2nd year)

DTIC Science & Technology

2010-06-01

heat removal technique and its efficiency , the gain medium itself is the bottleneck for non-distortive heat removal―simply due to low thermal...dysprosium (Dy) has been demonstrated by photoluminescence (PL), electroluminescence (EL), and/or cathodoluminescence (CL) (2, 3). As the RE dopant...provides the highest level of laser efficiency due to the pump and signal mode confinement within a crystalline-guided structure) has been designed. The

Rare-Earth Doped Gallium Nitride (GaN)- An Innovative Path Toward Area-scalable Solid-state High Energy Lasers Without Thermal Distortion

DTIC Science & Technology

2009-04-01

technique and its efficiency , the gain medium itself is the bottleneck for non-distortive heat removal—due to the low thermal conductivity of known gain...photoluminescence (PL), electroluminescence (EL), and/or cathodoluminescence (CL) (2,3). As the RE dopant, Nd is an excellent candidate due to its success...highest level of laser efficiency due to the pump and signal mode confinement within a crystalline-guided structure). The successful implementation of

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)

2002-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)

2001-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Perspectives in astrophysical databases

NASA Astrophysics Data System (ADS)

Frailis, Marco; de Angelis, Alessandro; Roberto, Vito

2004-07-01

Astrophysics has become a domain extremely rich of scientific data. Data mining tools are needed for information extraction from such large data sets. This asks for an approach to data management emphasizing the efficiency and simplicity of data access; efficiency is obtained using multidimensional access methods and simplicity is achieved by properly handling metadata. Moreover, clustering and classification techniques on large data sets pose additional requirements in terms of computation and memory scalability and interpretability of results. In this study we review some possible solutions.

Assessment of the scalability of a microtiter plate system for screening of oleaginous microorganisms.

PubMed

Kosa, Gergely; Vuoristo, Kiira S; Horn, Svein Jarle; Zimmermann, Boris; Afseth, Nils Kristian; Kohler, Achim; Shapaval, Volha

2018-06-01

Recent developments in molecular biology and metabolic engineering have resulted in a large increase in the number of strains that need to be tested, positioning high-throughput screening of microorganisms as an important step in bioprocess development. Scalability is crucial for performing reliable screening of microorganisms. Most of the scalability studies from microplate screening systems to controlled stirred-tank bioreactors have been performed so far with unicellular microorganisms. We have compared cultivation of industrially relevant oleaginous filamentous fungi and microalga in a Duetz-microtiter plate system to benchtop and pre-pilot bioreactors. Maximal glucose consumption rate, biomass concentration, lipid content of the biomass, biomass, and lipid yield values showed good scalability for Mucor circinelloides (less than 20% differences) and Mortierella alpina (less than 30% differences) filamentous fungi. Maximal glucose consumption and biomass production rates were identical for Crypthecodinium cohnii in microtiter plate and benchtop bioreactor. Most likely due to shear stress sensitivity of this microalga in stirred bioreactor, biomass concentration and lipid content of biomass were significantly higher in the microtiter plate system than in the benchtop bioreactor. Still, fermentation results obtained in the Duetz-microtiter plate system for Crypthecodinium cohnii are encouraging compared to what has been reported in literature. Good reproducibility (coefficient of variation less than 15% for biomass growth, glucose consumption, lipid content, and pH) were achieved in the Duetz-microtiter plate system for Mucor circinelloides and Crypthecodinium cohnii. Mortierella alpina cultivation reproducibility might be improved with inoculation optimization. In conclusion, we have presented suitability of the Duetz-microtiter plate system for the reproducible, scalable, and cost-efficient high-throughput screening of oleaginous microorganisms.

Doping and electronic properties of GaAs grown by close-spaced vapor transport from powder sources for scalable III–V photovoltaics

DOE PAGES

Ritenour, Andrew J.; Boucher, Jason W.; DeLancey, Robert; ...

2014-09-01

The high balance-of-system costs of photovoltaic (PV) installations indicate that reductions in cell $/W costs alone are likely insufficient for PV electricity to reach grid parity unless energy conversion efficiency is also increased. Technologies which yield both high-efficiency cells (>25%) and maintain low costs are needed. GaAs and related III-V semiconductors are used in the highest-efficiency single- and multi-junction photovoltaics, but the technology is too expensive for non-concentrated terrestrial applications. This is due in part to the difficulty of scaling the metal-organic chemical vapor deposition (MOCVD) process, which relies on expensive reactors and employs toxic and pyrophoric gas-phase precursors suchmore » as arsine and trimethyl gallium, respectively. In this study, we describe GaAs films made by an alternative close-spaced vapor transport (CSVT) technique which is carried out at atmospheric pressure and requires only bulk GaAs, water vapor, and a temperature gradient in order to deposit crystalline films with similar electronic properties to that of GaAs deposited by MOCVD. CSVT is similar to the vapor transport process used to deposit CdTe thin films and is thus a potentially scalable low-cost route to GaAs thin films.« less

Computer simulation of heterogeneous polymer photovoltaic devices

NASA Astrophysics Data System (ADS)

Kodali, Hari K.; Ganapathysubramanian, Baskar

2012-04-01

Polymer-based photovoltaic devices have the potential for widespread usage due to their low cost per watt and mechanical flexibility. Efficiencies close to 9.0% have been achieved recently in conjugated polymer based organic solar cells (OSCs). These devices were fabricated using solvent-based processing of electron-donating and electron-accepting materials into the so-called bulk heterojunction (BHJ) architecture. Experimental evidence suggests that a key property determining the power-conversion efficiency of such devices is the final morphological distribution of the donor and acceptor constituents. In order to understand the role of morphology on device performance, we develop a scalable computational framework that efficiently interrogates OSCs to investigate relationships between the morphology at the nano-scale with the device performance. In this work, we extend the Buxton and Clarke model (2007 Modelling Simul. Mater. Sci. Eng. 15 13-26) to simulate realistic devices with complex active layer morphologies using a dimensionally independent, scalable, finite-element method. We incorporate all stages involved in current generation, namely (1) exciton generation and diffusion, (2) charge generation and (3) charge transport in a modular fashion. The numerical challenges encountered during interrogation of realistic microstructures are detailed. We compare each stage of the photovoltaic process for two microstructures: a BHJ morphology and an idealized sawtooth morphology. The results are presented for both two- and three-dimensional structures.

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration,more » the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.« less

Efficient solar-to-fuels production from a hybrid microbial–water-splitting catalyst system

PubMed Central

Torella, Joseph P.; Gagliardi, Christopher J.; Chen, Janice S.; Bediako, D. Kwabena; Colón, Brendan; Way, Jeffery C.; Silver, Pamela A.; Nocera, Daniel G.

2015-01-01

Photovoltaic cells have considerable potential to satisfy future renewable-energy needs, but efficient and scalable methods of storing the intermittent electricity they produce are required for the large-scale implementation of solar energy. Current solar-to-fuels storage cycles based on water splitting produce hydrogen and oxygen, which are attractive fuels in principle but confront practical limitations from the current energy infrastructure that is based on liquid fuels. In this work, we report the development of a scalable, integrated bioelectrochemical system in which the bacterium Ralstonia eutropha is used to efficiently convert CO2, along with H2 and O2 produced from water splitting, into biomass and fusel alcohols. Water-splitting catalysis was performed using catalysts that are made of earth-abundant metals and enable low overpotential water splitting. In this integrated setup, equivalent solar-to-biomass yields of up to 3.2% of the thermodynamic maximum exceed that of most terrestrial plants. Moreover, engineering of R. eutropha enabled production of the fusel alcohol isopropanol at up to 216 mg/L, the highest bioelectrochemical fuel yield yet reported by >300%. This work demonstrates that catalysts of biotic and abiotic origin can be interfaced to achieve challenging chemical energy-to-fuels transformations. PMID:25675518

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

NASA Astrophysics Data System (ADS)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

2017-12-01

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated - reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

Efficient data replication for the delivery of high-quality video content over P2P VoD advertising networks

NASA Astrophysics Data System (ADS)

Ho, Chien-Peng; Yu, Jen-Yu; Lee, Suh-Yin

2011-12-01

Recent advances in modern television systems have had profound consequences for the scalability, stability, and quality of transmitted digital data signals. This is of particular significance for peer-to-peer (P2P) video-on-demand (VoD) related platforms, faced with an immediate and growing demand for reliable service delivery. In response to demands for high-quality video, the key objectives in the construction of the proposed framework were user satisfaction with perceived video quality and the effective utilization of available resources on P2P VoD networks. This study developed a peer-based promoter to support online advertising in P2P VoD networks based on an estimation of video distortion prior to the replication of data stream chunks. The proposed technology enables the recovery of lost video using replicated stream chunks in real time. Load balance is achieved by adjusting the replication level of each candidate group according to the degree-of-distortion, thereby enabling a significant reduction in server load and increased scalability in the P2P VoD system. This approach also promotes the use of advertising as an efficient tool for commercial promotion. Results indicate that the proposed system efficiently satisfies the given fault tolerances.

Large landscape conservation-synthetic and real-world datasets

Treesearch

Bistra Dilkina; Katherine Lai; Ronan Le Bras; Yexiang Xue; Carla P. Gomes; Ashish Sabharwal; Jordan Suter; Kevin S. McKelvey; Michael K. Schwartz; Claire Montgomery

2013-01-01

Biodiversity underpins ecosystem goods and services and hence protecting it is key to achieving sustainability. However, the persistence of many species is threatened by habitat loss and fragmentation due to human land use and climate change. Conservation efforts are implemented under very limited economic resources, and therefore designing scalable, cost-efficient and...

Conceptual net energy output for biofuel production from lignocellulosic biomass through biorefining

Treesearch

J.Y. Zhu; X.S. Zhuang

2012-01-01

There is a lack of comprehensive information in the retrievable literature on pilot scale process and energy data using promising process technologies and commercially scalable and available capital equipment for lignocellulosic biomass biorefining. This study conducted a comprehensive review of the energy efficiency of selected sugar platform biorefinery process...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allman, M. S., E-mail: shane.allman@boulder.nist.gov; Verma, V. B.; Stevens, M.

We demonstrate a 64-pixel free-space-coupled array of superconducting nanowire single photon detectors optimized for high detection efficiency in the near-infrared range. An integrated, readily scalable, multiplexed readout scheme is employed to reduce the number of readout lines to 16. The cryogenic, optical, and electronic packaging to read out the array as well as characterization measurements are discussed.

Parallel O(N) Stokes’ solver towards scalable Brownian dynamics of hydrodynamically interacting objects in general geometries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Xujun; Li, Jiyuan; Jiang, Xikai

An efficient parallel Stokes’s solver is developed towards the complete inclusion of hydrodynamic interactions of Brownian particles in any geometry. A Langevin description of the particle dynamics is adopted, where the long-range interactions are included using a Green’s function formalism. We present a scalable parallel computational approach, where the general geometry Stokeslet is calculated following a matrix-free algorithm using the General geometry Ewald-like method. Our approach employs a highly-efficient iterative finite element Stokes’ solver for the accurate treatment of long-range hydrodynamic interactions within arbitrary confined geometries. A combination of mid-point time integration of the Brownian stochastic differential equation, the parallelmore » Stokes’ solver, and a Chebyshev polynomial approximation for the fluctuation-dissipation theorem result in an O(N) parallel algorithm. We also illustrate the new algorithm in the context of the dynamics of confined polymer solutions in equilibrium and non-equilibrium conditions. Our method is extended to treat suspended finite size particles of arbitrary shape in any geometry using an Immersed Boundary approach.« less

Binary Interval Search: a scalable algorithm for counting interval intersections

PubMed Central

Layer, Ryan M.; Skadron, Kevin; Robins, Gabriel; Hall, Ira M.; Quinlan, Aaron R.

2013-01-01

Motivation: The comparison of diverse genomic datasets is fundamental to understand genome biology. Researchers must explore many large datasets of genome intervals (e.g. genes, sequence alignments) to place their experimental results in a broader context and to make new discoveries. Relationships between genomic datasets are typically measured by identifying intervals that intersect, that is, they overlap and thus share a common genome interval. Given the continued advances in DNA sequencing technologies, efficient methods for measuring statistically significant relationships between many sets of genomic features are crucial for future discovery. Results: We introduce the Binary Interval Search (BITS) algorithm, a novel and scalable approach to interval set intersection. We demonstrate that BITS outperforms existing methods at counting interval intersections. Moreover, we show that BITS is intrinsically suited to parallel computing architectures, such as graphics processing units by illustrating its utility for efficient Monte Carlo simulations measuring the significance of relationships between sets of genomic intervals. Availability: https://github.com/arq5x/bits. Contact: arq5x@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23129298

Jumping-Droplet-Enhanced Condensation on Scalable Superhydrophobic Nanostructured Surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miljkovic, N; Enright, R; Nam, Y

When droplets coalesce on a superhydrophobic nanostructured surface, the resulting droplet can jump from the surface due to the release of excess surface energy. If designed properly, these superhydrophobic nanostructured surfaces can not only allow for easy droplet removal at micrometric length scales during condensation but also promise to enhance heat transfer performance. However, the rationale for the design of an ideal nanostructured surface as well as heat transfer experiments demonstrating the advantage of this jumping behavior are lacking. Here, we show that silanized copper oxide surfaces created via a simple fabrication method can achieve highly efficient jumping-droplet condensation heatmore » transfer. We experimentally demonstrated a 25% higher overall heat flux and 30% higher condensation heat transfer coefficient compared to state-of-the-art hydrophobic condensing surfaces at low supersaturations (<1.12). This work not only shows significant condensation heat transfer enhancement but also promises a low cost and scalable approach to increase efficiency for applications such as atmospheric water harvesting and dehumidification. Furthermore, the results offer insights and an avenue to achieve high flux superhydrophobic condensation.« less

On delay adjustment for dynamic load balancing in distributed virtual environments.

PubMed

Deng, Yunhua; Lau, Rynson W H

2012-04-01

Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead.

Highly Efficient Perovskite Solar Modules by Scalable Fabrication and Interconnection Optimization

DOE PAGES

Yang, Mengjin; Kim, Dong Hoe; Klein, Talysa R.; ...

2018-01-02

To push perovskite solar cell (PSC) technology toward practical applications, large-area perovskite solar modules with multiple subcells need to be developed by fully scalable deposition approaches. Here, we demonstrate a deposition scheme for perovskite module fabrication with spray coating of a TiO2 electron transport layer (ETL) and blade coating of both a perovskite absorber layer and a spiro-OMeTAD-based hole transport layer (HTL). The TiO2 ETL remaining in the interconnection between subcells significantly affects the module performance. Reducing the TiO2 thickness changes the interconnection contact from a Schottky diode to ohmic behavior. Owing to interconnection resistance reduction, the perovskite modules withmore » a 10 nm TiO2 layer show enhanced performance mainly associated with an improved fill factor. Finally, we demonstrate a four-cell MA0.7FA0.3PbI3 perovskite module with a stabilized power conversion efficiency (PCE) of 15.6% measured from an aperture area of ~10.36 cm2, corresponding to an active-area module PCE of 17.9% with a geometric fill factor of ~87.3%.« less

Advances in Patch-Based Adaptive Mesh Refinement Scalability

DOE PAGES

Gunney, Brian T.N.; Anderson, Robert W.

2015-12-18

Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extensionmore » of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.« less

Efficient etching-free transfer of high quality, large-area CVD grown graphene onto polyvinyl alcohol films

NASA Astrophysics Data System (ADS)

Marta, Bogdan; Leordean, Cosmin; Istvan, Todor; Botiz, Ioan; Astilean, Simion

2016-02-01

Graphene transfer is a procedure of paramount importance for the production of graphene-based electronic devices. The transfer procedure can affect the electronic properties of the transferred graphene and can be detrimental for possible applications both due to procedure induced defects which can appear and due to scalability of the method. Hence, it is important to investigate new transfer methods for graphene that are less time consuming and show great promise. In the present study we propose an efficient, etching-free transfer method that consists in applying a thin polyvinyl alcohol layer on top of the CVD grown graphene on Cu and then peeling-off the graphene onto the polyvinyl alcohol film. We investigate the quality of the transferred graphene before and after the transfer, using Raman spectroscopy and imaging as well as optical and atomic force microscopy techniques. This simple transfer method is scalable and can lead to complete transfer of graphene onto flexible and transparent polymer support films without affecting the quality of the graphene during the transfer procedure.

A structural model decomposition framework for systems health management

NASA Astrophysics Data System (ADS)

Roychoudhury, I.; Daigle, M.; Bregon, A.; Pulido, B.

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

Parallel O(N) Stokes’ solver towards scalable Brownian dynamics of hydrodynamically interacting objects in general geometries

DOE PAGES

Zhao, Xujun; Li, Jiyuan; Jiang, Xikai; ...

2017-06-29

An efficient parallel Stokes’s solver is developed towards the complete inclusion of hydrodynamic interactions of Brownian particles in any geometry. A Langevin description of the particle dynamics is adopted, where the long-range interactions are included using a Green’s function formalism. We present a scalable parallel computational approach, where the general geometry Stokeslet is calculated following a matrix-free algorithm using the General geometry Ewald-like method. Our approach employs a highly-efficient iterative finite element Stokes’ solver for the accurate treatment of long-range hydrodynamic interactions within arbitrary confined geometries. A combination of mid-point time integration of the Brownian stochastic differential equation, the parallelmore » Stokes’ solver, and a Chebyshev polynomial approximation for the fluctuation-dissipation theorem result in an O(N) parallel algorithm. We also illustrate the new algorithm in the context of the dynamics of confined polymer solutions in equilibrium and non-equilibrium conditions. Our method is extended to treat suspended finite size particles of arbitrary shape in any geometry using an Immersed Boundary approach.« less

A Structural Model Decomposition Framework for Systems Health Management

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Daigle, Matthew J.; Bregon, Anibal; Pulido, Belamino

2013-01-01

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

Highly Efficient Perovskite Solar Modules by Scalable Fabrication and Interconnection Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Mengjin; Kim, Dong Hoe; Klein, Talysa R.

To push perovskite solar cell (PSC) technology toward practical applications, large-area perovskite solar modules with multiple subcells need to be developed by fully scalable deposition approaches. Here, we demonstrate a deposition scheme for perovskite module fabrication with spray coating of a TiO2 electron transport layer (ETL) and blade coating of both a perovskite absorber layer and a spiro-OMeTAD-based hole transport layer (HTL). The TiO2 ETL remaining in the interconnection between subcells significantly affects the module performance. Reducing the TiO2 thickness changes the interconnection contact from a Schottky diode to ohmic behavior. Owing to interconnection resistance reduction, the perovskite modules withmore » a 10 nm TiO2 layer show enhanced performance mainly associated with an improved fill factor. Finally, we demonstrate a four-cell MA0.7FA0.3PbI3 perovskite module with a stabilized power conversion efficiency (PCE) of 15.6% measured from an aperture area of ~10.36 cm2, corresponding to an active-area module PCE of 17.9% with a geometric fill factor of ~87.3%.« less

Advances in Patch-Based Adaptive Mesh Refinement Scalability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunney, Brian T.N.; Anderson, Robert W.

Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extensionmore » of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

Transportation Network Topologies

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.; Scott, John M.

2004-01-01

A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21PstP thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the 'Southwest Effect'). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.

Transportation Network Topologies

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.; Scott, John

2004-01-01

A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the Southwest Effect). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.

An Efficient, Scalable and Robust P2P Overlay for Autonomic Communication

NASA Astrophysics Data System (ADS)

Li, Deng; Liu, Hui; Vasilakos, Athanasios

The term Autonomic Communication (AC) refers to self-managing systems which are capable of supporting self-configuration, self-healing and self-optimization. However, information reflection and collection, lack of centralized control, non-cooperation and so on are just some of the challenges within AC systems. Since many self-* properties (e.g. selfconfiguration, self-optimization, self-healing, and self-protecting) are achieved by a group of autonomous entities that coordinate in a peer-to-peer (P2P) fashion, it has opened the door to migrating research techniques from P2P systems. P2P's meaning can be better understood with a set of key characteristics similar to AC: Decentralized organization, Self-organizing nature (i.e. adaptability), Resource sharing and aggregation, and Fault-tolerance. However, not all P2P systems are compatible with AC. Unstructured systems are designed more specifically than structured systems for the heterogeneous Internet environment, where the nodes' persistence and availability are not guaranteed. Motivated by the challenges in AC and based on comprehensive analysis of popular P2P applications, three correlative standards for evaluating the compatibility of a P2P system with AC are presented in this chapter. According to these standards, a novel Efficient, Scalable and Robust (ESR) P2P overlay is proposed. Differing from current structured and unstructured, or meshed and tree-like P2P overlay, the ESR is a whole new three dimensional structure to improve the efficiency of routing, while information exchanges take in immediate neighbors with local information to make the system scalable and fault-tolerant. Furthermore, rather than a complex game theory or incentive mechanism, asimple but effective punish mechanism has been presented based on a new ID structure which can guarantee the continuity of each node's record in order to discourage negative behavior on an autonomous environment as AC.

fastBMA: scalable network inference and transitive reduction.

PubMed

Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

2017-10-01

Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

Evaluation of in-network adaptation of scalable high efficiency video coding (SHVC) in mobile environments

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio

2014-02-01

High Efficiency Video Coding (HEVC), the latest video compression standard (also known as H.265), can deliver video streams of comparable quality to the current H.264 Advanced Video Coding (H.264/AVC) standard with a 50% reduction in bandwidth. Research into SHVC, the scalable extension to the HEVC standard, is still in its infancy. One important area for investigation is whether, given the greater compression ratio of HEVC (and SHVC), the loss of packets containing video content will have a greater impact on the quality of delivered video than is the case with H.264/AVC or its scalable extension H.264/SVC. In this work we empirically evaluate the layer-based, in-network adaptation of video streams encoded using SHVC in situations where dynamically changing bandwidths and datagram loss ratios require the real-time adaptation of video streams. Through the use of extensive experimentation, we establish a comprehensive set of benchmarks for SHVC-based highdefinition video streaming in loss prone network environments such as those commonly found in mobile networks. Among other results, we highlight that packet losses of only 1% can lead to a substantial reduction in PSNR of over 3dB and error propagation in over 130 pictures following the one in which the loss occurred. This work would be one of the earliest studies in this cutting-edge area that reports benchmark evaluation results for the effects of datagram loss on SHVC picture quality and offers empirical and analytical insights into SHVC adaptation to lossy, mobile networking conditions.

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

DOE PAGES

Banerjee, Amartya S.; Lin, Lin; Hu, Wei; ...

2016-10-21

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) canmore » be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.« less

Role of Edges in Complex Network Epidemiology

NASA Astrophysics Data System (ADS)

Zhang, Hao; Jiang, Zhi-Hong; Wang, Hui; Xie, Fei; Chen, Chao

2012-09-01

In complex network epidemiology, diseases spread along contacting edges between individuals and different edges may play different roles in epidemic outbreaks. Quantifying the efficiency of edges is an important step towards arresting epidemics. In this paper, we study the efficiency of edges in general susceptible-infected-recovered models, and introduce the transmission capability to measure the efficiency of edges. Results show that deleting edges with the highest transmission capability will greatly decrease epidemics on scale-free networks. Basing on the message passing approach, we get exact mathematical solution on configuration model networks with edge deletion in the large size limit.

Efficient computation of kinship and identity coefficients on large pedigrees.

PubMed

Cheng, En; Elliott, Brendan; Ozsoyoglu, Z Meral

2009-06-01

With the rapidly expanding field of medical genetics and genetic counseling, genealogy information is becoming increasingly abundant. An important computation on pedigree data is the calculation of identity coefficients, which provide a complete description of the degree of relatedness of a pair of individuals. The areas of application of identity coefficients are numerous and diverse, from genetic counseling to disease tracking, and thus, the computation of identity coefficients merits special attention. However, the computation of identity coefficients is not done directly, but rather as the final step after computing a set of generalized kinship coefficients. In this paper, we first propose a novel Path-Counting Formula for calculating generalized kinship coefficients, which is motivated by Wright's path-counting method for computing inbreeding coefficient. We then present an efficient and scalable scheme for calculating generalized kinship coefficients on large pedigrees using NodeCodes, a special encoding scheme for expediting the evaluation of queries on pedigree graph structures. Furthermore, we propose an improved scheme using Family NodeCodes for the computation of generalized kinship coefficients, which is motivated by the significant improvement of using Family NodeCodes for inbreeding coefficient over the use of NodeCodes. We also perform experiments for evaluating the efficiency of our method, and compare it with the performance of the traditional recursive algorithm for three individuals. Experimental results demonstrate that the resulting scheme is more scalable and efficient than the traditional recursive methods for computing generalized kinship coefficients.

Organic electronics on fibers for energy conversion applications

NASA Astrophysics Data System (ADS)

O'Connor, Brendan T.

Currently, there is great demand for pollution-free and renewable sources of electricity. Solar cells are particularly attractive from the standpoint of sunlight abundance. However, truly widespread adoption of solar cells is impeded by the high cost and poor scalability of existing technologies. For example, while 53,000 mi2 of 10% efficient solar cell modules would be required to supply the current U.S. energy demand, only about 50 mi2 have been installed worldwide. Organic semiconductors potentially offer a route to realizing low-cost solar cell modules, but currently suffer from low conversion efficiency. For organic-based solar cells to become commercially viable, further research is required to improve device performance, develop scalable manufacturing methods, and reduce installation costs via, for example, novel device form factors. This thesis makes several contributions to the field of organic solar cells, including the replacement of costly and brittle indium tin oxide (ITO) electrodes by inexpensive and malleable, thin metal films, and the application of external dielectric coatings to improve power conversion efficiency. Furthermore, we show that devices with non-planar geometries (e.g. organic solar cells deposited onto long fibers) can have higher efficiencies than conventional planar devices. Building on these results, we demonstrate novel fiber-based organic light emitting devices (OLEDs) that offer substantially improved color quality and manufacturability as a next-generation solid-state lighting technology. An intriguing possibility afforded by the fiber-based device architectures is the ability to integrate energy conversion and lighting functionalities with textiles, a mature, commodity-scale technology.

Efficient population-scale variant analysis and prioritization with VAPr.

PubMed

Birmingham, Amanda; Mark, Adam M; Mazzaferro, Carlo; Xu, Guorong; Fisch, Kathleen M

2018-04-06

With the growing availability of population-scale whole-exome and whole-genome sequencing, demand for reproducible, scalable variant analysis has spread within genomic research communities. To address this need, we introduce the Python package VAPr (Variant Analysis and Prioritization). VAPr leverages existing annotation tools ANNOVAR and MyVariant.info with MongoDB-based flexible storage and filtering functionality. It offers biologists and bioinformatics generalists easy-to-use and scalable analysis and prioritization of genomic variants from large cohort studies. VAPr is developed in Python and is available for free use and extension under the MIT License. An install package is available on PyPi at https://pypi.python.org/pypi/VAPr, while source code and extensive documentation are on GitHub at https://github.com/ucsd-ccbb/VAPr. kfisch@ucsd.edu.

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

PubMed

Merolla, Paul A; Arthur, John V; Alvarez-Icaza, Rodrigo; Cassidy, Andrew S; Sawada, Jun; Akopyan, Filipp; Jackson, Bryan L; Imam, Nabil; Guo, Chen; Nakamura, Yutaka; Brezzo, Bernard; Vo, Ivan; Esser, Steven K; Appuswamy, Rathinakumar; Taba, Brian; Amir, Arnon; Flickner, Myron D; Risk, William P; Manohar, Rajit; Modha, Dharmendra S

2014-08-08

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts. Copyright © 2014, American Association for the Advancement of Science.

Tunable optical frequency comb enabled scalable and cost-effective multiuser orthogonal frequency-division multiple access passive optical network with source-free optical network units.

PubMed

Chen, Chen; Zhang, Chongfu; Liu, Deming; Qiu, Kun; Liu, Shuang

2012-10-01

We propose and experimentally demonstrate a multiuser orthogonal frequency-division multiple access passive optical network (OFDMA-PON) with source-free optical network units (ONUs), enabled by tunable optical frequency comb generation technology. By cascading a phase modulator (PM) and an intensity modulator and dynamically controlling the peak-to-peak voltage of a PM driven signal, a tunable optical frequency comb source can be generated. It is utilized to assist the configuration of a multiple source-free ONUs enhanced OFDMA-PON where simultaneous and interference-free multiuser upstream transmission over a single wavelength can be efficiently supported. The proposed multiuser OFDMA-PON is scalable and cost effective, and its feasibility is successfully verified by experiment.

Scalable photonic quantum computing assisted by quantum-dot spin in double-sided optical microcavity.

PubMed

Wei, Hai-Rui; Deng, Fu-Guo

2013-07-29

We investigate the possibility of achieving scalable photonic quantum computing by the giant optical circular birefringence induced by a quantum-dot spin in a double-sided optical microcavity as a result of cavity quantum electrodynamics. We construct a deterministic controlled-not gate on two photonic qubits by two single-photon input-output processes and the readout on an electron-medium spin confined in an optical resonant microcavity. This idea could be applied to multi-qubit gates on photonic qubits and we give the quantum circuit for a three-photon Toffoli gate. High fidelities and high efficiencies could be achieved when the side leakage to the cavity loss rate is low. It is worth pointing out that our devices work in both the strong and the weak coupling regimes.

The high performance parallel algorithm for Unified Gas-Kinetic Scheme

NASA Astrophysics Data System (ADS)

Li, Shiyi; Li, Qibing; Fu, Song; Xu, Jinxiu

2016-11-01

A high performance parallel algorithm for UGKS is developed to simulate three-dimensional flows internal and external on arbitrary grid system. The physical domain and velocity domain are divided into different blocks and distributed according to the two-dimensional Cartesian topology with intra-communicators in physical domain for data exchange and other intra-communicators in velocity domain for sum reduction to moment integrals. Numerical results of three-dimensional cavity flow and flow past a sphere agree well with the results from the existing studies and validate the applicability of the algorithm. The scalability of the algorithm is tested both on small (1-16) and large (729-5832) scale processors. The tested speed-up ratio is near linear ashind thus the efficiency is around 1, which reveals the good scalability of the present algorithm.

A Scalable Nonuniform Pointer Analysis for Embedded Program

NASA Technical Reports Server (NTRS)

Venet, Arnaud

2004-01-01

In this paper we present a scalable pointer analysis for embedded applications that is able to distinguish between instances of recursively defined data structures and elements of arrays. The main contribution consists of an efficient yet precise algorithm that can handle multithreaded programs. We first perform an inexpensive flow-sensitive analysis of each function in the program that generates semantic equations describing the effect of the function on the memory graph. These equations bear numerical constraints that describe nonuniform points-to relationships. We then iteratively solve these equations in order to obtain an abstract storage graph that describes the shape of data structures at every point of the program for all possible thread interleavings. We bring experimental evidence that this approach is tractable and precise for real-size embedded applications.

Efficient multifeature index structures for music data retrieval

NASA Astrophysics Data System (ADS)

Lee, Wegin; Chen, Arbee L. P.

1999-12-01

In this paper, we propose four index structures for music data retrieval. Based on suffix trees, we develop two index structures called combined suffix tree and independent suffix trees. These methods still show shortcomings for some search functions. Hence we develop another index, called Twin Suffix Trees, to overcome these problems. However, the Twin Suffix Trees lack of scalability when the amount of music data becomes large. Therefore we propose the fourth index, called Grid-Twin Suffix Trees, to provide scalability and flexibility for a large amount of music data. For each index, we can use different search functions, like exact search and approximate search, on different music features, like melody, rhythm or both. We compare the performance of the different search functions applied on each index structure by a series of experiments.

Efficient Measurement of Quantum Gate Error by Interleaved Randomized Benchmarking

NASA Astrophysics Data System (ADS)

Magesan, Easwar; Gambetta, Jay M.; Johnson, B. R.; Ryan, Colm A.; Chow, Jerry M.; Merkel, Seth T.; da Silva, Marcus P.; Keefe, George A.; Rothwell, Mary B.; Ohki, Thomas A.; Ketchen, Mark B.; Steffen, M.

2012-08-01

We describe a scalable experimental protocol for estimating the average error of individual quantum computational gates. This protocol consists of interleaving random Clifford gates between the gate of interest and provides an estimate as well as theoretical bounds for the average error of the gate under test, so long as the average noise variation over all Clifford gates is small. This technique takes into account both state preparation and measurement errors and is scalable in the number of qubits. We apply this protocol to a superconducting qubit system and find a bounded average error of 0.003 [0,0.016] for the single-qubit gates Xπ/2 and Yπ/2. These bounded values provide better estimates of the average error than those extracted via quantum process tomography.

A complexity-scalable software-based MPEG-2 video encoder.

PubMed

Chen, Guo-bin; Lu, Xin-ning; Wang, Xing-guo; Liu, Ji-lin

2004-05-01

With the development of general-purpose processors (GPP) and video signal processing algorithms, it is possible to implement a software-based real-time video encoder on GPP, and its low cost and easy upgrade attract developers' interests to transfer video encoding from specialized hardware to more flexible software. In this paper, the encoding structure is set up first to support complexity scalability; then a lot of high performance algorithms are used on the key time-consuming modules in coding process; finally, at programming level, processor characteristics are considered to improve data access efficiency and processing parallelism. Other programming methods such as lookup table are adopted to reduce the computational complexity. Simulation results showed that these ideas could not only improve the global performance of video coding, but also provide great flexibility in complexity regulation.

Parallel scalability of Hartree-Fock calculations

NASA Astrophysics Data System (ADS)

Chow, Edmond; Liu, Xing; Smelyanskiy, Mikhail; Hammond, Jeff R.

2015-03-01

Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree-Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

A scalable SIMD digital signal processor for high-quality multifunctional printer systems

NASA Astrophysics Data System (ADS)

Kang, Hyeong-Ju; Choi, Yongwoo; Kim, Kimo; Park, In-Cheol; Kim, Jung-Wook; Lee, Eul-Hwan; Gahang, Goo-Soo

2005-01-01

This paper describes a high-performance scalable SIMD digital signal processor (DSP) developed for multifunctional printer systems. The DSP supports a variable number of datapaths to cover a wide range of performance and maintain a RISC-like pipeline structure. Many special instructions suitable for image processing algorithms are included in the DSP. Quad/dual instructions are introduced for 8-bit or 16-bit data, and bit-field extraction/insertion instructions are supported to process various data types. Conditional instructions are supported to deal with complex relative conditions efficiently. In addition, an intelligent DMA block is integrated to align data in the course of data reading. Experimental results show that the proposed DSP outperforms a high-end printer-system DSP by at least two times.

Integrated Avionics System (IAS)

NASA Technical Reports Server (NTRS)

Hunter, D. J.

2001-01-01

As spacecraft designs converge toward miniaturization and with the volumetric and mass constraints placed on avionics, programs will continue to advance the 'state of the art' in spacecraft systems development with new challenges to reduce power, mass, and volume. Although new technologies have improved packaging densities, a total system packaging architecture is required that not only reduces spacecraft volume and mass budgets, but increase integration efficiencies, provide modularity and scalability to accommodate multiple missions. With these challenges in mind, a novel packaging approach incorporates solutions that provide broader environmental applications, more flexible system interconnectivity, scalability, and simplified assembly test and integration schemes. This paper will describe the fundamental elements of the Integrated Avionics System (IAS), Horizontally Mounted Cube (HMC) hardware design, system and environmental test results. Additional information is contained in the original extended abstract.

Scalable algorithms for three-field mixed finite element coupled poromechanics

NASA Astrophysics Data System (ADS)

Castelletto, Nicola; White, Joshua A.; Ferronato, Massimiliano

2016-12-01

We introduce a class of block preconditioners for accelerating the iterative solution of coupled poromechanics equations based on a three-field formulation. The use of a displacement/velocity/pressure mixed finite-element method combined with a first order backward difference formula for the approximation of time derivatives produces a sequence of linear systems with a 3 × 3 unsymmetric and indefinite block matrix. The preconditioners are obtained by approximating the two-level Schur complement with the aid of physically-based arguments that can be also generalized in a purely algebraic approach. A theoretical and experimental analysis is presented that provides evidence of the robustness, efficiency and scalability of the proposed algorithm. The performance is also assessed for a real-world challenging consolidation experiment of a shallow formation.

Scalable implicit incompressible resistive MHD with stabilized FE and fully-coupled Newton–Krylov-AMG

DOE PAGES

Shadid, J. N.; Pawlowski, R. P.; Cyr, E. C.; ...

2016-02-10

Here, we discuss that the computational solution of the governing balance equations for mass, momentum, heat transfer and magnetic induction for resistive magnetohydrodynamics (MHD) systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena, as well as the significant range of time- and length-scales that the interactions of these physical mechanisms produce. This paper explores the development of a scalable, fully-implicit stabilized unstructured finite element (FE) capability for 3D incompressible resistive MHD. The discussion considers the development of a stabilized FE formulation in context of the variational multiscale (VMS) method,more » and describes the scalable implicit time integration and direct-to-steady-state solution capability. The nonlinear solver strategy employs Newton–Krylov methods, which are preconditioned using fully-coupled algebraic multilevel preconditioners. These preconditioners are shown to enable a robust, scalable and efficient solution approach for the large-scale sparse linear systems generated by the Newton linearization. Verification results demonstrate the expected order-of-accuracy for the stabilized FE discretization. The approach is tested on a variety of prototype problems, that include MHD duct flows, an unstable hydromagnetic Kelvin–Helmholtz shear layer, and a 3D island coalescence problem used to model magnetic reconnection. Initial results that explore the scaling of the solution methods are also presented on up to 128K processors for problems with up to 1.8B unknowns on a CrayXK7.« less

Smart integrated microsystems: the energy efficiency challenge (Conference Presentation) (Plenary Presentation)

NASA Astrophysics Data System (ADS)

Benini, Luca

2017-06-01

The "internet of everything" envisions trillions of connected objects loaded with high-bandwidth sensors requiring massive amounts of local signal processing, fusion, pattern extraction and classification. From the computational viewpoint, the challenge is formidable and can be addressed only by pushing computing fabrics toward massive parallelism and brain-like energy efficiency levels. CMOS technology can still take us a long way toward this goal, but technology scaling is losing steam. Energy efficiency improvement will increasingly hinge on architecture, circuits, design techniques such as heterogeneous 3D integration, mixed-signal preprocessing, event-based approximate computing and non-Von-Neumann architectures for scalable acceleration.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, Atul K.

The overall objectives of this DOE funded project is to combine scientific and computational challenges in climate modeling by expanding our understanding of the biogeophysical-biogeochemical processes and their interactions in the northern high latitudes (NHLs) using an earth system modeling (ESM) approach, and by adopting an adaptive parallel runtime system in an ESM to achieve efficient and scalable climate simulations through improved load balancing algorithms.

A Quantitative Risk Analysis Framework for Evaluating and Monitoring Operational Reliability of Cloud Computing

ERIC Educational Resources Information Center

Islam, Muhammad Faysal

2013-01-01

Cloud computing offers the advantage of on-demand, reliable and cost efficient computing solutions without the capital investment and management resources to build and maintain in-house data centers and network infrastructures. Scalability of cloud solutions enable consumers to upgrade or downsize their services as needed. In a cloud environment,…

Dense, Efficient Chip-to-Chip Communication at the Extremes of Computing

ERIC Educational Resources Information Center

Loh, Matthew

2013-01-01

The scalability of CMOS technology has driven computation into a diverse range of applications across the power consumption, performance and size spectra. Communication is a necessary adjunct to computation, and whether this is to push data from node-to-node in a high-performance computing cluster or from the receiver of wireless link to a neural…

Review of the harvesting and extraction of advanced biofuels and bioproducts

Treesearch

Babette L. Marrone;  Ronald E.  Lacey;  Daniel B. Anderson;  James Bonner;  Jim Coons;  Taraka Dale;  Cara Meghan Downes;  Sandun Fernando;  Christopher  Fuller;  Brian Goodall;  Johnathan E. Holladay;  Kiran Kadam;  Daniel  Kalb;  Wei  Liu;  John B. Mott;  Zivko Nikolov;  Kimberly L. Ogden;  Richard T. Sayre;  Brian G. Trewyn;  José A. Olivares

2017-01-01

Energy-efficient and scalable harvesting and lipid extraction processes must be developed in order for the algal biofuels and bioproducts industry to thrive. The major challenge for harvesting is the handling of large volumes of cultivation water to concentrate low amounts of biomass. For lipid extraction, the major energy and cost drivers are associated with...

Recovery of Rare Earths, Precious Metals and Other Critical Materials from Geothermal Waters with Advanced Sorbent Structures

DOE Data Explorer

Pamela M. Kinsey

2015-09-30

The work evaluates, develops and demonstrates flexible, scalable mineral extraction technology for geothermal brines based upon solid phase sorbent materials with a specific focus upon rare earth elements (REEs). The selected organic and inorganic sorbent materials demonstrated high performance for collection of trace REEs, precious and valuable metals. The nanostructured materials typically performed better than commercially available sorbents. Data contains organic and inorganic sorbent removal efficiency, Sharkey Hot Springs (Idaho) water chemsitry analysis, and rare earth removal efficiency from select sorbents.

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

Nosocomial infections—a new approach towards preventive medicine using plasmas

NASA Astrophysics Data System (ADS)

Morfill, G. E.; Shimizu, T.; Steffes, B.; Schmidt, H.-U.

2009-11-01

A new, very efficient, large area scalable and robust electrode design for plasma production in air at atmosphere pressures has been developed and tested. This has made the development of a 'plasma dispenser' for hospital disinfection possible, which has certain advantages over current fluid disinfection systems. The properties of this device are presented, in particular the bactericidal and fungicidal efficiency, and the advantages are described. Such plasma dispensers could play an important role in the future fight against the alarming and growing threat posed by nosocomial (=hospital and community associated) bacterial infections.

Space-Filling Supercapacitor Carpets: Highly scalable fractal architecture for energy storage

NASA Astrophysics Data System (ADS)

Tiliakos, Athanasios; Trefilov, Alexandra M. I.; Tanasǎ, Eugenia; Balan, Adriana; Stamatin, Ioan

2018-04-01

Revamping ground-breaking ideas from fractal geometry, we propose an alternative micro-supercapacitor configuration realized by laser-induced graphene (LIG) foams produced via laser pyrolysis of inexpensive commercial polymers. The Space-Filling Supercapacitor Carpet (SFSC) architecture introduces the concept of nested electrodes based on the pre-fractal Peano space-filling curve, arranged in a symmetrical equilateral setup that incorporates multiple parallel capacitor cells sharing common electrodes for maximum efficiency and optimal length-to-area distribution. We elucidate on the theoretical foundations of the SFSC architecture, and we introduce innovations (high-resolution vector-mode printing) in the LIG method that allow for the realization of flexible and scalable devices based on low iterations of the Peano algorithm. SFSCs exhibit distributed capacitance properties, leading to capacitance, energy, and power ratings proportional to the number of nested electrodes (up to 4.3 mF, 0.4 μWh, and 0.2 mW for the largest tested model of low iteration using aqueous electrolytes), with competitively high energy and power densities. This can pave the road for full scalability in energy storage, reaching beyond the scale of micro-supercapacitors for incorporating into larger and more demanding applications.

Revisiting Parallel Cyclic Reduction and Parallel Prefix-Based Algorithms for Block Tridiagonal System of Equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seal, Sudip K; Perumalla, Kalyan S; Hirshman, Steven Paul

2013-01-01

Simulations that require solutions of block tridiagonal systems of equations rely on fast parallel solvers for runtime efficiency. Leading parallel solvers that are highly effective for general systems of equations, dense or sparse, are limited in scalability when applied to block tridiagonal systems. This paper presents scalability results as well as detailed analyses of two parallel solvers that exploit the special structure of block tridiagonal matrices to deliver superior performance, often by orders of magnitude. A rigorous analysis of their relative parallel runtimes is shown to reveal the existence of a critical block size that separates the parameter space spannedmore » by the number of block rows, the block size and the processor count, into distinct regions that favor one or the other of the two solvers. Dependence of this critical block size on the above parameters as well as on machine-specific constants is established. These formal insights are supported by empirical results on up to 2,048 cores of a Cray XT4 system. To the best of our knowledge, this is the highest reported scalability for parallel block tridiagonal solvers to date.« less

Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems.

PubMed

Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

2016-10-28

Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems' architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation.

Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems

PubMed Central

Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

2016-01-01

Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems’ architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation. PMID:27801829

Identifying unproven cancer treatments on the health web: addressing accuracy, generalizability and scalability.

PubMed

Aphinyanaphongs, Yin; Fu, Lawrence D; Aliferis, Constantin F

2013-01-01

Building machine learning models that identify unproven cancer treatments on the Health Web is a promising approach for dealing with the dissemination of false and dangerous information to vulnerable health consumers. Aside from the obvious requirement of accuracy, two issues are of practical importance in deploying these models in real world applications. (a) Generalizability: The models must generalize to all treatments (not just the ones used in the training of the models). (b) Scalability: The models can be applied efficiently to billions of documents on the Health Web. First, we provide methods and related empirical data demonstrating strong accuracy and generalizability. Second, by combining the MapReduce distributed architecture and high dimensionality compression via Markov Boundary feature selection, we show how to scale the application of the models to WWW-scale corpora. The present work provides evidence that (a) a very small subset of unproven cancer treatments is sufficient to build a model to identify unproven treatments on the web; (b) unproven treatments use distinct language to market their claims and this language is learnable; (c) through distributed parallelization and state of the art feature selection, it is possible to prepare the corpora and build and apply models with large scalability.

The ELPA library: scalable parallel eigenvalue solutions for electronic structure theory and computational science.

PubMed

Marek, A; Blum, V; Johanni, R; Havu, V; Lang, B; Auckenthaler, T; Heinecke, A; Bungartz, H-J; Lederer, H

2014-05-28

Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structure theory and many other areas of computational science. The computational effort formally scales as O(N(3)) with the size of the investigated problem, N (e.g. the electron count in electronic structure theory), and thus often defines the system size limit that practical calculations cannot overcome. In many cases, more than just a small fraction of the possible eigenvalue/eigenvector pairs is needed, so that iterative solution strategies that focus only on a few eigenvalues become ineffective. Likewise, it is not always desirable or practical to circumvent the eigenvalue solution entirely. We here review some current developments regarding dense eigenvalue solvers and then focus on the Eigenvalue soLvers for Petascale Applications (ELPA) library, which facilitates the efficient algebraic solution of symmetric and Hermitian eigenvalue problems for dense matrices that have real-valued and complex-valued matrix entries, respectively, on parallel computer platforms. ELPA addresses standard as well as generalized eigenvalue problems, relying on the well documented matrix layout of the Scalable Linear Algebra PACKage (ScaLAPACK) library but replacing all actual parallel solution steps with subroutines of its own. For these steps, ELPA significantly outperforms the corresponding ScaLAPACK routines and proprietary libraries that implement the ScaLAPACK interface (e.g. Intel's MKL). The most time-critical step is the reduction of the matrix to tridiagonal form and the corresponding backtransformation of the eigenvectors. ELPA offers both a one-step tridiagonalization (successive Householder transformations) and a two-step transformation that is more efficient especially towards larger matrices and larger numbers of CPU cores. ELPA is based on the MPI standard, with an early hybrid MPI-OpenMPI implementation available as well. Scalability beyond 10,000 CPU cores for problem sizes arising in the field of electronic structure theory is demonstrated for current high-performance computer architectures such as Cray or Intel/Infiniband. For a matrix of dimension 260,000, scalability up to 295,000 CPU cores has been shown on BlueGene/P.

Towards scalable quantum communication and computation: Novel approaches and realizations

NASA Astrophysics Data System (ADS)

Jiang, Liang

Quantum information science involves exploration of fundamental laws of quantum mechanics for information processing tasks. This thesis presents several new approaches towards scalable quantum information processing. First, we consider a hybrid approach to scalable quantum computation, based on an optically connected network of few-qubit quantum registers. Specifically, we develop a novel scheme for scalable quantum computation that is robust against various imperfections. To justify that nitrogen-vacancy (NV) color centers in diamond can be a promising realization of the few-qubit quantum register, we show how to isolate a few proximal nuclear spins from the rest of the environment and use them for the quantum register. We also demonstrate experimentally that the nuclear spin coherence is only weakly perturbed under optical illumination, which allows us to implement quantum logical operations that use the nuclear spins to assist the repetitive-readout of the electronic spin. Using this technique, we demonstrate more than two-fold improvement in signal-to-noise ratio. Apart from direct application to enhance the sensitivity of the NV-based nano-magnetometer, this experiment represents an important step towards the realization of robust quantum information processors using electronic and nuclear spin qubits. We then study realizations of quantum repeaters for long distance quantum communication. Specifically, we develop an efficient scheme for quantum repeaters based on atomic ensembles. We use dynamic programming to optimize various quantum repeater protocols. In addition, we propose a new protocol of quantum repeater with encoding, which efficiently uses local resources (about 100 qubits) to identify and correct errors, to achieve fast one-way quantum communication over long distances. Finally, we explore quantum systems with topological order. Such systems can exhibit remarkable phenomena such as quasiparticles with anyonic statistics and have been proposed as candidates for naturally error-free quantum computation. We propose a scheme to unambiguously detect the anyonic statistics in spin lattice realizations using ultra-cold atoms in an optical lattice. We show how to reliably read and write topologically protected quantum memory using an atomic or photonic qubit.

Parallel processing architecture for H.264 deblocking filter on multi-core platforms

NASA Astrophysics Data System (ADS)

Prasad, Durga P.; Sonachalam, Sekar; Kunchamwar, Mangesh K.; Gunupudi, Nageswara Rao

2012-03-01

Massively parallel computing (multi-core) chips offer outstanding new solutions that satisfy the increasing demand for high resolution and high quality video compression technologies such as H.264. Such solutions not only provide exceptional quality but also efficiency, low power, and low latency, previously unattainable in software based designs. While custom hardware and Application Specific Integrated Circuit (ASIC) technologies may achieve lowlatency, low power, and real-time performance in some consumer devices, many applications require a flexible and scalable software-defined solution. The deblocking filter in H.264 encoder/decoder poses difficult implementation challenges because of heavy data dependencies and the conditional nature of the computations. Deblocking filter implementations tend to be fixed and difficult to reconfigure for different needs. The ability to scale up for higher quality requirements such as 10-bit pixel depth or a 4:2:2 chroma format often reduces the throughput of a parallel architecture designed for lower feature set. A scalable architecture for deblocking filtering, created with a massively parallel processor based solution, means that the same encoder or decoder will be deployed in a variety of applications, at different video resolutions, for different power requirements, and at higher bit-depths and better color sub sampling patterns like YUV, 4:2:2, or 4:4:4 formats. Low power, software-defined encoders/decoders may be implemented using a massively parallel processor array, like that found in HyperX technology, with 100 or more cores and distributed memory. The large number of processor elements allows the silicon device to operate more efficiently than conventional DSP or CPU technology. This software programing model for massively parallel processors offers a flexible implementation and a power efficiency close to that of ASIC solutions. This work describes a scalable parallel architecture for an H.264 compliant deblocking filter for multi core platforms such as HyperX technology. Parallel techniques such as parallel processing of independent macroblocks, sub blocks, and pixel row level are examined in this work. The deblocking architecture consists of a basic cell called deblocking filter unit (DFU) and dependent data buffer manager (DFM). The DFU can be used in several instances, catering to different performance needs the DFM serves the data required for the different number of DFUs, and also manages all the neighboring data required for future data processing of DFUs. This approach achieves the scalability, flexibility, and performance excellence required in deblocking filters.

On-Demand Single Photons with High Extraction Efficiency and Near-Unity Indistinguishability from a Resonantly Driven Quantum Dot in a Micropillar.

PubMed

Ding, Xing; He, Yu; Duan, Z-C; Gregersen, Niels; Chen, M-C; Unsleber, S; Maier, S; Schneider, Christian; Kamp, Martin; Höfling, Sven; Lu, Chao-Yang; Pan, Jian-Wei

2016-01-15

Scalable photonic quantum technologies require on-demand single-photon sources with simultaneously high levels of purity, indistinguishability, and efficiency. These key features, however, have only been demonstrated separately in previous experiments. Here, by s-shell pulsed resonant excitation of a Purcell-enhanced quantum dot-micropillar system, we deterministically generate resonance fluorescence single photons which, at π pulse excitation, have an extraction efficiency of 66%, single-photon purity of 99.1%, and photon indistinguishability of 98.5%. Such a single-photon source for the first time combines the features of high efficiency and near-perfect levels of purity and indistinguishabilty, and thus opens the way to multiphoton experiments with semiconductor quantum dots.

High-efficiency solid state power amplifier

NASA Technical Reports Server (NTRS)

Wallis, Robert E. (Inventor); Cheng, Sheng (Inventor)

2005-01-01

A high-efficiency solid state power amplifier (SSPA) for specific use in a spacecraft is provided. The SSPA has a mass of less than 850 g and includes two different X-band power amplifier sections, i.e., a lumped power amplifier with a single 11-W output and a distributed power amplifier with eight 2.75-W outputs. These two amplifier sections provide output power that is scalable from 11 to 15 watts without major design changes. Five different hybrid microcircuits, including high-efficiency Heterostructure Field Effect Transistor (HFET) amplifiers and Monolithic Microwave Integrated Circuit (MMIC) phase shifters have been developed for use within the SSPA. A highly efficient packaging approach enables the integration of a large number of hybrid circuits into the SSPA.

High-Performance Polymers Sandwiched with Chemical Vapor Deposited Hexagonal Boron Nitrides as Scalable High-Temperature Dielectric Materials.

PubMed

Azizi, Amin; Gadinski, Matthew R; Li, Qi; AlSaud, Mohammed Abu; Wang, Jianjun; Wang, Yi; Wang, Bo; Liu, Feihua; Chen, Long-Qing; Alem, Nasim; Wang, Qing

2017-09-01

Polymer dielectrics are the preferred materials of choice for power electronics and pulsed power applications. However, their relatively low operating temperatures significantly limit their uses in harsh-environment energy storage devices, e.g., automobile and aerospace power systems. Herein, hexagonal boron nitride (h-BN) films are prepared from chemical vapor deposition (CVD) and readily transferred onto polyetherimide (PEI) films. Greatly improved performance in terms of discharged energy density and charge-discharge efficiency is achieved in the PEI sandwiched with CVD-grown h-BN films at elevated temperatures when compared to neat PEI films and other high-temperature polymer and nanocomposite dielectrics. Notably, the h-BN-coated PEI films are capable of operating with >90% charge-discharge efficiencies and delivering high energy densities, i.e., 1.2 J cm -3 , even at a temperature close to the glass transition temperature of polymer (i.e., 217 °C) where pristine PEI almost fails. Outstanding cyclability and dielectric stability over a straight 55 000 charge-discharge cycles are demonstrated in the h-BN-coated PEI at high temperatures. The work demonstrates a general and scalable pathway to enable the high-temperature capacitive energy applications of a wide range of engineering polymers and also offers an efficient method for the synthesis and transfer of 2D nanomaterials at the scale demanded for applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

DOE PAGES

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; ...

2017-10-17

In this paper we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach ismore » used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.« less

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan

In this paper we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach ismore » used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.« less

A scalable geometric multigrid solver for nonsymmetric elliptic systems with application to variable-density flows

NASA Astrophysics Data System (ADS)

Esmaily, M.; Jofre, L.; Mani, A.; Iaccarino, G.

2018-03-01

A geometric multigrid algorithm is introduced for solving nonsymmetric linear systems resulting from the discretization of the variable density Navier-Stokes equations on nonuniform structured rectilinear grids and high-Reynolds number flows. The restriction operation is defined such that the resulting system on the coarser grids is symmetric, thereby allowing for the use of efficient smoother algorithms. To achieve an optimal rate of convergence, the sequence of interpolation and restriction operations are determined through a dynamic procedure. A parallel partitioning strategy is introduced to minimize communication while maintaining the load balance between all processors. To test the proposed algorithm, we consider two cases: 1) homogeneous isotropic turbulence discretized on uniform grids and 2) turbulent duct flow discretized on stretched grids. Testing the algorithm on systems with up to a billion unknowns shows that the cost varies linearly with the number of unknowns. This O (N) behavior confirms the robustness of the proposed multigrid method regarding ill-conditioning of large systems characteristic of multiscale high-Reynolds number turbulent flows. The robustness of our method to density variations is established by considering cases where density varies sharply in space by a factor of up to 104, showing its applicability to two-phase flow problems. Strong and weak scalability studies are carried out, employing up to 30,000 processors, to examine the parallel performance of our implementation. Excellent scalability of our solver is shown for a granularity as low as 104 to 105 unknowns per processor. At its tested peak throughput, it solves approximately 4 billion unknowns per second employing over 16,000 processors with a parallel efficiency higher than 50%.

Joint-layer encoder optimization for HEVC scalable extensions

NASA Astrophysics Data System (ADS)

Tsai, Chia-Ming; He, Yuwen; Dong, Jie; Ye, Yan; Xiu, Xiaoyu; He, Yong

2014-09-01

Scalable video coding provides an efficient solution to support video playback on heterogeneous devices with various channel conditions in heterogeneous networks. SHVC is the latest scalable video coding standard based on the HEVC standard. To improve enhancement layer coding efficiency, inter-layer prediction including texture and motion information generated from the base layer is used for enhancement layer coding. However, the overall performance of the SHVC reference encoder is not fully optimized because rate-distortion optimization (RDO) processes in the base and enhancement layers are independently considered. It is difficult to directly extend the existing joint-layer optimization methods to SHVC due to the complicated coding tree block splitting decisions and in-loop filtering process (e.g., deblocking and sample adaptive offset (SAO) filtering) in HEVC. To solve those problems, a joint-layer optimization method is proposed by adjusting the quantization parameter (QP) to optimally allocate the bit resource between layers. Furthermore, to make more proper resource allocation, the proposed method also considers the viewing probability of base and enhancement layers according to packet loss rate. Based on the viewing probability, a novel joint-layer RD cost function is proposed for joint-layer RDO encoding. The QP values of those coding tree units (CTUs) belonging to lower layers referenced by higher layers are decreased accordingly, and the QP values of those remaining CTUs are increased to keep total bits unchanged. Finally the QP values with minimal joint-layer RD cost are selected to match the viewing probability. The proposed method was applied to the third temporal level (TL-3) pictures in the Random Access configuration. Simulation results demonstrate that the proposed joint-layer optimization method can improve coding performance by 1.3% for these TL-3 pictures compared to the SHVC reference encoder without joint-layer optimization.

Investigation on scalable high-power lasers with enhanced 'eye-safety' for future weapon systems

NASA Astrophysics Data System (ADS)

Bigotta, S.; Diener, K.; Eichhorn, M.; Galecki, L.; Geiss, L.; Ibach, T.; Scharf, H.; von Salisch, M.; Schöner, J.; Vincent, G.

2016-10-01

The possible use of lasers as weapons becomes more and more interesting for military forces. Besides the generation of high laser power and good beam quality, also safety considerations, e. g. concerning eye hazards, are of importance. The MELIAS (medium energy laser in the "eye-safe" spectral domain) project of ISL addresses these issues, and ISL has developed the most powerful solid-state laser in the "eye-safe" wavelength region up to now. "Eye safety" in this context means that light at a wavelength of > 1.4 μm does not penetrate the eye and thus will not be focused onto the retina. The basic principle of this technology is that a laser source needs to be scalable in power to far beyond 100 kW without a significant deterioration in beam quality. ISL has studied a very promising laser technology: the erbium heat-capacity laser. This type of laser is characterised by a compact design, a simple and robust technology and a scaling law which, in principle, allows the generation of laser power far beyond megawatts at small volumes. Previous investigations demonstrated the scalability of the SSHCL and up to 4.65 kW and 440 J in less than 800 ms have been obtained. Opticalto- optical efficiencies of over 41% and slope efficiencies of over 51% are obtained. The residual thermal gradients, due to non perfect pumping homogeneity, negatively affect the performance in terms of laser pulse energy, duration and beam quality. In the course of the next two years, ISL will be designing a 25 to 30 kW erbium heat-capacity laser.

Scalable and template-free synthesis of nanostructured Na{sub 1.08}V{sub 6}O{sub 15} as high-performance cathode material for lithium-ion batteries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Shili, E-mail: slzheng@ipe.ac.cn; Wang, Xinran; Yan, Hong

2016-09-15

Highlights: • Nanostructured Na{sub 1.08}V{sub 6}O{sub 15} was synthesized through additive-free sol-gel process. • Prepared Na{sub 1.08}V{sub 6}O{sub 15} demonstrated high capacity and sufficient cycling stability. • The reaction temperature was optimized to allow scalable Na{sub 1.08}V{sub 6}O{sub 15} fabrication. - Abstract: Developing high-capacity cathode material with feasibility and scalability is still challenging for lithium-ion batteries (LIBs). In this study, a high-capacity ternary sodium vanadate compound, nanostructured NaV{sub 6}O{sub 15}, was template-free synthesized through sol-gel process with high producing efficiency. The as-prepared sample was systematically post-treated at different temperature and the post-annealing temperature was found to determine the cycling stabilitymore » and capacity of NaV{sub 6}O{sub 15}. The well-crystallized one exhibited good electrochemical performance with a high specific capacity of 302 mAh g{sup −1} when cycled at current density of 0.03 mA g{sup −1}. Its relatively long-term cycling stability was characterized by the cell performance under the current density of 1 A g{sup −1}, delivering a reversible capacity of 118 mAh g{sup −1} after 300 cycles with 79% capacity retention and nearly 100% coulombic efficiency: all demonstrating its significant promise of proposed strategy for large-scale synthesis of NaV{sub 6}O{sub 15} as cathode with high-capacity and high energy density for LIBs.« less

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

PubMed Central

Teng, Rui; Leibnitz, Kenji; Miura, Ryu

2013-01-01

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner. PMID:23748172

SeqHBase: a big data toolset for family based sequencing data analysis.

PubMed

He, Min; Person, Thomas N; Hebbring, Scott J; Heinzen, Ethan; Ye, Zhan; Schrodi, Steven J; McPherson, Elizabeth W; Lin, Simon M; Peissig, Peggy L; Brilliant, Murray H; O'Rawe, Jason; Robison, Reid J; Lyon, Gholson J; Wang, Kai

2015-04-01

Whole-genome sequencing (WGS) and whole-exome sequencing (WES) technologies are increasingly used to identify disease-contributing mutations in human genomic studies. It can be a significant challenge to process such data, especially when a large family or cohort is sequenced. Our objective was to develop a big data toolset to efficiently manipulate genome-wide variants, functional annotations and coverage, together with conducting family based sequencing data analysis. Hadoop is a framework for reliable, scalable, distributed processing of large data sets using MapReduce programming models. Based on Hadoop and HBase, we developed SeqHBase, a big data-based toolset for analysing family based sequencing data to detect de novo, inherited homozygous, or compound heterozygous mutations that may contribute to disease manifestations. SeqHBase takes as input BAM files (for coverage at every site), variant call format (VCF) files (for variant calls) and functional annotations (for variant prioritisation). We applied SeqHBase to a 5-member nuclear family and a 10-member 3-generation family with WGS data, as well as a 4-member nuclear family with WES data. Analysis times were almost linearly scalable with number of data nodes. With 20 data nodes, SeqHBase took about 5 secs to analyse WES familial data and approximately 1 min to analyse WGS familial data. These results demonstrate SeqHBase's high efficiency and scalability, which is necessary as WGS and WES are rapidly becoming standard methods to study the genetics of familial disorders. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Creating a process for incorporating epidemiological modelling into outbreak management decisions.

PubMed

Akselrod, Hana; Mercon, Monica; Kirkeby Risoe, Petter; Schlegelmilch, Jeffrey; McGovern, Joanne; Bogucki, Sandy

2012-01-01

Modern computational models of infectious diseases greatly enhance our ability to understand new infectious threats and assess the effects of different interventions. The recently-released CDC Framework for Preventing Infectious Diseases calls for increased use of predictive modelling of epidemic emergence for public health preparedness. Currently, the utility of these technologies in preparedness and response to outbreaks is limited by gaps between modelling output and information requirements for incident management. The authors propose an operational structure that will facilitate integration of modelling capabilities into action planning for outbreak management, using the Incident Command System (ICS) and Synchronization Matrix framework. It is designed to be adaptable and scalable for use by state and local planners under the National Response Framework (NRF) and Emergency Support Function #8 (ESF-8). Specific epidemiological modelling requirements are described, and integrated with the core processes for public health emergency decision support. These methods can be used in checklist format to align prospective or real-time modelling output with anticipated decision points, and guide strategic situational assessments at the community level. It is anticipated that formalising these processes will facilitate translation of the CDC's policy guidance from theory to practice during public health emergencies involving infectious outbreaks.

Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: A population-based study.

PubMed

Jajou, Rana; de Neeling, Albert; van Hunen, Rianne; de Vries, Gerard; Schimmel, Henrieke; Mulder, Arnout; Anthony, Richard; van der Hoek, Wim; van Soolingen, Dick

2018-01-01

Patients with Mycobacterium tuberculosis isolates sharing identical DNA fingerprint patterns can be epidemiologically linked. However, municipal health services in the Netherlands are able to confirm an epidemiological link in only around 23% of the patients with isolates clustered by the conventional variable number of tandem repeat (VNTR) genotyping. This research aims to investigate whether whole genome sequencing (WGS) is a more reliable predictor of epidemiological links between tuberculosis patients than VNTR genotyping. VNTR genotyping and WGS were performed in parallel on all Mycobacterium tuberculosis complex isolates received at the Netherlands National Institute for Public Health and the Environment in 2016. Isolates were clustered by VNTR when they shared identical 24-loci VNTR patterns; isolates were assigned to a WGS cluster when the pair-wise genetic distance was ≤ 12 single nucleotide polymorphisms (SNPs). Cluster investigation was performed by municipal health services on all isolates clustered by VNTR in 2016. The proportion of epidemiological links identified among patients clustered by either method was calculated. In total, 535 isolates were genotyped, of which 25% (134/535) were clustered by VNTR and 14% (76/535) by WGS; the concordance between both typing methods was 86%. The proportion of epidemiological links among WGS clustered cases (57%) was twice as common than among VNTR clustered cases (31%). When WGS was applied, the number of clustered isolates was halved, while all epidemiologically linked cases remained clustered. WGS is therefore a more reliable tool to predict epidemiological links between tuberculosis cases than VNTR genotyping and will allow more efficient transmission tracing, as epidemiological investigations based on false clustering can be avoided.

Scalable quantum information processing with atomic ensembles and flying photons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mei Feng; Yu Yafei; Feng Mang

2009-10-15

We present a scheme for scalable quantum information processing with atomic ensembles and flying photons. Using the Rydberg blockade, we encode the qubits in the collective atomic states, which could be manipulated fast and easily due to the enhanced interaction in comparison to the single-atom case. We demonstrate that our proposed gating could be applied to generation of two-dimensional cluster states for measurement-based quantum computation. Moreover, the atomic ensembles also function as quantum repeaters useful for long-distance quantum state transfer. We show the possibility of our scheme to work in bad cavity or in weak coupling regime, which could muchmore » relax the experimental requirement. The efficient coherent operations on the ensemble qubits enable our scheme to be switchable between quantum computation and quantum communication using atomic ensembles.« less

Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduce

NASA Astrophysics Data System (ADS)

Farhan Husain, Mohammad; Doshi, Pankil; Khan, Latifur; Thuraisingham, Bhavani

Handling huge amount of data scalably is a matter of concern for a long time. Same is true for semantic web data. Current semantic web frameworks lack this ability. In this paper, we describe a framework that we built using Hadoop to store and retrieve large number of RDF triples. We describe our schema to store RDF data in Hadoop Distribute File System. We also present our algorithms to answer a SPARQL query. We make use of Hadoop's MapReduce framework to actually answer the queries. Our results reveal that we can store huge amount of semantic web data in Hadoop clusters built mostly by cheap commodity class hardware and still can answer queries fast enough. We conclude that ours is a scalable framework, able to handle large amount of RDF data efficiently.

Use of the NetBeans Platform for NASA Robotic Conjunction Assessment Risk Analysis

NASA Technical Reports Server (NTRS)

Sabey, Nickolas J.

2014-01-01

The latest Java and JavaFX technologies are very attractive software platforms for customers involved in space mission operations such as those of NASA and the US Air Force. For NASA Robotic Conjunction Assessment Risk Analysis (CARA), the NetBeans platform provided an environment in which scalable software solutions could be developed quickly and efficiently. Both Java 8 and the NetBeans platform are in the process of simplifying CARA development in secure environments by providing a significant amount of capability in a single accredited package, where accreditation alone can account for 6-8 months for each library or software application. Capabilities either in use or being investigated by CARA include: 2D and 3D displays with JavaFX, parallelization with the new Streams API, and scalability through the NetBeans plugin architecture.

Optically enhanced acoustophoresis

NASA Astrophysics Data System (ADS)

McDougall, Craig; O'Mahoney, Paul; McGuinn, Alan; Willoughby, Nicholas A.; Qiu, Yongqiang; Demore, Christine E. M.; MacDonald, Michael P.

2017-08-01

Regenerative medicine has the capability to revolutionise many aspects of medical care, but for it to make the step from small scale autologous treatments to larger scale allogeneic approaches, robust and scalable label free cell sorting technologies are needed as part of a cell therapy bioprocessing pipeline. In this proceedings we describe several strategies for addressing the requirements for high throughput without labeling via: dimensional scaling, rare species targeting and sorting from a stable state. These three approaches are demonstrated through a combination of optical and ultrasonic forces. By combining mostly conservative and non-conservative forces from two different modalities it is possible to reduce the influence of flow velocity on sorting efficiency, hence increasing robustness and scalability. One such approach can be termed "optically enhanced acoustophoresis" which combines the ability of acoustics to handle large volumes of analyte with the high specificity of optical sorting.

Vortex Filaments in Grids for Scalable, Fine Smoke Simulation.

PubMed

Meng, Zhang; Weixin, Si; Yinling, Qian; Hanqiu, Sun; Jing, Qin; Heng, Pheng-Ann

2015-01-01

Vortex modeling can produce attractive visual effects of dynamic fluids, which are widely applicable for dynamic media, computer games, special effects, and virtual reality systems. However, it is challenging to effectively simulate intensive and fine detailed fluids such as smoke with fast increasing vortex filaments and smoke particles. The authors propose a novel vortex filaments in grids scheme in which the uniform grids dynamically bridge the vortex filaments and smoke particles for scalable, fine smoke simulation with macroscopic vortex structures. Using the vortex model, their approach supports the trade-off between simulation speed and scale of details. After computing the whole velocity, external control can be easily exerted on the embedded grid to guide the vortex-based smoke motion. The experimental results demonstrate the efficiency of using the proposed scheme for a visually plausible smoke simulation with macroscopic vortex structures.

Efficient Byzantine Fault Tolerance for Scalable Storage and Services

DTIC Science & Technology

2009-07-01

most critical applications must survive in ever harsher environments. Less synchronous networking delivers packets unreliably and unpredictably, and... synchronous environments to allowing asynchrony, and from tolerating crashes to tolerating some corruptions through ad-hoc consistency checks. Ad-hoc...servers are responsive. To support this thesis statement, this disseration takes the following steps. First, it develops a new cryptographic primitive

Electricity generation from cattle manure slurry by cassette-electrode microbial fuel cells.

PubMed

Inoue, Kengo; Ito, Toshihiro; Kawano, Yoshihiro; Iguchi, Atsushi; Miyahara, Morio; Suzuki, Yoshihiro; Watanabe, Kazuya

2013-11-01

Cassette-electrode microbial fuel cells (CE-MFCs) are efficient and scalable devices for electricity production from organic waste. Previous studies have demonstrated that CE-MFCs are capable of generating electricity from artificial wastewater at relatively high efficiencies. In this study, a single-cassette CE-MFC was constructed, and its capacity for electricity generation from cattle manure suspended in water (solid to water ratio of 1:50) was examined. The CE-MFC reactor was operated in batch mode for 49 days; electricity generation became stable 2 weeks after initiating the operation. The maximum power density was measured at 16.3 W m⁻³ on day 26. Sequencing analysis of PCR-amplified 16S rRNA gene fragments obtained from the original manure and from anode biofilms suggested that Chloroflexi and Geobacteraceae were abundant in the anode biofilm (29% and 18%, respectively), whereas no Geobacteraceae sequences were detected in the original manure sample. The results of this study suggest that CE-MFCs can be used to generate electricity from water-suspended cattle manure in a scalable MFC system. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

DOE PAGES

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

2018-05-01

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less

Toward Perovskite Solar Cell Commercialization: A Perspective and Research Roadmap Based on Interfacial Engineering.

PubMed

Rajagopal, Adharsh; Yao, Kai; Jen, Alex K-Y

2018-06-08

High-efficiency and low-cost perovskite solar cells (PVKSCs) are an ideal candidate for addressing the scalability challenge of solar-based renewable energy. The dynamically evolving research field of PVKSCs has made immense progress in solving inherent challenges and capitalizing on their unique structure-property-processing-performance traits. This review offers a unique outlook on the paths toward commercialization of PVKSCs from the interfacial engineering perspective, relevant to both specialists and nonspecialists in the field through a brief introduction of the background of the field, current state-of-the-art evolution, and future research prospects. The multifaceted role of interfaces in facilitating PVKSC development is explained. Beneficial impacts of diverse charge-transporting materials and interfacial modifications are summarized. In addition, the role of interfaces in improving efficiency and stability for all emerging areas of PVKSC design are also evaluated. The authors' integral contributions in this area are highlighted on all fronts. Finally, future research opportunities for interfacial material development and applications along with scalability-durability-sustainability considerations pivotal for facilitating laboratory to industry translation are presented. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-Layer Approach for the Detection of Selective Forwarding Attacks

PubMed Central

Alajmi, Naser; Elleithy, Khaled

2015-01-01

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable. PMID:26610499

Scalable PGAS Metadata Management on Extreme Scale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavarría-Miranda, Daniel; Agarwal, Khushbu; Straatsma, TP

Programming models intended to run on exascale systems have a number of challenges to overcome, specially the sheer size of the system as measured by the number of concurrent software entities created and managed by the underlying runtime. It is clear from the size of these systems that any state maintained by the programming model has to be strictly sub-linear in size, in order not to overwhelm memory usage with pure overhead. A principal feature of Partitioned Global Address Space (PGAS) models is providing easy access to global-view distributed data structures. In order to provide efficient access to these distributedmore » data structures, PGAS models must keep track of metadata such as where array sections are located with respect to processes/threads running on the HPC system. As PGAS models and applications become ubiquitous on very large transpetascale systems, a key component to their performance and scalability will be efficient and judicious use of memory for model overhead (metadata) compared to application data. We present an evaluation of several strategies to manage PGAS metadata that exhibit different space/time tradeoffs. We use two real-world PGAS applications to capture metadata usage patterns and gain insight into their communication behavior.« less

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Multi-Layer Approach for the Detection of Selective Forwarding Attacks.

PubMed

Alajmi, Naser; Elleithy, Khaled

2015-11-19

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

Scalable and Versatile Genome Editing Using Linear DNAs with Microhomology to Cas9 Sites in Caenorhabditis elegans

PubMed Central

Paix, Alexandre; Wang, Yuemeng; Smith, Harold E.; Lee, Chih-Yung S.; Calidas, Deepika; Lu, Tu; Smith, Jarrett; Schmidt, Helen; Krause, Michael W.; Seydoux, Geraldine

2014-01-01

Homology-directed repair (HDR) of double-strand DNA breaks is a promising method for genome editing, but is thought to be less efficient than error-prone nonhomologous end joining in most cell types. We have investigated HDR of double-strand breaks induced by CRISPR-associated protein 9 (Cas9) in Caenorhabditis elegans. We find that HDR is very robust in the C. elegans germline. Linear repair templates with short (∼30–60 bases) homology arms support the integration of base and gene-sized edits with high efficiency, bypassing the need for selection. Based on these findings, we developed a systematic method to mutate, tag, or delete any gene in the C. elegans genome without the use of co-integrated markers or long homology arms. We generated 23 unique edits at 11 genes, including premature stops, whole-gene deletions, and protein fusions to antigenic peptides and GFP. Whole-genome sequencing of five edited strains revealed the presence of passenger variants, but no mutations at predicted off-target sites. The method is scalable for multi-gene editing projects and could be applied to other animals with an accessible germline. PMID:25249454

A scalable variational inequality approach for flow through porous media models with pressure-dependent viscosity

NASA Astrophysics Data System (ADS)

Mapakshi, N. K.; Chang, J.; Nakshatrala, K. B.

2018-04-01

Mathematical models for flow through porous media typically enjoy the so-called maximum principles, which place bounds on the pressure field. It is highly desirable to preserve these bounds on the pressure field in predictive numerical simulations, that is, one needs to satisfy discrete maximum principles (DMP). Unfortunately, many of the existing formulations for flow through porous media models do not satisfy DMP. This paper presents a robust, scalable numerical formulation based on variational inequalities (VI), to model non-linear flows through heterogeneous, anisotropic porous media without violating DMP. VI is an optimization technique that places bounds on the numerical solutions of partial differential equations. To crystallize the ideas, a modification to Darcy equations by taking into account pressure-dependent viscosity will be discretized using the lowest-order Raviart-Thomas (RT0) and Variational Multi-scale (VMS) finite element formulations. It will be shown that these formulations violate DMP, and, in fact, these violations increase with an increase in anisotropy. It will be shown that the proposed VI-based formulation provides a viable route to enforce DMP. Moreover, it will be shown that the proposed formulation is scalable, and can work with any numerical discretization and weak form. A series of numerical benchmark problems are solved to demonstrate the effects of heterogeneity, anisotropy and non-linearity on DMP violations under the two chosen formulations (RT0 and VMS), and that of non-linearity on solver convergence for the proposed VI-based formulation. Parallel scalability on modern computational platforms will be illustrated through strong-scaling studies, which will prove the efficiency of the proposed formulation in a parallel setting. Algorithmic scalability as the problem size is scaled up will be demonstrated through novel static-scaling studies. The performed static-scaling studies can serve as a guide for users to be able to select an appropriate discretization for a given problem size.

Efficient sintering of nanocrystalline titanium dioxide films for dye solar cells via raster scanning laser

NASA Astrophysics Data System (ADS)

Mincuzzi, Girolamo; Vesce, Luigi; Reale, Andrea; Di Carlo, Aldo; Brown, Thomas M.

2009-09-01

By identifying the right combination of laser parameters, in particular the integrated laser fluence Φ, we fabricated dye solar cells (DSCs) with UV laser-sintered TiO2 films exhibiting a power conversion efficiency η =5.2%, the highest reported for laser-sintered devices. η is dramatically affected by Φ and a clear trend is reported. Significantly, DSCs fabricated by raster scanning the laser beam to sinter the TiO2 films are made as efficient as those with oven-sintered ones. These results, confirmed on three batches of cells, demonstrate the remarkable potential (noncontact, local, low cost, rapid, selective, and scalable) of scanning laser processing applied to DSC technology.

Optimising the efficiency of pulsed diode pumped Yb:YAG laser amplifiers for ns pulse generation.

PubMed

Ertel, K; Banerjee, S; Mason, P D; Phillips, P J; Siebold, M; Hernandez-Gomez, C; Collier, J C

2011-12-19

We present a numerical model of a pulsed, diode-pumped Yb:YAG laser amplifier for the generation of high energy ns-pulses. This model is used to explore how optical-to-optical efficiency depends on factors such as pump duration, pump spectrum, pump intensity, doping concentration, and operating temperature. We put special emphasis on finding ways to achieve high efficiency within the practical limitations imposed by real-world laser systems, such as limited pump brightness and limited damage fluence. We show that a particularly advantageous way of improving efficiency within those constraints is operation at cryogenic temperature. Based on the numerical findings we present a concept for a scalable amplifier based on an end-pumped, cryogenic, gas-cooled multi-slab architecture.

Optimization through satisficing with prospects

NASA Astrophysics Data System (ADS)

Oyo, Kuratomo; Takahashi, Tatsuji

2017-07-01

As the broadening scope of reinforcement learning calls for a rational and more efficient heuristics, we test a satisficing strategy named RS, based on the theory of bounded rationality that considers the limited resources in agents. In K-armed bandit problems, despite its simpler form than the previous formalization of satisficing, RS shows better-than-optimal performances when the optimal aspiration level is given. We also show that RS shows a scalability for the number of actions, K, and an adaptability in the face of an infinite number of actions. It may be an efficient means for online learning in a complex or real environments.

Efficient Measurement of Multiparticle Entanglement with Embedding Quantum Simulator.

PubMed

Chen, Ming-Cheng; Wu, Dian; Su, Zu-En; Cai, Xin-Dong; Wang, Xi-Lin; Yang, Tao; Li, Li; Liu, Nai-Le; Lu, Chao-Yang; Pan, Jian-Wei

2016-02-19

The quantum measurement of entanglement is a demanding task in the field of quantum information. Here, we report the direct and scalable measurement of multiparticle entanglement with embedding photonic quantum simulators. In this embedding framework [R. Di Candia et al. Phys. Rev. Lett. 111, 240502 (2013)], the N-qubit entanglement, which does not associate with a physical observable directly, can be efficiently measured with only two (for even N) and six (for odd N) local measurement settings. Our experiment uses multiphoton quantum simulators to mimic dynamical concurrence and three-tangle entangled systems and to track their entanglement evolutions.

A Fast parallel tridiagonal algorithm for a class of CFD applications

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Sun, Xian-He

1996-01-01

The parallel diagonal dominant (PDD) algorithm is an efficient tridiagonal solver. This paper presents for study a variation of the PDD algorithm, the reduced PDD algorithm. The new algorithm maintains the minimum communication provided by the PDD algorithm, but has a reduced operation count. The PDD algorithm also has a smaller operation count than the conventional sequential algorithm for many applications. Accuracy analysis is provided for the reduced PDD algorithm for symmetric Toeplitz tridiagonal (STT) systems. Implementation results on Langley's Intel Paragon and IBM SP2 show that both the PDD and reduced PDD algorithms are efficient and scalable.

Electrondriven processes in polyatomic molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKoy, Vincent

2017-03-20

This project developed and applied scalable computational methods to obtain information about low-energy electron collisions with larger polyatomic molecules. Such collisions are important in modeling radiation damage to living systems, in spark ignition and combustion, and in plasma processing of materials. The focus of the project was to develop efficient methods that could be used to obtain both fundamental scientific insights and data of practical value to applications.

Time domain topology optimization of 3D nanophotonic devices

NASA Astrophysics Data System (ADS)

Elesin, Y.; Lazarov, B. S.; Jensen, J. S.; Sigmund, O.

2014-02-01

We present an efficient parallel topology optimization framework for design of large scale 3D nanophotonic devices. The code shows excellent scalability and is demonstrated for optimization of broadband frequency splitter, waveguide intersection, photonic crystal-based waveguide and nanowire-based waveguide. The obtained results are compared to simplified 2D studies and we demonstrate that 3D topology optimization may lead to significant performance improvements.

Novel and Efficient Synthesis of the Promising Drug Candidate Discodermolide

DTIC Science & Technology

2010-02-01

stereotriad building blocks for discodermolide and related polyketide antibiotics could be obtained from variations on a short, scalable scheme that did...chains required for the chemical synthesis of the nonaromatic polyketides is usually based on the iterative lengthening of an acyclic substituted chain...burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense

Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiu, Dongbin

2017-03-03

The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.

Recent advances in superconducting nanowire single photon detectors for single-photon imaging

NASA Astrophysics Data System (ADS)

Verma, V. B.; Allman, M. S.; Stevens, M.; Gerrits, T.; Horansky, R. D.; Lita, A. E.; Marsili, F.; Beyer, A.; Shaw, M. D.; Stern, J. A.; Mirin, R. P.; Nam, S. W.

2016-05-01

We demonstrate a 64-pixel free-space-coupled array of superconducting nanowire single photon detectors optimized for high detection efficiency in the near-infrared range. An integrated, readily scalable, multiplexed readout scheme is employed to reduce the number of readout lines to 16. The cryogenic, optical, and electronic packaging to read out the array, as well as characterization measurements are discussed.

Enabling Service Discovery in a Federation of Systems: WS-Discovery Case Study

DTIC Science & Technology

2014-06-01

found that Pastry [3] coupled with SCRIBE [4] provides everything we require from the overlay network: Pastry nodes form a decentralized, self...application-independent manner. Furthermore, Pastry provides mechanisms that support and facilitate application-specific object replication, caching, and fault...recovery. Add SCRIBE to Pastry , and you get a generic, scalable and efficient group communication and event notification system providing

Conclusion (The Mobile Future)

NASA Astrophysics Data System (ADS)

Marcus, Aaron; Sala, Riccardo; Roibás, Anxo Cereijo

There are a couple of fundamental beliefs that I hold about the future of technology and media. First, I believe that, absolutely, most, if not all, media will be delivered, at least intermittently in its lifecycle, over an IP network. It is an efficient carrier, it is scalable, and it can be organically evolved. Whether this is IPV6 or some other technology is inconsequential, it will just work.

JobCenter: an open source, cross-platform, and distributed job queue management system optimized for scalability and versatility.

PubMed

Jaschob, Daniel; Riffle, Michael

2012-07-30

Laboratories engaged in computational biology or bioinformatics frequently need to run lengthy, multistep, and user-driven computational jobs. Each job can tie up a computer for a few minutes to several days, and many laboratories lack the expertise or resources to build and maintain a dedicated computer cluster. JobCenter is a client-server application and framework for job management and distributed job execution. The client and server components are both written in Java and are cross-platform and relatively easy to install. All communication with the server is client-driven, which allows worker nodes to run anywhere (even behind external firewalls or "in the cloud") and provides inherent load balancing. Adding a worker node to the worker pool is as simple as dropping the JobCenter client files onto any computer and performing basic configuration, which provides tremendous ease-of-use, flexibility, and limitless horizontal scalability. Each worker installation may be independently configured, including the types of jobs it is able to run. Executed jobs may be written in any language and may include multistep workflows. JobCenter is a versatile and scalable distributed job management system that allows laboratories to very efficiently distribute all computational work among available resources. JobCenter is freely available at http://code.google.com/p/jobcenter/.

Scalable microcarrier-based manufacturing of mesenchymal stem/stromal cells.

PubMed

de Soure, António M; Fernandes-Platzgummer, Ana; da Silva, Cláudia L; Cabral, Joaquim M S

2016-10-20

Due to their unique features, mesenchymal stem/stromal cells (MSC) have been exploited in clinical settings as therapeutic candidates for the treatment of a variety of diseases. However, the success in obtaining clinically-relevant MSC numbers for cell-based therapies is dependent on efficient isolation and ex vivo expansion protocols, able to comply with good manufacturing practices (GMP). In this context, the 2-dimensional static culture systems typically used for the expansion of these cells present several limitations that may lead to reduced cell numbers and compromise cell functions. Furthermore, many studies in the literature report the expansion of MSC using fetal bovine serum (FBS)-supplemented medium, which has been critically rated by regulatory agencies. Alternative platforms for the scalable manufacturing of MSC have been developed, namely using microcarriers in bioreactors, with also a considerable number of studies now reporting the production of MSC using xenogeneic/serum-free medium formulations. In this review we provide a comprehensive overview on the scalable manufacturing of human mesenchymal stem/stromal cells, depicting the various steps involved in the process from cell isolation to ex vivo expansion, using different cell tissue sources and culture medium formulations and exploiting bioprocess engineering tools namely microcarrier technology and bioreactors. Copyright © 2016 Elsevier B.V. All rights reserved.

A Fast Approximate Algorithm for Mapping Long Reads to Large Reference Databases.

PubMed

Jain, Chirag; Dilthey, Alexander; Koren, Sergey; Aluru, Srinivas; Phillippy, Adam M

2018-04-30

Emerging single-molecule sequencing technologies from Pacific Biosciences and Oxford Nanopore have revived interest in long-read mapping algorithms. Alignment-based seed-and-extend methods demonstrate good accuracy, but face limited scalability, while faster alignment-free methods typically trade decreased precision for efficiency. In this article, we combine a fast approximate read mapping algorithm based on minimizers with a novel MinHash identity estimation technique to achieve both scalability and precision. In contrast to prior methods, we develop a mathematical framework that defines the types of mapping targets we uncover, establish probabilistic estimates of p-value and sensitivity, and demonstrate tolerance for alignment error rates up to 20%. With this framework, our algorithm automatically adapts to different minimum length and identity requirements and provides both positional and identity estimates for each mapping reported. For mapping human PacBio reads to the hg38 reference, our method is 290 × faster than Burrows-Wheeler Aligner-MEM with a lower memory footprint and recall rate of 96%. We further demonstrate the scalability of our method by mapping noisy PacBio reads (each ≥5 kbp in length) to the complete NCBI RefSeq database containing 838 Gbp of sequence and >60,000 genomes.

Scalable and sustainable electrochemical allylic C-H oxidation

NASA Astrophysics Data System (ADS)

Horn, Evan J.; Rosen, Brandon R.; Chen, Yong; Tang, Jiaze; Chen, Ke; Eastgate, Martin D.; Baran, Phil S.

2016-05-01

New methods and strategies for the direct functionalization of C-H bonds are beginning to reshape the field of retrosynthetic analysis, affecting the synthesis of natural products, medicines and materials. The oxidation of allylic systems has played a prominent role in this context as possibly the most widely applied C-H functionalization, owing to the utility of enones and allylic alcohols as versatile intermediates, and their prevalence in natural and unnatural materials. Allylic oxidations have featured in hundreds of syntheses, including some natural product syntheses regarded as “classics”. Despite many attempts to improve the efficiency and practicality of this transformation, the majority of conditions still use highly toxic reagents (based around toxic elements such as chromium or selenium) or expensive catalysts (such as palladium or rhodium). These requirements are problematic in industrial settings; currently, no scalable and sustainable solution to allylic oxidation exists. This oxidation strategy is therefore rarely used for large-scale synthetic applications, limiting the adoption of this retrosynthetic strategy by industrial scientists. Here we describe an electrochemical C-H oxidation strategy that exhibits broad substrate scope, operational simplicity and high chemoselectivity. It uses inexpensive and readily available materials, and represents a scalable allylic C-H oxidation (demonstrated on 100 grams), enabling the adoption of this C-H oxidation strategy in large-scale industrial settings without substantial environmental impact.

Scalable Method to Produce Biodegradable Nanoparticles that Rapidly Penetrate Human Mucus

PubMed Central

Xu, Qingguo; Boylan, Nicholas J.; Cai, Shutian; Miao, Bolong; Patel, Himatkumar; Hanes, Justin

2013-01-01

Mucus typically traps and rapidly removes foreign particles from the airways, gastrointestinal tract, nasopharynx, female reproductive tract and the surface of the eye. Nanoparticles capable of rapid penetration through mucus can potentially avoid rapid clearance, and open significant opportunities for controlled drug delivery at mucosal surfaces. Here, we report an industrially scalable emulsification method to produce biodegradable mucus-penetrating particles (MPP). The emulsification of diblock copolymers of poly(lactic-co-glycolic acid) and polyethylene glycol (PLGA-PEG) using low molecular weight (MW) emulsifiers forms dense brush PEG coatings on nanoparticles that allow rapid nanoparticle penetration through fresh undiluted human mucus. In comparison, conventional high MW emulsifiers, such as polyvinyl alcohol (PVA), interrupts the PEG coating on nanoparticles, resulting in their immobilization in mucus owing to adhesive interactions with mucus mesh elements. PLGA-PEG nanoparticles with a wide range of PEG MW (1, 2, 5, and 10 kDa), prepared by the emulsification method using low MW emulsifiers, all rapidly penetrated mucus. A range of drugs, from hydrophobic small molecules to hydrohilic large biologics, can be efficiently loaded into biodegradable MPP using the method described. This readily scalable method should facilitate the production of MPP products for mucosal drug delivery, as well as potentially longer-circulating particles following intravenous administration. PMID:23751567

Integrated spatial multiplexing of heralded single-photon sources

PubMed Central

Collins, M.J.; Xiong, C.; Rey, I.H.; Vo, T.D.; He, J.; Shahnia, S.; Reardon, C.; Krauss, T.F.; Steel, M.J.; Clark, A.S.; Eggleton, B.J.

2013-01-01

The non-deterministic nature of photon sources is a key limitation for single-photon quantum processors. Spatial multiplexing overcomes this by enhancing the heralded single-photon yield without enhancing the output noise. Here the intrinsic statistical limit of an individual source is surpassed by spatially multiplexing two monolithic silicon-based correlated photon pair sources in the telecommunications band, demonstrating a 62.4% increase in the heralded single-photon output without an increase in unwanted multipair generation. We further demonstrate the scalability of this scheme by multiplexing photons generated in two waveguides pumped via an integrated coupler with a 63.1% increase in the heralded photon rate. This demonstration paves the way for a scalable architecture for multiplexing many photon sources in a compact integrated platform and achieving efficient two-photon interference, required at the core of optical quantum computing and quantum communication protocols. PMID:24107840

Highly aligned arrays of high aspect ratio barium titanate nanowires via hydrothermal synthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowland, Christopher C.; Zhou, Zhi; Malakooti, Mohammad H.

2015-06-01

We report on the development of a hydrothermal synthesis procedure that results in the growth of highly aligned arrays of high aspect ratio barium titanate nanowires. Using a multiple step, scalable hydrothermal reaction, a textured titanium dioxide film is deposited on titanium foil upon which highly aligned nanowires are grown via homoepitaxy and converted to barium titanate. Scanning electron microscope images clearly illustrate the effect the textured film has on the degree of orientation of the nanowires. The alignment of nanowires is quantified by calculating the Herman's Orientation Factor, which reveals a 58% improvement in orientation as compared to growthmore » in the absence of the textured film. The ferroelectric properties of barium titanate combined with the development of this scalable growth procedure provide a powerful route towards increasing the efficiency and performance of nanowire-based devices in future real-world applications such as sensing and power harvesting.« less

Job Scheduling in a Heterogeneous Grid Environment

NASA Technical Reports Server (NTRS)

Shan, Hong-Zhang; Smith, Warren; Oliker, Leonid; Biswas, Rupak

2004-01-01

Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.

Demonstration of Scalable Nernst Voltage in a Coiled Galfenol Wire

NASA Astrophysics Data System (ADS)

Codecido, Emilio; Yang, Zihao; Marquez, Jason; Zheng, Yuanhua; Heremans, Joseph; Myers, Roberto

Transverse thermopower by the Nernst effect is usually considered far too weak an effect for waste heat recovery and power generation. We propose that magnetostriction provides a pathway to enhance the Nernst effect because it increases phonon and magnon coupling. Here, we measure the Nernst coefficient in the magnetostrictive alloy, Galfenol (Fe0.85Ga0.15) and observe an extraordinarily large Nernst coefficient at room temperature of 4 μV/KT. Next we demonstrate a new geometry for efficient and low cost power generation by wrapping Galfenol wire around a hot cylinder. This coil geometry results in a radial temperature gradient direction. With a magnetic field applied in the axial direction, a uniform Nernst electric field is produced along the azimuthal direction at every point along the coil. As a result of this geometry, the Nernst voltage is shown to increase linearly with wire length, proving the concept of scalable Nernst thermal power generation.

Deterministic strain-induced arrays of quantum emitters in a two-dimensional semiconductor

PubMed Central

Branny, Artur; Kumar, Santosh; Proux, Raphaël; Gerardot, Brian D

2017-01-01

An outstanding challenge in quantum photonics is scalability, which requires positioning of single quantum emitters in a deterministic fashion. Site positioning progress has been made in established platforms including defects in diamond and self-assembled quantum dots, albeit often with compromised coherence and optical quality. The emergence of single quantum emitters in layered transition metal dichalcogenide semiconductors offers new opportunities to construct a scalable quantum architecture. Here, using nanoscale strain engineering, we deterministically achieve a two-dimensional lattice of quantum emitters in an atomically thin semiconductor. We create point-like strain perturbations in mono- and bi-layer WSe2 which locally modify the band-gap, leading to efficient funnelling of excitons towards isolated strain-tuned quantum emitters that exhibit high-purity single photon emission. We achieve near unity emitter creation probability and a mean positioning accuracy of 120±32 nm, which may be improved with further optimization of the nanopillar dimensions. PMID:28530219

Implementation of the semiclassical quantum Fourier transform in a scalable system.

PubMed

Chiaverini, J; Britton, J; Leibfried, D; Knill, E; Barrett, M D; Blakestad, R B; Itano, W M; Jost, J D; Langer, C; Ozeri, R; Schaetz, T; Wineland, D J

2005-05-13

We report the implementation of the semiclassical quantum Fourier transform in a system of three beryllium ion qubits (two-level quantum systems) confined in a segmented multizone trap. The quantum Fourier transform is the crucial final step in Shor's algorithm, and it acts on a register of qubits to determine the periodicity of the quantum state's amplitudes. Because only probability amplitudes are required for this task, a more efficient semiclassical version can be used, for which only single-qubit operations conditioned on measurement outcomes are required. We apply the transform to several input states of different periodicities; the results enable the location of peaks corresponding to the original periods. This demonstration incorporates the key elements of a scalable ion-trap architecture, suggesting the future capability of applying the quantum Fourier transform to a large number of qubits as required for a useful quantum factoring algorithm.

Distributed Cognition and Process Management Enabling Individualized Translational Research: The NIH Undiagnosed Diseases Program Experience

PubMed Central

Links, Amanda E.; Draper, David; Lee, Elizabeth; Guzman, Jessica; Valivullah, Zaheer; Maduro, Valerie; Lebedev, Vlad; Didenko, Maxim; Tomlin, Garrick; Brudno, Michael; Girdea, Marta; Dumitriu, Sergiu; Haendel, Melissa A.; Mungall, Christopher J.; Smedley, Damian; Hochheiser, Harry; Arnold, Andrew M.; Coessens, Bert; Verhoeven, Steven; Bone, William; Adams, David; Boerkoel, Cornelius F.; Gahl, William A.; Sincan, Murat

2016-01-01

The National Institutes of Health Undiagnosed Diseases Program (NIH UDP) applies translational research systematically to diagnose patients with undiagnosed diseases. The challenge is to implement an information system enabling scalable translational research. The authors hypothesized that similar complex problems are resolvable through process management and the distributed cognition of communities. The team, therefore, built the NIH UDP integrated collaboration system (UDPICS) to form virtual collaborative multidisciplinary research networks or communities. UDPICS supports these communities through integrated process management, ontology-based phenotyping, biospecimen management, cloud-based genomic analysis, and an electronic laboratory notebook. UDPICS provided a mechanism for efficient, transparent, and scalable translational research and thereby addressed many of the complex and diverse research and logistical problems of the NIH UDP. Full definition of the strengths and deficiencies of UDPICS will require formal qualitative and quantitative usability and process improvement measurement. PMID:27785453

Strategic redox relay enables a scalable synthesis of ouabagenin, a bioactive cardenolide.

PubMed

Renata, Hans; Zhou, Qianghui; Baran, Phil S

2013-01-04

Here, we report on a scalable route to the polyhydroxylated steroid ouabagenin with an unusual take on the age-old practice of steroid semisynthesis. The incorporation of both redox and stereochemical relays during the design of this synthesis resulted in efficient access to more than 500 milligrams of a key precursor toward ouabagenin-and ultimately ouabagenin itself-and the discovery of innovative methods for carbon-hydrogen (C-H) and carbon-carbon activation and carbon-oxygen bond homolysis. Given the medicinal relevance of the cardenolides in the treatment of congestive heart failure, a variety of ouabagenin analogs could potentially be generated from the key intermediate as a means of addressing the narrow therapeutic index of these molecules. This synthesis also showcases an approach to bypass the historically challenging problem of selective C-H oxidation of saturated carbon centers in a controlled fashion.

Emergent Adaptive Noise Reduction from Communal Cooperation of Sensor Grid

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Jones, Michael G.; Nark, Douglas M.; Lodding, Kenneth N.

2010-01-01

In the last decade, the realization of small, inexpensive, and powerful devices with sensors, computers, and wireless communication has promised the development of massive sized sensor networks with dense deployments over large areas capable of high fidelity situational assessments. However, most management models have been based on centralized control and research has concentrated on methods for passing data from sensor devices to the central controller. Most implementations have been small but, as it is not scalable, this methodology is insufficient for massive deployments. Here, a specific application of a large sensor network for adaptive noise reduction demonstrates a new paradigm where communities of sensor/computer devices assess local conditions and make local decisions from which emerges a global behaviour. This approach obviates many of the problems of centralized control as it is not prone to single point of failure and is more scalable, efficient, robust, and fault tolerant

Scalable Lunar Surface Networks and Adaptive Orbit Access

NASA Technical Reports Server (NTRS)

Wang, Xudong

2015-01-01

Teranovi Technologies, Inc., has developed innovative network architecture, protocols, and algorithms for both lunar surface and orbit access networks. A key component of the overall architecture is a medium access control (MAC) protocol that includes a novel mechanism of overlaying time division multiple access (TDMA) and carrier sense multiple access with collision avoidance (CSMA/CA), ensuring scalable throughput and quality of service. The new MAC protocol is compatible with legacy Institute of Electrical and Electronics Engineers (IEEE) 802.11 networks. Advanced features include efficiency power management, adaptive channel width adjustment, and error control capability. A hybrid routing protocol combines the advantages of ad hoc on-demand distance vector (AODV) routing and disruption/delay-tolerant network (DTN) routing. Performance is significantly better than AODV or DTN and will be particularly effective for wireless networks with intermittent links, such as lunar and planetary surface networks and orbit access networks.

Antibody Production in Plants and Green Algae.

PubMed

Yusibov, Vidadi; Kushnir, Natasha; Streatfield, Stephen J

2016-04-29

Monoclonal antibodies (mAbs) have a wide range of modern applications, including research, diagnostic, therapeutic, and industrial uses. Market demand for mAbs is high and continues to grow. Although mammalian systems, which currently dominate the biomanufacturing industry, produce effective and safe recombinant mAbs, they have a limited manufacturing capacity and high costs. Bacteria, yeast, and insect cell systems are highly scalable and cost effective but vary in their ability to produce appropriate posttranslationally modified mAbs. Plants and green algae are emerging as promising production platforms because of their time and cost efficiencies, scalability, lack of mammalian pathogens, and eukaryotic posttranslational protein modification machinery. So far, plant- and algae-derived mAbs have been produced predominantly as candidate therapeutics for infectious diseases and cancer. These candidates have been extensively evaluated in animal models, and some have shown efficacy in clinical trials. Here, we review ongoing efforts to advance the production of mAbs in plants and algae.

Functional Two-Dimensional Coordination Polymeric Layer as a Charge Barrier in Li-S Batteries.

PubMed

Huang, Jing-Kai; Li, Mengliu; Wan, Yi; Dey, Sukumar; Ostwal, Mayur; Zhang, Daliang; Yang, Chih-Wen; Su, Chun-Jen; Jeng, U-Ser; Ming, Jun; Amassian, Aram; Lai, Zhiping; Han, Yu; Li, Sean; Li, Lain-Jong

2018-01-23

Ultrathin two-dimensional (2D) polymeric layers are capable of separating gases and molecules based on the reported size exclusion mechanism. What is equally important but missing today is an exploration of the 2D layers with charge functionality, which enables applications using the charge exclusion principle. This work demonstrates a simple and scalable method of synthesizing a free-standing 2D coordination polymer Zn 2 (benzimidazolate) 2 (OH) 2 at the air-water interface. The hydroxyl (-OH) groups are stoichiometrically coordinated and implement electrostatic charges in the 2D structures, providing powerful functionality as a charge barrier. Electrochemical performance of the Li-S battery shows that the Zn 2 (benzimidazolate) 2 (OH) 2 coordination polymer layers efficiently mitigate the polysulfide shuttling effects and largely enhance the battery capacity and cycle performance. The synthesis of the proposed coordination polymeric layers is simple, scalable, cost saving, and promising for practical use in batteries.

Scalable Faceted Ranking in Tagging Systems

NASA Astrophysics Data System (ADS)

Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

Parallel multigrid smoothing: polynomial versus Gauss-Seidel

NASA Astrophysics Data System (ADS)

Adams, Mark; Brezina, Marian; Hu, Jonathan; Tuminaro, Ray

2003-07-01

Gauss-Seidel is often the smoother of choice within multigrid applications. In the context of unstructured meshes, however, maintaining good parallel efficiency is difficult with multiplicative iterative methods such as Gauss-Seidel. This leads us to consider alternative smoothers. We discuss the computational advantages of polynomial smoothers within parallel multigrid algorithms for positive definite symmetric systems. Two particular polynomials are considered: Chebyshev and a multilevel specific polynomial. The advantages of polynomial smoothing over traditional smoothers such as Gauss-Seidel are illustrated on several applications: Poisson's equation, thin-body elasticity, and eddy current approximations to Maxwell's equations. While parallelizing the Gauss-Seidel method typically involves a compromise between a scalable convergence rate and maintaining high flop rates, polynomial smoothers achieve parallel scalable multigrid convergence rates without sacrificing flop rates. We show that, although parallel computers are the main motivation, polynomial smoothers are often surprisingly competitive with Gauss-Seidel smoothers on serial machines.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

PubMed

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

Feasibility of Using Distributed Wireless Mesh Networks for Medical Emergency Response

PubMed Central

Braunstein, Brian; Trimble, Troy; Mishra, Rajesh; Manoj, B. S.; Rao, Ramesh; Lenert, Leslie

2006-01-01

Achieving reliable, efficient data communications networks at a disaster site is a difficult task. Network paradigms, such as Wireless Mesh Network (WMN) architectures, form one exemplar for providing high-bandwidth, scalable data communication for medical emergency response activity. WMNs are created by self-organized wireless nodes that use multi-hop wireless relaying for data transfer. In this paper, we describe our experience using a mesh network architecture we developed for homeland security and medical emergency applications. We briefly discuss the architecture and present the traffic behavioral observations made by a client-server medical emergency application tested during a large-scale homeland security drill. We present our traffic measurements, describe lessons learned, and offer functional requirements (based on field testing) for practical 802.11 mesh medical emergency response networks. With certain caveats, the results suggest that 802.11 mesh networks are feasible and scalable systems for field communications in disaster settings. PMID:17238308

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems.

PubMed

Niethammer, Christoph; Becker, Stefan; Bernreuther, Martin; Buchholz, Martin; Eckhardt, Wolfgang; Heinecke, Alexander; Werth, Stephan; Bungartz, Hans-Joachim; Glass, Colin W; Hasse, Hans; Vrabec, Jadran; Horsch, Martin

2014-10-14

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

Scalability, Scintillation Readout and Charge Drift in a Kilogram Scale Solid Xenon Particle Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, J.; Cease, H.; Jaskierny, W. F.

2014-10-23

We report a demonstration of the scalability of optically transparent xenon in the solid phase for use as a particle detector above a kilogram scale. We employ a liquid nitrogen cooled cryostat combined with a xenon purification and chiller system to measure the scintillation light output and electron drift speed from both the solid and liquid phases of xenon. Scintillation light output from sealed radioactive sources is measured by a set of high quantum efficiency photomultiplier tubes suitable for cryogenic applications. We observed a reduced amount of photons in solid phase compared to that in liquid phase. We used amore » conventional time projection chamber system to measure the electron drift time in a kilogram of solid xenon and observed faster electron drift speed in the solid phase xenon compared to that in the liquid phase.« less

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

NASA Astrophysics Data System (ADS)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Facile approach to prepare Pt decorated SWNT/graphene hybrid catalytic ink

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayavan, Sundar, E-mail: sundarmayavan@cecri.res.in; Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701; Mandalam, Aditya

Highlights: • Pt NPs were in situ synthesized onto CNT–graphene support in aqueous solution. • The as-prepared material was used directly as a catalyst ink without further treatment. • Catalyst ink is active toward methanol oxidation. • This approach realizes both scalable and greener production of hybrid catalysts. - Abstract: Platinum nanoparticles were in situ synthesized onto hybrid support involving graphene and single walled carbon nanotube in aqueous solution. We investigate the reduction of graphene oxide, and platinum nanoparticle functionalization on hybrid support by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The as-preparedmore » platinum on hybrid support was used directly as a catalyst ink without further treatment and is active toward methanol oxidation. This work realizes both scalable and greener production of highly efficient hybrid catalysts, and would be valuable for practical applications of graphene based fuel cell catalysts.« less

Status Report on NEAMS PROTEUS/ORIGEN Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wieselquist, William A

2016-02-18

The US Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program has contributed significantly to the development of the PROTEUS neutron transport code at Argonne National Laboratory and to the Oak Ridge Isotope Generation and Depletion Code (ORIGEN) depletion/decay code at Oak Ridge National Laboratory. PROTEUS’s key capability is the efficient and scalable (up to hundreds of thousands of cores) neutron transport solver on general, unstructured, three-dimensional finite-element-type meshes. The scalability and mesh generality enable the transfer of neutron and power distributions to other codes in the NEAMS toolkit for advanced multiphysics analysis. Recently, ORIGEN has received considerablemore » modernization to provide the high-performance depletion/decay capability within the NEAMS toolkit. This work presents a description of the initial integration of ORIGEN in PROTEUS, mainly performed during FY 2015, with minor updates in FY 2016.« less

A scalable silicon photonic chip-scale optical switch for high performance computing systems.

PubMed

Yu, Runxiang; Cheung, Stanley; Li, Yuliang; Okamoto, Katsunari; Proietti, Roberto; Yin, Yawei; Yoo, S J B

2013-12-30

This paper discusses the architecture and provides performance studies of a silicon photonic chip-scale optical switch for scalable interconnect network in high performance computing systems. The proposed switch exploits optical wavelength parallelism and wavelength routing characteristics of an Arrayed Waveguide Grating Router (AWGR) to allow contention resolution in the wavelength domain. Simulation results from a cycle-accurate network simulator indicate that, even with only two transmitter/receiver pairs per node, the switch exhibits lower end-to-end latency and higher throughput at high (>90%) input loads compared with electronic switches. On the device integration level, we propose to integrate all the components (ring modulators, photodetectors and AWGR) on a CMOS-compatible silicon photonic platform to ensure a compact, energy efficient and cost-effective device. We successfully demonstrate proof-of-concept routing functions on an 8 × 8 prototype fabricated using foundry services provided by OpSIS-IME.

Learning Optimized Local Difference Binaries for Scalable Augmented Reality on Mobile Devices.

PubMed

Xin Yang; Kwang-Ting Cheng

2014-06-01

The efficiency, robustness and distinctiveness of a feature descriptor are critical to the user experience and scalability of a mobile augmented reality (AR) system. However, existing descriptors are either too computationally expensive to achieve real-time performance on a mobile device such as a smartphone or tablet, or not sufficiently robust and distinctive to identify correct matches from a large database. As a result, current mobile AR systems still only have limited capabilities, which greatly restrict their deployment in practice. In this paper, we propose a highly efficient, robust and distinctive binary descriptor, called Learning-based Local Difference Binary (LLDB). LLDB directly computes a binary string for an image patch using simple intensity and gradient difference tests on pairwise grid cells within the patch. To select an optimized set of grid cell pairs, we densely sample grid cells from an image patch and then leverage a modified AdaBoost algorithm to automatically extract a small set of critical ones with the goal of maximizing the Hamming distance between mismatches while minimizing it between matches. Experimental results demonstrate that LLDB is extremely fast to compute and to match against a large database due to its high robustness and distinctiveness. Compared to the state-of-the-art binary descriptors, primarily designed for speed, LLDB has similar efficiency for descriptor construction, while achieving a greater accuracy and faster matching speed when matching over a large database with 2.3M descriptors on mobile devices.

Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data.

PubMed

Li, Wenyuan; Gong, Ke; Li, Qingjiao; Alber, Frank; Zhou, Xianghong Jasmine

2015-03-15

Genome-wide proximity ligation assays, e.g. Hi-C and its variant TCC, have recently become important tools to study spatial genome organization. Removing biases from chromatin contact matrices generated by such techniques is a critical preprocessing step of subsequent analyses. The continuing decline of sequencing costs has led to an ever-improving resolution of the Hi-C data, resulting in very large matrices of chromatin contacts. Such large-size matrices, however, pose a great challenge on the memory usage and speed of its normalization. Therefore, there is an urgent need for fast and memory-efficient methods for normalization of Hi-C data. We developed Hi-Corrector, an easy-to-use, open source implementation of the Hi-C data normalization algorithm. Its salient features are (i) scalability-the software is capable of normalizing Hi-C data of any size in reasonable times; (ii) memory efficiency-the sequential version can run on any single computer with very limited memory, no matter how little; (iii) fast speed-the parallel version can run very fast on multiple computing nodes with limited local memory. The sequential version is implemented in ANSI C and can be easily compiled on any system; the parallel version is implemented in ANSI C with the MPI library (a standardized and portable parallel environment designed for solving large-scale scientific problems). The package is freely available at http://zhoulab.usc.edu/Hi-Corrector/. © The Author 2014. Published by Oxford University Press.

Network-aware scalable video monitoring system for emergency situations with operator-managed fidelity control

NASA Astrophysics Data System (ADS)

Al Hadhrami, Tawfik; Nightingale, James M.; Wang, Qi; Grecos, Christos

2014-05-01

In emergency situations, the ability to remotely monitor unfolding events using high-quality video feeds will significantly improve the incident commander's understanding of the situation and thereby aids effective decision making. This paper presents a novel, adaptive video monitoring system for emergency situations where the normal communications network infrastructure has been severely impaired or is no longer operational. The proposed scheme, operating over a rapidly deployable wireless mesh network, supports real-time video feeds between first responders, forward operating bases and primary command and control centers. Video feeds captured on portable devices carried by first responders and by static visual sensors are encoded in H.264/SVC, the scalable extension to H.264/AVC, allowing efficient, standard-based temporal, spatial, and quality scalability of the video. A three-tier video delivery system is proposed, which balances the need to avoid overuse of mesh nodes with the operational requirements of the emergency management team. In the first tier, the video feeds are delivered at a low spatial and temporal resolution employing only the base layer of the H.264/SVC video stream. Routing in this mode is designed to employ all nodes across the entire mesh network. In the second tier, whenever operational considerations require that commanders or operators focus on a particular video feed, a `fidelity control' mechanism at the monitoring station sends control messages to the routing and scheduling agents in the mesh network, which increase the quality of the received picture using SNR scalability while conserving bandwidth by maintaining a low frame rate. In this mode, routing decisions are based on reliable packet delivery with the most reliable routes being used to deliver the base and lower enhancement layers; as fidelity is increased and more scalable layers are transmitted they will be assigned to routes in descending order of reliability. The third tier of video delivery transmits a high-quality video stream including all available scalable layers using the most reliable routes through the mesh network ensuring the highest possible video quality. The proposed scheme is implemented in a proven simulator, and the performance of the proposed system is numerically evaluated through extensive simulations. We further present an in-depth analysis of the proposed solutions and potential approaches towards supporting high-quality visual communications in such a demanding context.

High-speed and high-efficiency travelling wave single-photon detectors embedded in nanophotonic circuits

PubMed Central

Pernice, W.H.P.; Schuck, C.; Minaeva, O.; Li, M.; Goltsman, G.N.; Sergienko, A.V.; Tang, H.X.

2012-01-01

Ultrafast, high-efficiency single-photon detectors are among the most sought-after elements in modern quantum optics and quantum communication. However, imperfect modal matching and finite photon absorption rates have usually limited their maximum attainable detection efficiency. Here we demonstrate superconducting nanowire detectors atop nanophotonic waveguides, which enable a drastic increase of the absorption length for incoming photons. This allows us to achieve high on-chip single-photon detection efficiency up to 91% at telecom wavelengths, repeatable across several fabricated chips. We also observe remarkably low dark count rates without significant compromise of the on-chip detection efficiency. The detectors are fully embedded in scalable silicon photonic circuits and provide ultrashort timing jitter of 18 ps. Exploiting this high temporal resolution, we demonstrate ballistic photon transport in silicon ring resonators. Our direct implementation of a high-performance single-photon detector on chip overcomes a major barrier in integrated quantum photonics. PMID:23271658

Polyvinylpyrrolidone (PVP)-Capped Pt Nanocubes with Superior Peroxidase-Like Activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ye, Haihang; Liu, Yuzi; Chhabra, Ashima

2016-12-21

Peroxidase mimics of inorganic nanoparticles are expected to circumvent the inherent issues of natural peroxidases, providing enhanced performance in important applications such as diagnosis and imaging. Despite the report of a variety of peroxidase mimics in the past decade, very limited progress has been made on improving their catalytic efficiency. The catalytic efficiencies of most previously reported mimics are only up to one order of magnitude higher than those of natural peroxidases. In this work, we demonstrate a type of highly efficient peroxidase mimic – polyvinylpyrrolidone (PVP)-capped Pt nanocubes of sub-10 nm in size. These PVP-capped Pt cubes are ~200-foldmore » more active than the natural counterparts and exhibit a record-high specific catalytic efficiency. In addition to the superior efficiency, the new mimic shows several other promising features, including excellent stabilities, well-controlled uniformity in both size and shape, controllable sizes, and facile and scalable production.« less

[Congenital ChagaśDisease: epidemiology, laboratorial diagnosis, prognosis and treatment].

PubMed

Reiche, E M; Inouye, M M; Bonametti, A M; Jankevicius, J V

1996-01-01

The authors review studies about epidemiology, clinical aspects and methods used in laboratorial diagnosis of congenital Chagas'disease, emphasizing the limitations in their specificity and sensibility, and suggest alternative methods to improve the accuracy and the quality of the laboratorial diagnosis of congenital Chagaśdisease, essential to an efficient treatment.

Highly scalable, resonantly cladding-pumped, Er-doped fiber laser with record efficiency.

PubMed

Dubinskii, M; Zhang, J; Ter-Mikirtychev, V

2009-05-15

We report the performance of a resonantly cladding-pumped, Yb-free, Er-doped fiber laser. We believe this is the first reported resonantly cladding-pumped fiber-Bragg-grating-based, Er-doped, large-mode-area (LMA) fiber laser. The laser, pumped by fiber-coupled InGaAsP/InP laser diode modules at 1,532.5 nm, delivers approximately 48 W of cw output at 1,590 nm. It is believed to be the highest power ever reported from a Yb-free Er-doped LMA fiber. This fully integrated laser also has the optical-to-optical efficiency of approximately 57%, to the best of our knowledge, the highest efficiency reported for cladding-pumped unidirectionally emitting Er-doped laser.

Making Spatial Statistics Service Accessible On Cloud Platform

NASA Astrophysics Data System (ADS)

Mu, X.; Wu, J.; Li, T.; Zhong, Y.; Gao, X.

2014-04-01

Web service can bring together applications running on diverse platforms, users can access and share various data, information and models more effectively and conveniently from certain web service platform. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With the rampant growth of massive data and restriction of net, traditional web services platforms have some prominent problems existing in development such as calculation efficiency, maintenance cost and data security. In this paper, we offer a spatial statistics service based on Microsoft cloud. An experiment was carried out to evaluate the availability and efficiency of this service. The results show that this spatial statistics service is accessible for the public conveniently with high processing efficiency.

Video streaming with SHVC to HEVC transcoding

NASA Astrophysics Data System (ADS)

Gudumasu, Srinivas; He, Yuwen; Ye, Yan; Xiu, Xiaoyu

2015-09-01

This paper proposes an efficient Scalable High efficiency Video Coding (SHVC) to High Efficiency Video Coding (HEVC) transcoder, which can reduce the transcoding complexity significantly, and provide a desired trade-off between the transcoding complexity and the transcoded video quality. To reduce the transcoding complexity, some of coding information, such as coding unit (CU) depth, prediction mode, merge mode, motion vector information, intra direction information and transform unit (TU) depth information, in the SHVC bitstream are mapped and transcoded to single layer HEVC bitstream. One major difficulty in transcoding arises when trying to reuse the motion information from SHVC bitstream since motion vectors referring to inter-layer reference (ILR) pictures cannot be reused directly in transcoding. Reusing motion information obtained from ILR pictures for those prediction units (PUs) will reduce the complexity of the SHVC transcoder greatly but a significant reduction in the quality of the picture is observed. Pictures corresponding to the intra refresh pictures in the base layer (BL) will be coded as P pictures in enhancement layer (EL) in the SHVC bitstream; and directly reusing the intra information from the BL for transcoding will not get a good coding efficiency. To solve these problems, various transcoding technologies are proposed. The proposed technologies offer different trade-offs between transcoding speed and transcoding quality. They are implemented on the basis of reference software SHM-6.0 and HM-14.0 for the two layer spatial scalability configuration. Simulations show that the proposed SHVC software transcoder reduces the transcoding complexity by up to 98-99% using low complexity transcoding mode when compared with cascaded re-encoding method. The transcoder performance at various bitrates with different transcoding modes are compared in terms of transcoding speed and transcoded video quality.

From field notes to data portal - An operational QA/QC framework for tower networks

NASA Astrophysics Data System (ADS)

Sturtevant, C.; Hackley, S.; Meehan, T.; Roberti, J. A.; Holling, G.; Bonarrigo, S.

2016-12-01

Quality assurance and control (QA/QC) is one of the most important yet challenging aspects of producing research-quality data. This is especially so for environmental sensor networks collecting numerous high-frequency measurement streams at distributed sites. Here, the quality issues are multi-faceted, including sensor malfunctions, unmet theoretical assumptions, and measurement interference from the natural environment. To complicate matters, there are often multiple personnel managing different sites or different steps in the data flow. For large, centrally managed sensor networks such as NEON, the separation of field and processing duties is in the extreme. Tower networks such as Ameriflux, ICOS, and NEON continue to grow in size and sophistication, yet tools for robust, efficient, scalable QA/QC have lagged. Quality control remains a largely manual process relying on visual inspection of the data. In addition, notes of observed measurement interference or visible problems are often recorded on paper without an explicit pathway to data flagging during processing. As such, an increase in network size requires a near-proportional increase in personnel devoted to QA/QC, quickly stressing the human resources available. There is a need for a scalable, operational QA/QC framework that combines the efficiency and standardization of automated tests with the power and flexibility of visual checks, and includes an efficient communication pathway from field personnel to data processors to end users. Here we propose such a framework and an accompanying set of tools in development, including a mobile application template for recording tower maintenance and an R/shiny application for efficiently monitoring and synthesizing data quality issues. This framework seeks to incorporate lessons learned from the Ameriflux community and provide tools to aid continued network advancements.

Highly Efficient and Scalable Compound Decomposition of Two-Electron Integral Tensor and Its Application in Coupled Cluster Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng, Bo; Kowalski, Karol

The representation and storage of two-electron integral tensors are vital in large- scale applications of accurate electronic structure methods. Low-rank representation and efficient storage strategy of integral tensors can significantly reduce the numerical overhead and consequently time-to-solution of these methods. In this paper, by combining pivoted incomplete Cholesky decomposition (CD) with a follow-up truncated singular vector decomposition (SVD), we develop a decomposition strategy to approximately represent the two-electron integral tensor in terms of low-rank vectors. A systematic benchmark test on a series of 1-D, 2-D, and 3-D carbon-hydrogen systems demonstrates high efficiency and scalability of the compound two-step decomposition ofmore » the two-electron integral tensor in our implementation. For the size of atomic basis set N_b ranging from ~ 100 up to ~ 2, 000, the observed numerical scaling of our implementation shows O(N_b^{2.5~3}) versus O(N_b^{3~4}) of single CD in most of other implementations. More importantly, this decomposition strategy can significantly reduce the storage requirement of the atomic-orbital (AO) two-electron integral tensor from O(N_b^4) to O(N_b^2 log_{10}(N_b)) with moderate decomposition thresholds. The accuracy tests have been performed using ground- and excited-state formulations of coupled- cluster formalism employing single and double excitations (CCSD) on several bench- mark systems including the C_{60} molecule described by nearly 1,400 basis functions. The results show that the decomposition thresholds can be generally set to 10^{-4} to 10^{-3} to give acceptable compromise between efficiency and accuracy.« less

An efficient and scalable graph modeling approach for capturing information at different levels in next generation sequencing reads

PubMed Central

2013-01-01

Background Next generation sequencing technologies have greatly advanced many research areas of the biomedical sciences through their capability to generate massive amounts of genetic information at unprecedented rates. The advent of next generation sequencing has led to the development of numerous computational tools to analyze and assemble the millions to billions of short sequencing reads produced by these technologies. While these tools filled an important gap, current approaches for storing, processing, and analyzing short read datasets generally have remained simple and lack the complexity needed to efficiently model the produced reads and assemble them correctly. Results Previously, we presented an overlap graph coarsening scheme for modeling read overlap relationships on multiple levels. Most current read assembly and analysis approaches use a single graph or set of clusters to represent the relationships among a read dataset. Instead, we use a series of graphs to represent the reads and their overlap relationships across a spectrum of information granularity. At each information level our algorithm is capable of generating clusters of reads from the reduced graph, forming an integrated graph modeling and clustering approach for read analysis and assembly. Previously we applied our algorithm to simulated and real 454 datasets to assess its ability to efficiently model and cluster next generation sequencing data. In this paper we extend our algorithm to large simulated and real Illumina datasets to demonstrate that our algorithm is practical for both sequencing technologies. Conclusions Our overlap graph theoretic algorithm is able to model next generation sequencing reads at various levels of granularity through the process of graph coarsening. Additionally, our model allows for efficient representation of the read overlap relationships, is scalable for large datasets, and is practical for both Illumina and 454 sequencing technologies. PMID:24564333

A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

NASA Astrophysics Data System (ADS)

Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

2017-08-01

Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

Highly Efficient and Scalable Compound Decomposition of Two-Electron Integral Tensor and Its Application in Coupled Cluster Calculations.

PubMed

Peng, Bo; Kowalski, Karol

2017-09-12

The representation and storage of two-electron integral tensors are vital in large-scale applications of accurate electronic structure methods. Low-rank representation and efficient storage strategy of integral tensors can significantly reduce the numerical overhead and consequently time-to-solution of these methods. In this work, by combining pivoted incomplete Cholesky decomposition (CD) with a follow-up truncated singular vector decomposition (SVD), we develop a decomposition strategy to approximately represent the two-electron integral tensor in terms of low-rank vectors. A systematic benchmark test on a series of 1-D, 2-D, and 3-D carbon-hydrogen systems demonstrates high efficiency and scalability of the compound two-step decomposition of the two-electron integral tensor in our implementation. For the size of the atomic basis set, N b , ranging from ∼100 up to ∼2,000, the observed numerical scaling of our implementation shows [Formula: see text] versus [Formula: see text] cost of performing single CD on the two-electron integral tensor in most of the other implementations. More importantly, this decomposition strategy can significantly reduce the storage requirement of the atomic orbital (AO) two-electron integral tensor from [Formula: see text] to [Formula: see text] with moderate decomposition thresholds. The accuracy tests have been performed using ground- and excited-state formulations of coupled cluster formalism employing single and double excitations (CCSD) on several benchmark systems including the C 60 molecule described by nearly 1,400 basis functions. The results show that the decomposition thresholds can be generally set to 10 -4 to 10 -3 to give acceptable compromise between efficiency and accuracy.

An efficient implementation of a high-order filter for a cubed-sphere spectral element model

NASA Astrophysics Data System (ADS)

Kang, Hyun-Gyu; Cheong, Hyeong-Bin

2017-03-01

A parallel-scalable, isotropic, scale-selective spatial filter was developed for the cubed-sphere spectral element model on the sphere. The filter equation is a high-order elliptic (Helmholtz) equation based on the spherical Laplacian operator, which is transformed into cubed-sphere local coordinates. The Laplacian operator is discretized on the computational domain, i.e., on each cell, by the spectral element method with Gauss-Lobatto Lagrange interpolating polynomials (GLLIPs) as the orthogonal basis functions. On the global domain, the discrete filter equation yielded a linear system represented by a highly sparse matrix. The density of this matrix increases quadratically (linearly) with the order of GLLIP (order of the filter), and the linear system is solved in only O (Ng) operations, where Ng is the total number of grid points. The solution, obtained by a row reduction method, demonstrated the typical accuracy and convergence rate of the cubed-sphere spectral element method. To achieve computational efficiency on parallel computers, the linear system was treated by an inverse matrix method (a sparse matrix-vector multiplication). The density of the inverse matrix was lowered to only a few times of the original sparse matrix without degrading the accuracy of the solution. For better computational efficiency, a local-domain high-order filter was introduced: The filter equation is applied to multiple cells, and then the central cell was only used to reconstruct the filtered field. The parallel efficiency of applying the inverse matrix method to the global- and local-domain filter was evaluated by the scalability on a distributed-memory parallel computer. The scale-selective performance of the filter was demonstrated on Earth topography. The usefulness of the filter as a hyper-viscosity for the vorticity equation was also demonstrated.

Light manipulation for organic optoelectronics using bio-inspired moth's eye nanostructures.

PubMed

Zhou, Lei; Ou, Qing-Dong; Chen, Jing-De; Shen, Su; Tang, Jian-Xin; Li, Yan-Qing; Lee, Shuit-Tong

2014-02-10

Organic-based optoelectronic devices, including light-emitting diodes (OLEDs) and solar cells (OSCs) hold great promise as low-cost and large-area electro-optical devices and renewable energy sources. However, further improvement in efficiency remains a daunting challenge due to limited light extraction or absorption in conventional device architectures. Here we report a universal method of optical manipulation of light by integrating a dual-side bio-inspired moth's eye nanostructure with broadband anti-reflective and quasi-omnidirectional properties. Light out-coupling efficiency of OLEDs with stacked triple emission units is over 2 times that of a conventional device, resulting in drastic increase in external quantum efficiency and current efficiency to 119.7% and 366 cd A(-1) without introducing spectral distortion and directionality. Similarly, the light in-coupling efficiency of OSCs is increased 20%, yielding an enhanced power conversion efficiency of 9.33%. We anticipate this method would offer a convenient and scalable way for inexpensive and high-efficiency organic optoelectronic designs.

Scalable continuous flow synthesis of ZnO nanorod arrays in 3-D ceramic honeycomb substrates for low-temperature desulfurization

DOE PAGES

Wang, Sibo; Wu, Yunchao; Miao, Ran; ...

2017-07-26

Scalable and cost-effective synthesis and assembly of technologically important nanostructures in three-dimensional (3D) substrates hold keys to bridge the demonstrated nanotechnologies in academia with industrially relevant scalable manufacturing. In this paper, using ZnO nanorod arrays as an example, a hydrothermal-based continuous flow synthesis (CFS) method is successfully used to integrate the nano-arrays in multi-channeled monolithic cordierite. Compared to the batch process, CFS enhances the average growth rate of nano-arrays by 125%, with the average length increasing from 2 μm to 4.5 μm within the same growth time of 4 hours. The precursor utilization efficiency of CFS is enhanced by 9more » times compared to that of batch process by preserving the majority of precursors in recyclable solution. Computational fluid dynamic simulation suggests a steady-state solution flow and mass transport inside the channels of honeycomb substrates, giving rise to steady and consecutive growth of ZnO nano-arrays with an average length of 10 μm in 12 h. The monolithic ZnO nano-array-integrated cordierite obtained through CFS shows enhanced low-temperature (200 °C) desulfurization capacity and recyclability in comparison to ZnO powder wash-coated cordierite. This can be attributed to exposed ZnO {101¯0} planes, better dispersion and stronger interactions between sorbent and reactant in the ZnO nanorod arrays, as well as the sintering-resistance of nano-array configurations during sulfidation–regeneration cycles. Finally, with the demonstrated scalable synthesis and desulfurization performance of ZnO nano-arrays, a promising, industrially relevant integration strategy is provided to fabricate metal oxide nano-array-based monolithic devices for various environmental and energy applications.« less

Scalable continuous flow synthesis of ZnO nanorod arrays in 3-D ceramic honeycomb substrates for low-temperature desulfurization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Sibo; Wu, Yunchao; Miao, Ran

Scalable and cost-effective synthesis and assembly of technologically important nanostructures in three-dimensional (3D) substrates hold keys to bridge the demonstrated nanotechnologies in academia with industrially relevant scalable manufacturing. In this paper, using ZnO nanorod arrays as an example, a hydrothermal-based continuous flow synthesis (CFS) method is successfully used to integrate the nano-arrays in multi-channeled monolithic cordierite. Compared to the batch process, CFS enhances the average growth rate of nano-arrays by 125%, with the average length increasing from 2 μm to 4.5 μm within the same growth time of 4 hours. The precursor utilization efficiency of CFS is enhanced by 9more » times compared to that of batch process by preserving the majority of precursors in recyclable solution. Computational fluid dynamic simulation suggests a steady-state solution flow and mass transport inside the channels of honeycomb substrates, giving rise to steady and consecutive growth of ZnO nano-arrays with an average length of 10 μm in 12 h. The monolithic ZnO nano-array-integrated cordierite obtained through CFS shows enhanced low-temperature (200 °C) desulfurization capacity and recyclability in comparison to ZnO powder wash-coated cordierite. This can be attributed to exposed ZnO {101¯0} planes, better dispersion and stronger interactions between sorbent and reactant in the ZnO nanorod arrays, as well as the sintering-resistance of nano-array configurations during sulfidation–regeneration cycles. Finally, with the demonstrated scalable synthesis and desulfurization performance of ZnO nano-arrays, a promising, industrially relevant integration strategy is provided to fabricate metal oxide nano-array-based monolithic devices for various environmental and energy applications.« less

Application Layer Multicast

NASA Astrophysics Data System (ADS)

Allani, Mouna; Garbinato, Benoît; Pedone, Fernando

An increasing number of Peer-to-Peer (P2P) Internet applications rely today on data dissemination as their cornerstone, e.g., audio or video streaming, multi-party games. These applications typically depend on some support for multicast communication, where peers interested in a given data stream can join a corresponding multicast group. As a consequence, the efficiency, scalability, and reliability guarantees of these applications are tightly coupled with that of the underlying multicast mechanism.

Scalability, Complexity and Reliability in Quantum Information Processing

DTIC Science & Technology

2007-03-01

finding short lattice vectors . In [2], we showed that the generalization of the standard method --- random coset state preparation followed by fourier...results in cryptography. In [3], we proposed an efficient new cryptosystem based on the quantum intractability of finding short vectors in a lattice...state. We have explored realizations with neutral atoms as well as a more promising scheme employing polar molecules that allows for much stronger

Frontiers of Engineering: Reports on Leading-Edge Engineering from the 2008 Symposium

DTIC Science & Technology

2009-07-07

article, we review recent progress on a highly 61 ROLL PRINTING OF CRYSTALliNE NANOWIRES efficient, scalable approach for the ordered, unifonn...NATIONAL ACADEMIES Advisers to the Nation on Science, Engineering, and Medicine The National Academy of Sciences is a private, nonprofit, self...target delivery of a therapy to a particular physiological system, minimizing systemic side effects. Talks in the session provided an overview of

Improving the Accuracy and Scalability of Discriminative Learning Methods for Markov Logic Networks

DTIC Science & Technology

2011-05-01

9 2.2 Inductive Logic Programming and Aleph . . . . . . . . . . . . 10 2.3 MLNs and Alchemy ...positive examples. Aleph allows users to customize each of 10 these steps, and thereby supports a variety of specific algorithms. 2.3 MLNs and Alchemy An...tural motifs. By limiting the search to each unique motif, LSM is able to find good clauses in an efficient manner. Alchemy (Kok, Singla, Richardson

Anytime Prediction: Efficient Ensemble Methods for Any Computational Budget

DTIC Science & Technology

2014-01-21

difficult problem and is the focus of this work. 1.1 Motivation The number of machine learning applications which involve real time and latency sensitive pre...significantly increasing latency , and the computational costs associated with hosting a service are often critical to its viability. For such...balancing training costs, concerns such as scalability and tractability are often more important, as opposed to factors such as latency which are more

Real-Time Optimization in Complex Stochastic Environment

DTIC Science & Technology

2015-06-24

simpler ones, thus addressing scalability and the limited resources of networked wireless devices. This, however, comes at the expense of increased...Maximization of Wireless Sensor Networks with Non-ideal Batteries”, IEEE Trans. on Control of Network Systems, Vol. 1, 1, pp. 86-98, 2014. [27...C.G., “Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks ”, subm. to IEEE Trans. on Control of Network Systems

Scalable diode array pumped Nd rod laser

NASA Technical Reports Server (NTRS)

Zenzie, H. H.; Knights, M. G.; Mosto, J. R.; Chicklis, E. P.; Perkins, P. E.

1991-01-01

Experiments were carried out on a five-array pump head which utilizes gold-coated reflective cones to couple the pump energy to Nd:YAG and Nd:YLF rod lasers, demonstrating high efficiency and uniform energy deposition. Because the cones function as optical diodes to light outside their acceptance angle (typically 10-15 deg), much of the diode energy not absorbed on the first pass can be returned to the rod.

Functional Basis for Efficient Physical Layer Classical Control in Quantum Processors

NASA Astrophysics Data System (ADS)

Ball, Harrison; Nguyen, Trung; Leong, Philip H. W.; Biercuk, Michael J.

2016-12-01

The rapid progress seen in the development of quantum-coherent devices for information processing has motivated serious consideration of quantum computer architecture and organization. One topic which remains open for investigation and optimization relates to the design of the classical-quantum interface, where control operations on individual qubits are applied according to higher-level algorithms; accommodating competing demands on performance and scalability remains a major outstanding challenge. In this work, we present a resource-efficient, scalable framework for the implementation of embedded physical layer classical controllers for quantum-information systems. Design drivers and key functionalities are introduced, leading to the selection of Walsh functions as an effective functional basis for both programing and controller hardware implementation. This approach leverages the simplicity of real-time Walsh-function generation in classical digital hardware, and the fact that a wide variety of physical layer controls, such as dynamic error suppression, are known to fall within the Walsh family. We experimentally implement a real-time field-programmable-gate-array-based Walsh controller producing Walsh timing signals and Walsh-synthesized analog waveforms appropriate for critical tasks in error-resistant quantum control and noise characterization. These demonstrations represent the first step towards a unified framework for the realization of physical layer controls compatible with large-scale quantum-information processing.

AWE-WQ: fast-forwarding molecular dynamics using the accelerated weighted ensemble.

PubMed

Abdul-Wahid, Badi'; Feng, Haoyun; Rajan, Dinesh; Costaouec, Ronan; Darve, Eric; Thain, Douglas; Izaguirre, Jesús A

2014-10-27

A limitation of traditional molecular dynamics (MD) is that reaction rates are difficult to compute. This is due to the rarity of observing transitions between metastable states since high energy barriers trap the system in these states. Recently the weighted ensemble (WE) family of methods have emerged which can flexibly and efficiently sample conformational space without being trapped and allow calculation of unbiased rates. However, while WE can sample correctly and efficiently, a scalable implementation applicable to interesting biomolecular systems is not available. We provide here a GPLv2 implementation called AWE-WQ of a WE algorithm using the master/worker distributed computing WorkQueue (WQ) framework. AWE-WQ is scalable to thousands of nodes and supports dynamic allocation of computer resources, heterogeneous resource usage (such as central processing units (CPU) and graphical processing units (GPUs) concurrently), seamless heterogeneous cluster usage (i.e., campus grids and cloud providers), and support for arbitrary MD codes such as GROMACS, while ensuring that all statistics are unbiased. We applied AWE-WQ to a 34 residue protein which simulated 1.5 ms over 8 months with peak aggregate performance of 1000 ns/h. Comparison was done with a 200 μs simulation collected on a GPU over a similar timespan. The folding and unfolded rates were of comparable accuracy.

Automated Expansion of Primary Human T Cells in Scalable and Cell-Friendly Hydrogel Microtubes for Adoptive Immunotherapy.

PubMed

Lin, Haishuang; Li, Qiang; Wang, Ou; Rauch, Jack; Harm, Braden; Viljoen, Hendrik J; Zhang, Chi; Van Wyk, Erika; Zhang, Chi; Lei, Yuguo

2018-05-11

Adoptive immunotherapy is a highly effective strategy for treating many human cancers, such as melanoma, cervical cancer, lymphoma, and leukemia. Here, a novel cell culture technology is reported for expanding primary human T cells for adoptive immunotherapy. T cells are suspended and cultured in microscale alginate hydrogel tubes (AlgTubes) that are suspended in the cell culture medium in a culture vessel. The hydrogel tubes protect cells from hydrodynamic stresses and confine the cell mass less than 400 µm (in radial diameter) to ensure efficient mass transport, creating a cell-friendly microenvironment for growing T cells. This system is simple, scalable, highly efficient, defined, cost-effective, and compatible with current good manufacturing practices. Under optimized culture conditions, the AlgTubes enable culturing T cells with high cell viability, low DNA damage, high growth rate (≈320-fold expansion over 14 days), high purity (≈98% CD3+), and high yield (≈3.2 × 10 8 cells mL -1 hydrogel). All offer considerable advantages compared to current T cell culturing approaches. This new culture technology can significantly reduce the culture volume, time, and cost, while increasing the production. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Efficient generation of hPSC-derived midbrain dopaminergic neurons in a fully defined, scalable, 3D biomaterial platform

PubMed Central

Adil, Maroof M.; Rodrigues, Gonçalo M. C.; Kulkarni, Rishikesh U.; Rao, Antara T.; Chernavsky, Nicole E.; Miller, Evan W.; Schaffer, David V.

2017-01-01

Pluripotent stem cells (PSCs) have major potential as an unlimited source of functional cells for many biomedical applications; however, the development of cell manufacturing systems to enable this promise faces many challenges. For example, there have been major recent advances in the generation of midbrain dopaminergic (mDA) neurons from stem cells for Parkinson’s Disease (PD) therapy; however, production of these cells typically involves undefined components and difficult to scale 2D culture formats. Here, we used a fully defined, 3D, thermoresponsive biomaterial platform to rapidly generate large numbers of action-potential firing mDA neurons after 25 days of differentiation (~40% tyrosine hydroxylase (TH) positive, maturing into 25% cells exhibiting mDA neuron-like spiking behavior). Importantly, mDA neurons generated in 3D exhibited a 30-fold increase in viability upon implantation into rat striatum compared to neurons generated on 2D, consistent with the elevated expression of survival markers FOXA2 and EN1 in 3D. A defined, scalable, and resource-efficient cell culture platform can thus rapidly generate high quality differentiated cells, both neurons and potentially other cell types, with strong potential to accelerate both basic and translational research. PMID:28091566

Fast bi-directional prediction selection in H.264/MPEG-4 AVC temporal scalable video coding.

PubMed

Lin, Hung-Chih; Hang, Hsueh-Ming; Peng, Wen-Hsiao

2011-12-01

In this paper, we propose a fast algorithm that efficiently selects the temporal prediction type for the dyadic hierarchical-B prediction structure in the H.264/MPEG-4 temporal scalable video coding (SVC). We make use of the strong correlations in prediction type inheritance to eliminate the superfluous computations for the bi-directional (BI) prediction in the finer partitions, 16×8/8×16/8×8 , by referring to the best temporal prediction type of 16 × 16. In addition, we carefully examine the relationship in motion bit-rate costs and distortions between the BI and the uni-directional temporal prediction types. As a result, we construct a set of adaptive thresholds to remove the unnecessary BI calculations. Moreover, for the block partitions smaller than 8 × 8, either the forward prediction (FW) or the backward prediction (BW) is skipped based upon the information of their 8 × 8 partitions. Hence, the proposed schemes can efficiently reduce the extensive computational burden in calculating the BI prediction. As compared to the JSVM 9.11 software, our method saves the encoding time from 48% to 67% for a large variety of test videos over a wide range of coding bit-rates and has only a minor coding performance loss. © 2011 IEEE

Scalable, High-performance 3D Imaging Software Platform: System Architecture and Application to Virtual Colonoscopy

PubMed Central

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli; Brett, Bevin

2013-01-01

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. In this work, we have developed a software platform that is designed to support high-performance 3D medical image processing for a wide range of applications using increasingly available and affordable commodity computing systems: multi-core, clusters, and cloud computing systems. To achieve scalable, high-performance computing, our platform (1) employs size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D image processing algorithms; (2) supports task scheduling for efficient load distribution and balancing; and (3) consists of a layered parallel software libraries that allow a wide range of medical applications to share the same functionalities. We evaluated the performance of our platform by applying it to an electronic cleansing system in virtual colonoscopy, with initial experimental results showing a 10 times performance improvement on an 8-core workstation over the original sequential implementation of the system. PMID:23366803

AWE-WQ: Fast-Forwarding Molecular Dynamics Using the Accelerated Weighted Ensemble

PubMed Central

2015-01-01

A limitation of traditional molecular dynamics (MD) is that reaction rates are difficult to compute. This is due to the rarity of observing transitions between metastable states since high energy barriers trap the system in these states. Recently the weighted ensemble (WE) family of methods have emerged which can flexibly and efficiently sample conformational space without being trapped and allow calculation of unbiased rates. However, while WE can sample correctly and efficiently, a scalable implementation applicable to interesting biomolecular systems is not available. We provide here a GPLv2 implementation called AWE-WQ of a WE algorithm using the master/worker distributed computing WorkQueue (WQ) framework. AWE-WQ is scalable to thousands of nodes and supports dynamic allocation of computer resources, heterogeneous resource usage (such as central processing units (CPU) and graphical processing units (GPUs) concurrently), seamless heterogeneous cluster usage (i.e., campus grids and cloud providers), and support for arbitrary MD codes such as GROMACS, while ensuring that all statistics are unbiased. We applied AWE-WQ to a 34 residue protein which simulated 1.5 ms over 8 months with peak aggregate performance of 1000 ns/h. Comparison was done with a 200 μs simulation collected on a GPU over a similar timespan. The folding and unfolded rates were of comparable accuracy. PMID:25207854

3D-printed conductive static mixers enable all-vanadium redox flow battery using slurry electrodes

NASA Astrophysics Data System (ADS)

Percin, Korcan; Rommerskirchen, Alexandra; Sengpiel, Robert; Gendel, Youri; Wessling, Matthias

2018-03-01

State-of-the-art all-vanadium redox flow batteries employ porous carbonaceous materials as electrodes. The battery cells possess non-scalable fixed electrodes inserted into a cell stack. In contrast, a conductive particle network dispersed in the electrolyte, known as slurry electrode, may be beneficial for a scalable redox flow battery. In this work, slurry electrodes are successfully introduced to an all-vanadium redox flow battery. Activated carbon and graphite powder particles are dispersed up to 20 wt% in the vanadium electrolyte and charge-discharge behavior is inspected via polarization studies. Graphite powder slurry is superior over activated carbon with a polarization behavior closer to the standard graphite felt electrodes. 3D-printed conductive static mixers introduced to the slurry channel improve the charge transfer via intensified slurry mixing and increased surface area. Consequently, a significant increase in the coulombic efficiency up to 95% and energy efficiency up to 65% is obtained. Our results show that slurry electrodes supported by conductive static mixers can be competitive to state-of-the-art electrodes yielding an additional degree of freedom in battery design. Research into carbon properties (particle size, internal surface area, pore size distribution) tailored to the electrolyte system and optimization of the mixer geometry may yield even better battery properties.

An electrochemical and structural study of highly uniform tin oxide nanowires fabricated by a novel, scalable solvoplasma technique as anode material for sodium ion batteries

NASA Astrophysics Data System (ADS)

Mukherjee, Santanu; Schuppert, Nicholas; Bates, Alex; Jasinski, Jacek; Hong, Jong-Eun; Choi, Moon Jong; Park, Sam

2017-04-01

A novel solvoplasma based technique was used to fabricate highly uniform SnO2 nanowires (NWs) for application as an anode in sodium-ion batteries (SIBs). This technique is scalable, rapid, and utilizes a rigorous cleaning process to produce very pure SnO2 NWs with enhanced porosity; which improves sodium-ion hosting and reaction kinetics. The batch of NWs obtained from the plasma process were named the "as-made" sample and after cleaning the "pure" sample. Structural characterization showed that the as-made sample has a K+ ion impurity which is absent in the pure samples. The pure samples have a higher maximum specific capacity, 400.71 mAhg-1, and Coulombic efficiency, 85%, compared to the as-made samples which have a maximum specific capacity of 174.69 mAhg-1 and Coulombic efficiency of 74% upon cycling. A study of the electrochemical impedance spectra showed that the as-made samples have a higher interfacial and diffusion resistance than the pure samples and resistances increased after 50 cycles of cell operation for both samples due to progressive electrode degradation. Specific energy vs specific power plots were employed to analyze the performance of the system with respect to the working conditions.

Efficient Q-switched operation in 1.64 μm Er:YAG tapered rod laser

NASA Astrophysics Data System (ADS)

Polyakov, Vadim M.; Vitkin, Vladimir V.; Krylov, Alexandr A.; Uskov, Alexander V.; Mak, Andrey A.

2017-02-01

We model output characteristics of the 1645 nm 8 mJ 10 ns 100 Hz Q-switched Er:YAG DPSSL. The laser is end pumped at a wavelength of 1532 nm. Fiber-coupled diode laser module was 10 nm FWHM, 12 W CW, 200 μm, NA 0.22. Various tapering of the active rod has been considered for 1 mm diameter, 20 mm long and 0.5% Er doping. We discuss the heat deposition process, the energy storage efficiency and the average power limitations for Q-switched regime of generation and amplification, and find the system scalable for the high power operation.

3D CSEM inversion based on goal-oriented adaptive finite element method

NASA Astrophysics Data System (ADS)

Zhang, Y.; Key, K.

2016-12-01

We present a parallel 3D frequency domain controlled-source electromagnetic inversion code name MARE3DEM. Non-linear inversion of observed data is performed with the Occam variant of regularized Gauss-Newton optimization. The forward operator is based on the goal-oriented finite element method that efficiently calculates the responses and sensitivity kernels in parallel using a data decomposition scheme where independent modeling tasks contain different frequencies and subsets of the transmitters and receivers. To accommodate complex 3D conductivity variation with high flexibility and precision, we adopt the dual-grid approach where the forward mesh conforms to the inversion parameter grid and is adaptively refined until the forward solution converges to the desired accuracy. This dual-grid approach is memory efficient, since the inverse parameter grid remains independent from fine meshing generated around the transmitter and receivers by the adaptive finite element method. Besides, the unstructured inverse mesh efficiently handles multiple scale structures and allows for fine-scale model parameters within the region of interest. Our mesh generation engine keeps track of the refinement hierarchy so that the map of conductivity and sensitivity kernel between the forward and inverse mesh is retained. We employ the adjoint-reciprocity method to calculate the sensitivity kernels which establish a linear relationship between changes in the conductivity model and changes in the modeled responses. Our code uses a direcy solver for the linear systems, so the adjoint problem is efficiently computed by re-using the factorization from the primary problem. Further computational efficiency and scalability is obtained in the regularized Gauss-Newton portion of the inversion using parallel dense matrix-matrix multiplication and matrix factorization routines implemented with the ScaLAPACK library. We show the scalability, reliability and the potential of the algorithm to deal with complex geological scenarios by applying it to the inversion of synthetic marine controlled source EM data generated for a complex 3D offshore model with significant seafloor topography.

Efficient path-based computations on pedigree graphs with compact encodings

PubMed Central

2012-01-01

A pedigree is a diagram of family relationships, and it is often used to determine the mode of inheritance (dominant, recessive, etc.) of genetic diseases. Along with rapidly growing knowledge of genetics and accumulation of genealogy information, pedigree data is becoming increasingly important. In large pedigree graphs, path-based methods for efficiently computing genealogical measurements, such as inbreeding and kinship coefficients of individuals, depend on efficient identification and processing of paths. In this paper, we propose a new compact path encoding scheme on large pedigrees, accompanied by an efficient algorithm for identifying paths. We demonstrate the utilization of our proposed method by applying it to the inbreeding coefficient computation. We present time and space complexity analysis, and also manifest the efficiency of our method for evaluating inbreeding coefficients as compared to previous methods by experimental results using pedigree graphs with real and synthetic data. Both theoretical and experimental results demonstrate that our method is more scalable and efficient than previous methods in terms of time and space requirements. PMID:22536898

Self assembled dual responsive micelles stabilized with protein for co-delivery of drug and siRNA in cancer therapy.

PubMed

Aji Alex, M R; Nehate, Chetan; Veeranarayanan, Srivani; Kumar, D Sakthi; Kulshreshtha, Ritu; Koul, Veena

2017-07-01

Design of safe and efficient vehicles for the combinatorial delivery of drugs and genetic agents is an emerging requisite for achieving enhanced therapeutic effect in cancer. Even though several nanoplatforms have been explored for the co-delivery of drugs and genetic materials the translation of these systems to clinical phase is still a challenge, mainly due to tedious synthesis procedures, lack of serum stability, inefficient scalability etc. Here in, we report development of reduction and pH sensitive polymeric graft of low molecular weight poly (styrene -alt -maleic anhydride) and evaluation of its efficacy in co-delivering drug and siRNA. The polymer was modified with suitable components, which could help in overcoming various systemic and cellular barriers for successful co-delivery of drugs and nucleic acids to cancer cells, using simple chemical reactions. The polymeric derivative could easily self assemble in water to form smooth, spherical micellar structures, indicating their scalability. Doxorubicin and PLK-1 siRNA were selected as model drug and nucleic acid, respectively. Doxorubicin could be loaded in the self assembling micelles with an optimum loading content of ∼8.6% w/w and efficient siRNA complexation was achieved with polymer/siRNA weight ratios >40. The polyplexes were stabilized in physiological saline by coating with bovine serum albumin (BSA). Stable drug loaded nanoplexes, for clinical administration, could be easily formulated by gently dispersing them in physiological saline containing appropriate amount of albumin. Drug release from the nanoplexes was significantly enhanced at low pH (5) and in the presence of 10 mM glutathione (GSH) showing their dual stimuli sensitive nature. In vitro cell proliferation assay and in vivo tumor regression study have shown synergistic effect of the drug loaded nanoplexes in inhibiting cancer cell proliferation. Facile synthesis steps, scalability and ease of formulation depict excellent clinical translation potential of the proposed nanosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Monte Carlo MP2 on Many Graphical Processing Units.

PubMed

Doran, Alexander E; Hirata, So

2016-10-11

In the Monte Carlo second-order many-body perturbation (MC-MP2) method, the long sum-of-product matrix expression of the MP2 energy, whose literal evaluation may be poorly scalable, is recast into a single high-dimensional integral of functions of electron pair coordinates, which is evaluated by the scalable method of Monte Carlo integration. The sampling efficiency is further accelerated by the redundant-walker algorithm, which allows a maximal reuse of electron pairs. Here, a multitude of graphical processing units (GPUs) offers a uniquely ideal platform to expose multilevel parallelism: fine-grain data-parallelism for the redundant-walker algorithm in which millions of threads compute and share orbital amplitudes on each GPU; coarse-grain instruction-parallelism for near-independent Monte Carlo integrations on many GPUs with few and infrequent interprocessor communications. While the efficiency boost by the redundant-walker algorithm on central processing units (CPUs) grows linearly with the number of electron pairs and tends to saturate when the latter exceeds the number of orbitals, on a GPU it grows quadratically before it increases linearly and then eventually saturates at a much larger number of pairs. This is because the orbital constructions are nearly perfectly parallelized on a GPU and thus completed in a near-constant time regardless of the number of pairs. In consequence, an MC-MP2/cc-pVDZ calculation of a benzene dimer is 2700 times faster on 256 GPUs (using 2048 electron pairs) than on two CPUs, each with 8 cores (which can use only up to 256 pairs effectively). We also numerically determine that the cost to achieve a given relative statistical uncertainty in an MC-MP2 energy increases as O(n 3 ) or better with system size n, which may be compared with the O(n 5 ) scaling of the conventional implementation of deterministic MP2. We thus establish the scalability of MC-MP2 with both system and computer sizes.

Scalable Conjunction Processing using Spatiotemporally Indexed Ephemeris Data

NASA Astrophysics Data System (ADS)

Budianto-Ho, I.; Johnson, S.; Sivilli, R.; Alberty, C.; Scarberry, R.

2014-09-01

The collision warnings produced by the Joint Space Operations Center (JSpOC) are of critical importance in protecting U.S. and allied spacecraft against destructive collisions and protecting the lives of astronauts during space flight. As the Space Surveillance Network (SSN) improves its sensor capabilities for tracking small and dim space objects, the number of tracked objects increases from thousands to hundreds of thousands of objects, while the number of potential conjunctions increases with the square of the number of tracked objects. Classical filtering techniques such as apogee and perigee filters have proven insufficient. Novel and orders of magnitude faster conjunction analysis algorithms are required to find conjunctions in a timely manner. Stellar Science has developed innovative filtering techniques for satellite conjunction processing using spatiotemporally indexed ephemeris data that efficiently and accurately reduces the number of objects requiring high-fidelity and computationally-intensive conjunction analysis. Two such algorithms, one based on the k-d Tree pioneered in robotics applications and the other based on Spatial Hash Tables used in computer gaming and animation, use, at worst, an initial O(N log N) preprocessing pass (where N is the number of tracked objects) to build large O(N) spatial data structures that substantially reduce the required number of O(N^2) computations, substituting linear memory usage for quadratic processing time. The filters have been implemented as Open Services Gateway initiative (OSGi) plug-ins for the Continuous Anomalous Orbital Situation Discriminator (CAOS-D) conjunction analysis architecture. We have demonstrated the effectiveness, efficiency, and scalability of the techniques using a catalog of 100,000 objects, an analysis window of one day, on a 64-core computer with 1TB shared memory. Each algorithm can process the full catalog in 6 minutes or less, almost a twenty-fold performance improvement over the baseline implementation running on the same machine. We will present an overview of the algorithms and results that demonstrate the scalability of our concepts.

History of Significant Vehicle and Fuel Introductions in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shirk, Matthew; Alleman, Teresa; Melendez, Margo

This is one of a series of reports produced as a result of the Co-Optimization of Fuels & Engines (Co-Optima) project, a Department of Energy (DOE)-sponsored multi-agency project initiated to accelerate the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development is designed to deliver maximum energy savings, emissions reduction, and on-road performance.

Validation of 3D RANS-SA Calculations on Strand/Cartesian Meshes

DTIC Science & Technology

2014-01-07

a parallel environment. This allows for significant gains in efficiency and scalability of domain connectiv- ity, effectively eliminating inter... equation of state , p = ρRT is used to close the equations . 4 of 22 American Institute of Aeronautics and Astronautics 6 III.A. Discretization and...Utah State University 1415 Old Main Hill - Room 64 Logan, UT 84322 -1415 1 ABSTRACT Validation of 3D RANS-SA Calculations on Strand/Cartesian Meshes

Silicon photonics for neuromorphic information processing

NASA Astrophysics Data System (ADS)

Bienstman, Peter; Dambre, Joni; Katumba, Andrew; Freiberger, Matthias; Laporte, Floris; Lugnan, Alessio

2018-02-01

We present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. We will discuss aspects like scalability, novel architectures for enhanced power efficiency, as well as all-optical readout. Additionally, we will touch upon new machine learning techniques to operate these integrated readouts. Finally, we will show how these systems can be used for high-speed low-power information processing for applications like recognition of biological cells.

Algal Biofuels Strategy. Proceedings from the March 26-27, 2014, Workshop, Charleston, South Carolina

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

2014-06-01

This report is based on the proceedings of the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy’s Bioenergy Technologies Office’s Algal Biofuel Strategy Workshop on March 26-27, 2014, in Charleston, South Carolina. The workshop objective was to convene stakeholders to engage in discussion on strategies over the next 5 to 10 years to achieve affordable, scalable, and sustainable algal biofuels.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, David G.; Cook, Marvin A.

This report summarizes collaborative efforts between Secure Scalable Microgrid and Korean Institute of Energy Research team members . The efforts aim to advance microgrid research and development towards the efficient utilization of networked microgrids . The collaboration resulted in the identification of experimental and real time simulation capabilities that may be leveraged for networked microgrids research, development, and demonstration . Additional research was performed to support the demonstration of control techniques within real time simulation and with hardware in the loop for DC microgrids .

Execution of a parallel edge-based Navier-Stokes solver on commodity graphics processor units

NASA Astrophysics Data System (ADS)

Corral, Roque; Gisbert, Fernando; Pueblas, Jesus

2017-02-01

The implementation of an edge-based three-dimensional Reynolds Average Navier-Stokes solver for unstructured grids able to run on multiple graphics processing units (GPUs) is presented. Loops over edges, which are the most time-consuming part of the solver, have been written to exploit the massively parallel capabilities of GPUs. Non-blocking communications between parallel processes and between the GPU and the central processor unit (CPU) have been used to enhance code scalability. The code is written using a mixture of C++ and OpenCL, to allow the execution of the source code on GPUs. The Message Passage Interface (MPI) library is used to allow the parallel execution of the solver on multiple GPUs. A comparative study of the solver parallel performance is carried out using a cluster of CPUs and another of GPUs. It is shown that a single GPU is up to 64 times faster than a single CPU core. The parallel scalability of the solver is mainly degraded due to the loss of computing efficiency of the GPU when the size of the case decreases. However, for large enough grid sizes, the scalability is strongly improved. A cluster featuring commodity GPUs and a high bandwidth network is ten times less costly and consumes 33% less energy than a CPU-based cluster with an equivalent computational power.

Dynamic and scalable audio classification by collective network of binary classifiers framework: an evolutionary approach.

PubMed

Kiranyaz, Serkan; Mäkinen, Toni; Gabbouj, Moncef

2012-10-01

In this paper, we propose a novel framework based on a collective network of evolutionary binary classifiers (CNBC) to address the problems of feature and class scalability. The main goal of the proposed framework is to achieve a high classification performance over dynamic audio and video repositories. The proposed framework adopts a "Divide and Conquer" approach in which an individual network of binary classifiers (NBC) is allocated to discriminate each audio class. An evolutionary search is applied to find the best binary classifier in each NBC with respect to a given criterion. Through the incremental evolution sessions, the CNBC framework can dynamically adapt to each new incoming class or feature set without resorting to a full-scale re-training or re-configuration. Therefore, the CNBC framework is particularly designed for dynamically varying databases where no conventional static classifiers can adapt to such changes. In short, it is entirely a novel topology, an unprecedented approach for dynamic, content/data adaptive and scalable audio classification. A large set of audio features can be effectively used in the framework, where the CNBCs make appropriate selections and combinations so as to achieve the highest discrimination among individual audio classes. Experiments demonstrate a high classification accuracy (above 90%) and efficiency of the proposed framework over large and dynamic audio databases. Copyright © 2012 Elsevier Ltd. All rights reserved.

HiDi: an efficient reverse engineering schema for large-scale dynamic regulatory network reconstruction using adaptive differentiation.

PubMed

Deng, Yue; Zenil, Hector; Tegnér, Jesper; Kiani, Narsis A

2017-12-15

The use of differential equations (ODE) is one of the most promising approaches to network inference. The success of ODE-based approaches has, however, been limited, due to the difficulty in estimating parameters and by their lack of scalability. Here, we introduce a novel method and pipeline to reverse engineer gene regulatory networks from gene expression of time series and perturbation data based upon an improvement on the calculation scheme of the derivatives and a pre-filtration step to reduce the number of possible links. The method introduces a linear differential equation model with adaptive numerical differentiation that is scalable to extremely large regulatory networks. We demonstrate the ability of this method to outperform current state-of-the-art methods applied to experimental and synthetic data using test data from the DREAM4 and DREAM5 challenges. Our method displays greater accuracy and scalability. We benchmark the performance of the pipeline with respect to dataset size and levels of noise. We show that the computation time is linear over various network sizes. The Matlab code of the HiDi implementation is available at: www.complexitycalculator.com/HiDiScript.zip. hzenilc@gmail.com or narsis.kiani@ki.se. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

JobCenter: an open source, cross-platform, and distributed job queue management system optimized for scalability and versatility

PubMed Central

2012-01-01

Background Laboratories engaged in computational biology or bioinformatics frequently need to run lengthy, multistep, and user-driven computational jobs. Each job can tie up a computer for a few minutes to several days, and many laboratories lack the expertise or resources to build and maintain a dedicated computer cluster. Results JobCenter is a client–server application and framework for job management and distributed job execution. The client and server components are both written in Java and are cross-platform and relatively easy to install. All communication with the server is client-driven, which allows worker nodes to run anywhere (even behind external firewalls or “in the cloud”) and provides inherent load balancing. Adding a worker node to the worker pool is as simple as dropping the JobCenter client files onto any computer and performing basic configuration, which provides tremendous ease-of-use, flexibility, and limitless horizontal scalability. Each worker installation may be independently configured, including the types of jobs it is able to run. Executed jobs may be written in any language and may include multistep workflows. Conclusions JobCenter is a versatile and scalable distributed job management system that allows laboratories to very efficiently distribute all computational work among available resources. JobCenter is freely available at http://code.google.com/p/jobcenter/. PMID:22846423

HOKF: High Order Kalman Filter for Epilepsy Forecasting Modeling.

PubMed

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2017-08-01

Epilepsy forecasting has been extensively studied using high-order time series obtained from scalp-recorded electroencephalography (EEG). An accurate seizure prediction system would not only help significantly improve patients' quality of life, but would also facilitate new therapeutic strategies to manage epilepsy. This paper thus proposes an improved Kalman Filter (KF) algorithm to mine seizure forecasts from neural activity by modeling three properties in the high-order EEG time series: noise, temporal smoothness, and tensor structure. The proposed High-Order Kalman Filter (HOKF) is an extension of the standard Kalman filter, for which higher-order modeling is limited. The efficient dynamic of HOKF system preserves the tensor structure of the observations and latent states. As such, the proposed method offers two main advantages: (i) effectiveness with HOKF results in hidden variables that capture major evolving trends suitable to predict neural activity, even in the presence of missing values; and (ii) scalability in that the wall clock time of the HOKF is linear with respect to the number of time-slices of the sequence. The HOKF algorithm is examined in terms of its effectiveness and scalability by conducting forecasting and scalability experiments with a real epilepsy EEG dataset. The results of the simulation demonstrate the superiority of the proposed method over the original Kalman Filter and other existing methods. Copyright © 2017 Elsevier B.V. All rights reserved.

The TOTEM DAQ based on the Scalable Readout System (SRS)

NASA Astrophysics Data System (ADS)

Quinto, Michele; Cafagna, Francesco S.; Fiergolski, Adrian; Radicioni, Emilio

2018-02-01

The TOTEM (TOTal cross section, Elastic scattering and diffraction dissociation Measurement at the LHC) experiment at LHC, has been designed to measure the total proton-proton cross-section and study the elastic and diffractive scattering at the LHC energies. In order to cope with the increased machine luminosity and the higher statistic required by the extension of the TOTEM physics program, approved for the LHC's Run Two phase, the previous VME based data acquisition system has been replaced with a new one based on the Scalable Readout System. The system features an aggregated data throughput of 2GB / s towards the online storage system. This makes it possible to sustain a maximum trigger rate of ˜ 24kHz, to be compared with the 1KHz rate of the previous system. The trigger rate is further improved by implementing zero-suppression and second-level hardware algorithms in the Scalable Readout System. The new system fulfils the requirements for an increased efficiency, providing higher bandwidth, and increasing the purity of the data recorded. Moreover full compatibility has been guaranteed with the legacy front-end hardware, as well as with the DAQ interface of the CMS experiment and with the LHC's Timing, Trigger and Control distribution system. In this contribution we describe in detail the architecture of full system and its performance measured during the commissioning phase at the LHC Interaction Point.

WordSeeker: concurrent bioinformatics software for discovering genome-wide patterns and word-based genomic signatures

PubMed Central

2010-01-01

Background An important focus of genomic science is the discovery and characterization of all functional elements within genomes. In silico methods are used in genome studies to discover putative regulatory genomic elements (called words or motifs). Although a number of methods have been developed for motif discovery, most of them lack the scalability needed to analyze large genomic data sets. Methods This manuscript presents WordSeeker, an enumerative motif discovery toolkit that utilizes multi-core and distributed computational platforms to enable scalable analysis of genomic data. A controller task coordinates activities of worker nodes, each of which (1) enumerates a subset of the DNA word space and (2) scores words with a distributed Markov chain model. Results A comprehensive suite of performance tests was conducted to demonstrate the performance, speedup and efficiency of WordSeeker. The scalability of the toolkit enabled the analysis of the entire genome of Arabidopsis thaliana; the results of the analysis were integrated into The Arabidopsis Gene Regulatory Information Server (AGRIS). A public version of WordSeeker was deployed on the Glenn cluster at the Ohio Supercomputer Center. Conclusion WordSeeker effectively utilizes concurrent computing platforms to enable the identification of putative functional elements in genomic data sets. This capability facilitates the analysis of the large quantity of sequenced genomic data. PMID:21210985

EnerCage: A Smart Experimental Arena With Scalable Architecture for Behavioral Experiments

PubMed Central

Uei-Ming Jow; Peter McMenamin; Mehdi Kiani; Manns, Joseph R.; Ghovanloo, Maysam

2014-01-01

Wireless power, when coupled with miniaturized implantable electronics, has the potential to provide a solution to several challenges facing neuroscientists during basic and preclinical studies with freely behaving animals. The EnerCage system is one such solution as it allows for uninterrupted electrophysiology experiments over extended periods of time and vast experimental arenas, while eliminating the need for bulky battery payloads or tethering. It has a scalable array of overlapping planar spiral coils (PSCs) and three-axis magnetic sensors for focused wireless power transmission to devices on freely moving subjects. In this paper, we present the first fully functional EnerCage system, in which the number of PSC drivers and magnetic sensors was reduced to one-third of the number used in our previous design via multicoil coupling. The power transfer efficiency (PTE) has been improved to 5.6% at a 120 mm coupling distance and a 48.5 mm lateral misalignment (worst case) between the transmitter (Tx) array and receiver (Rx) coils. The new EnerCage system is equipped with an Ethernet backbone, further supporting its modular/scalable architecture, which, in turn, allows experimental arenas with arbitrary shapes and dimensions. A set of experiments on a freely behaving rat were conducted by continuously delivering 20 mW to the electronics in the animal headstage for more than one hour in a powered 3538 cm2 experimental area. PMID:23955695

EnerCage: a smart experimental arena with scalable architecture for behavioral experiments.

PubMed

Uei-Ming Jow; McMenamin, Peter; Kiani, Mehdi; Manns, Joseph R; Ghovanloo, Maysam

2014-01-01

Wireless power, when coupled with miniaturized implantable electronics, has the potential to provide a solution to several challenges facing neuroscientists during basic and preclinical studies with freely behaving animals. The EnerCage system is one such solution as it allows for uninterrupted electrophysiology experiments over extended periods of time and vast experimental arenas, while eliminating the need for bulky battery payloads or tethering. It has a scalable array of overlapping planar spiral coils (PSCs) and three-axis magnetic sensors for focused wireless power transmission to devices on freely moving subjects. In this paper, we present the first fully functional EnerCage system, in which the number of PSC drivers and magnetic sensors was reduced to one-third of the number used in our previous design via multicoil coupling. The power transfer efficiency (PTE) has been improved to 5.6% at a 120 mm coupling distance and a 48.5 mm lateral misalignment (worst case) between the transmitter (Tx) array and receiver (Rx) coils. The new EnerCage system is equipped with an Ethernet backbone, further supporting its modular/scalable architecture, which, in turn, allows experimental arenas with arbitrary shapes and dimensions. A set of experiments on a freely behaving rat were conducted by continuously delivering 20 mW to the electronics in the animal headstage for more than one hour in a powered 3538 cm(2) experimental area.

Scalable Production of Si Nanoparticles Directly from Low Grade Sources for Lithium-Ion Battery Anode.

PubMed

Zhu, Bin; Jin, Yan; Tan, Yingling; Zong, Linqi; Hu, Yue; Chen, Lei; Chen, Yanbin; Zhang, Qiao; Zhu, Jia

2015-09-09

Silicon, one of the most promising candidates as lithium-ion battery anode, has attracted much attention due to its high theoretical capacity, abundant existence, and mature infrastructure. Recently, Si nanostructures-based lithium-ion battery anode, with sophisticated structure designs and process development, has made significant progress. However, low cost and scalable processes to produce these Si nanostructures remained as a challenge, which limits the widespread applications. Herein, we demonstrate that Si nanoparticles with controlled size can be massively produced directly from low grade Si sources through a scalable high energy mechanical milling process. In addition, we systematically studied Si nanoparticles produced from two major low grade Si sources, metallurgical silicon (∼99 wt % Si, $1/kg) and ferrosilicon (∼83 wt % Si, $0.6/kg). It is found that nanoparticles produced from ferrosilicon sources contain FeSi2, which can serve as a buffer layer to alleviate the mechanical fractures of volume expansion, whereas nanoparticles from metallurgical Si sources have higher capacity and better kinetic properties because of higher purity and better electronic transport properties. Ferrosilicon nanoparticles and metallurgical Si nanoparticles demonstrate over 100 stable deep cycling after carbon coating with the reversible capacities of 1360 mAh g(-1) and 1205 mAh g(-1), respectively. Therefore, our approach provides a new strategy for cost-effective, energy-efficient, large scale synthesis of functional Si electrode materials.

Development of high-efficiency power amplifiers for PIP2 (Project X), Phase II

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raab, Frederick

The Fermi Lab PIP II (formerly Project X) accelerator will require the generation of over a megawatt of radio-frequency (RF) power at 325 and 650 MHz. This Phase-II SBIR grant developed techniques to generate this RF power efficienly. The basis of this approach is a system comprising high-efficiency RF power amplifiers, high-efficiency class-S modulators to maintain efficiency at all power levels, and low-loss power combiners. A digital signal processor adjusts signal parameters to obtain the maximum efficiency while producing a signal of the desired amplitude and phase. Components of 4-kW prototypes were designed, assembled, and tested. The 500-W modules producemore » signals at 325 MHz with an overall efficiency of 83 percent and signals at 650 MHz with an overall efficiency of 79 percent. This efficiency is nearly double that available from conventional techniques, which makes it possible to cut the power consumption nearly in half. The system is designed to be scalable to the multi-kilowatt level and can be adapted to other DoE applications.« less

Engaging Patients through Mobile Phones: Demonstrator Services, Success Factors, and Future Opportunities in Low and Middle-income Countries

PubMed Central

Hartzler, A.

2014-01-01

Summary Objectives Evolving technology and infrastructure can benefit patients even in the poorest countries through mobile health (mHealth). Yet, what makes mobile-phone-based services succeed in low and middle-income countries (LMIC) and what opportunities does the future hold that still need to be studied. We showcase demonstrator services that leverage mobile phones in the hands of patients to promote health and facilitate health care. Methods We surveyed the recent biomedical literature for demonstrator services that illustrate well-considered examples of mobile phone interventions for consumer health. We draw upon those examples to discuss enabling factors, scalability, reach, and potential of mHealth as well as obstacles in LMIC. Results Among the 227 articles returned by a PubMed search, we identified 55 articles that describe services targeting health consumers equipped with mobile phones. From those articles, we showcase 19 as demonstrator services across clinical care, prevention, infectious diseases, and population health. Services range from education, reminders, reporting, and peer support, to epidemiologic reporting, and care management with phone communication and messages. Key achievements include timely adherence to treatment and appointments, clinical effectiveness of treatment reminders, increased vaccination coverage and uptake of screening, and capacity for efficient disease surveillance. We discuss methodologies of delivery and evaluation of mobile-phone-based mHealth in LMIC, including service design, social context, and environmental factors to success. Conclusions Demonstrated promises using mobile phones in the poorest countries encourage a future in which IMIA takes a lead role in leveraging mHealth for citizen empowerment through Consumer Health Informatics. PMID:25123741

Engaging Patients through Mobile Phones: Demonstrator Services, Success Factors, and Future Opportunities in Low and Middle-income Countries.

PubMed

Hartzler, A; Wetter, T

2014-08-15

Evolving technology and infrastructure can benefit patients even in the poorest countries through mobile health (mHealth). Yet, what makes mobile-phone-based services succeed in low and middle-income countries (LMIC) and what opportunities does the future hold that still need to be studied. We showcase demonstrator services that leverage mobile phones in the hands of patients to promote health and facilitate health care. We surveyed the recent biomedical literature for demonstrator services that illustrate well-considered examples of mobile phone interventions for consumer health. We draw upon those examples to discuss enabling factors, scalability, reach, and potential of mHealth as well as obstacles in LMIC. Among the 227 articles returned by a PubMed search, we identified 55 articles that describe services targeting health consumers equipped with mobile phones. From those articles, we showcase 19 as demonstrator services across clinical care, prevention, infectious diseases, and population health. Services range from education, reminders, reporting, and peer support, to epidemiologic reporting, and care management with phone communication and messages. Key achievements include timely adherence to treatment and appointments, clinical effectiveness of treatment reminders, increased vaccination coverage and uptake of screening, and capacity for efficient disease surveillance. We discuss methodologies of delivery and evaluation of mobile-phone-based mHealth in LMIC, including service design, social context, and environmental factors to success. Demonstrated promises using mobile phones in the poorest countries encourage a future in which IMIA takes a lead role in leveraging mHealth for citizen empowerment through Consumer Health Informatics.

A slotted access control protocol for metropolitan WDM ring networks

NASA Astrophysics Data System (ADS)

Baziana, P. A.; Pountourakis, I. E.

2009-03-01

In this study we focus on the serious scalability problems that many access protocols for WDM ring networks introduce due to the use of a dedicated wavelength per access node for either transmission or reception. We propose an efficient slotted MAC protocol suitable for WDM ring metropolitan area networks. The proposed network architecture employs a separate wavelength for control information exchange prior to the data packet transmission. Each access node is equipped with a pair of tunable transceivers for data communication and a pair of fixed tuned transceivers for control information exchange. Also, each access node includes a set of fixed delay lines for synchronization reasons; to keep the data packets, while the control information is processed. An efficient access algorithm is applied to avoid both the data wavelengths and the receiver collisions. In our protocol, each access node is capable of transmitting and receiving over any of the data wavelengths, facing the scalability issues. Two different slot reuse schemes are assumed: the source and the destination stripping schemes. For both schemes, performance measures evaluation is provided via an analytic model. The analytical results are validated by a discrete event simulation model that uses Poisson traffic sources. Simulation results show that the proposed protocol manages efficient bandwidth utilization, especially under high load. Also, comparative simulation results prove that our protocol achieves significant performance improvement as compared with other WDMA protocols which restrict transmission over a dedicated data wavelength. Finally, performance measures evaluation is explored for diverse numbers of buffer size, access nodes and data wavelengths.

Miniature EVA Software Defined Radio

NASA Technical Reports Server (NTRS)

Pozhidaev, Aleksey

2012-01-01

As NASA embarks upon developing the Next-Generation Extra Vehicular Activity (EVA) Radio for deep space exploration, the demands on EVA battery life will substantially increase. The number of modes and frequency bands required will continue to grow in order to enable efficient and complex multi-mode operations including communications, navigation, and tracking applications. Whether conducting astronaut excursions, communicating to soldiers, or first responders responding to emergency hazards, NASA has developed an innovative, affordable, miniaturized, power-efficient software defined radio that offers unprecedented power-efficient flexibility. This lightweight, programmable, S-band, multi-service, frequency- agile EVA software defined radio (SDR) supports data, telemetry, voice, and both standard and high-definition video. Features include a modular design, an easily scalable architecture, and the EVA SDR allows for both stationary and mobile battery powered handheld operations. Currently, the radio is equipped with an S-band RF section. However, its scalable architecture can accommodate multiple RF sections simultaneously to cover multiple frequency bands. The EVA SDR also supports multiple network protocols. It currently implements a Hybrid Mesh Network based on the 802.11s open standard protocol. The radio targets RF channel data rates up to 20 Mbps and can be equipped with a real-time operating system (RTOS) that can be switched off for power-aware applications. The EVA SDR's modular design permits implementation of the same hardware at all Network Nodes concept. This approach assures the portability of the same software into any radio in the system. It also brings several benefits to the entire system including reducing system maintenance, system complexity, and development cost.

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.

PubMed

Azman, Syafiq Kamarul; Anwar, Muhammad Zohaib; Henschel, Andreas

2017-07-24

Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database. Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.

Enhancing the photon-extraction efficiency of site-controlled quantum dots by deterministically fabricated microlenses

NASA Astrophysics Data System (ADS)

Kaganskiy, Arsenty; Fischbach, Sarah; Strittmatter, André; Rodt, Sven; Heindel, Tobias; Reitzenstein, Stephan

2018-04-01

We report on the realization of scalable single-photon sources (SPSs) based on single site-controlled quantum dots (SCQDs) and deterministically fabricated microlenses. The fabrication process comprises the buried-stressor growth technique complemented with low-temperature in-situ electron-beam lithography for the integration of SCQDs into microlens structures with high yield and high alignment accuracy. The microlens-approach leads to a broadband enhancement of the photon-extraction efficiency of up to (21 ± 2)% and a high suppression of multi-photon events with g (2)(τ = 0) < 0.06 without background subtraction. The demonstrated combination of site-controlled growth of QDs and in-situ electron-beam lithography is relevant for arrays of efficient SPSs which, can be applied in photonic quantum circuits and advanced quantum computation schemes.

GLIDES – Efficient Energy Storage from ORNL

ScienceCinema

Momen, Ayyoub M.; Abu-Heiba, Ahmad; Odukomaiya, Wale; Akinina, Alla

2018-06-25

The research shown in this video features the GLIDES (Ground-Level Integrated Diverse Energy Storage) project, which has been under development at Oak Ridge National Laboratory (ORNL) since 2013. GLIDES can store energy via combined inputs of electricity and heat, and deliver dispatchable electricity. Supported by ORNL’s Laboratory Director’s Research and Development (LDRD) fund, this energy storage system is low-cost, and hybridizes compressed air and pumped-hydro approaches to allow for storage of intermittent renewable energy at high efficiency. A U.S. patent application for this novel energy storage concept has been submitted, and research findings suggest it has the potential to be a flexible, low-cost, scalable, high-efficiency option for energy storage, especially useful in residential and commercial buildings.

GLIDES – Efficient Energy Storage from ORNL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Momen, Ayyoub M.; Abu-Heiba, Ahmad; Odukomaiya, Wale

2016-03-01

The research shown in this video features the GLIDES (Ground-Level Integrated Diverse Energy Storage) project, which has been under development at Oak Ridge National Laboratory (ORNL) since 2013. GLIDES can store energy via combined inputs of electricity and heat, and deliver dispatchable electricity. Supported by ORNL’s Laboratory Director’s Research and Development (LDRD) fund, this energy storage system is low-cost, and hybridizes compressed air and pumped-hydro approaches to allow for storage of intermittent renewable energy at high efficiency. A U.S. patent application for this novel energy storage concept has been submitted, and research findings suggest it has the potential to bemore » a flexible, low-cost, scalable, high-efficiency option for energy storage, especially useful in residential and commercial buildings.« less

EvoGraph: On-The-Fly Efficient Mining of Evolving Graphs on GPU

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Song, Shuaiwen

With the prevalence of the World Wide Web and social networks, there has been a growing interest in high performance analytics for constantly-evolving dynamic graphs. Modern GPUs provide massive AQ1 amount of parallelism for efficient graph processing, but the challenges remain due to their lack of support for the near real-time streaming nature of dynamic graphs. Specifically, due to the current high volume and velocity of graph data combined with the complexity of user queries, traditional processing methods by first storing the updates and then repeatedly running static graph analytics on a sequence of versions or snapshots are deemed undesirablemore » and computational infeasible on GPU. We present EvoGraph, a highly efficient and scalable GPU- based dynamic graph analytics framework.« less

Waveguide integrated superconducting single-photon detectors with high internal quantum efficiency at telecom wavelengths

PubMed Central

Kahl, Oliver; Ferrari, Simone; Kovalyuk, Vadim; Goltsman, Gregory N.; Korneev, Alexander; Pernice, Wolfram H. P.

2015-01-01

Superconducting nanowire single-photon detectors (SNSPDs) provide high efficiency for detecting individual photons while keeping dark counts and timing jitter minimal. Besides superior detection performance over a broad optical bandwidth, compatibility with an integrated optical platform is a crucial requirement for applications in emerging quantum photonic technologies. Here we present SNSPDs embedded in nanophotonic integrated circuits which achieve internal quantum efficiencies close to unity at 1550 nm wavelength. This allows for the SNSPDs to be operated at bias currents far below the critical current where unwanted dark count events reach milli-Hz levels while on-chip detection efficiencies above 70% are maintained. The measured dark count rates correspond to noise-equivalent powers in the 10−19 W/Hz−1/2 range and the timing jitter is as low as 35 ps. Our detectors are fully scalable and interface directly with waveguide-based optical platforms. PMID:26061283

Waveguide integrated superconducting single-photon detectors with high internal quantum efficiency at telecom wavelengths.

PubMed

Kahl, Oliver; Ferrari, Simone; Kovalyuk, Vadim; Goltsman, Gregory N; Korneev, Alexander; Pernice, Wolfram H P

2015-06-10

Superconducting nanowire single-photon detectors (SNSPDs) provide high efficiency for detecting individual photons while keeping dark counts and timing jitter minimal. Besides superior detection performance over a broad optical bandwidth, compatibility with an integrated optical platform is a crucial requirement for applications in emerging quantum photonic technologies. Here we present SNSPDs embedded in nanophotonic integrated circuits which achieve internal quantum efficiencies close to unity at 1550 nm wavelength. This allows for the SNSPDs to be operated at bias currents far below the critical current where unwanted dark count events reach milli-Hz levels while on-chip detection efficiencies above 70% are maintained. The measured dark count rates correspond to noise-equivalent powers in the 10(-19) W/Hz(-1/2) range and the timing jitter is as low as 35 ps. Our detectors are fully scalable and interface directly with waveguide-based optical platforms.

Cobalt-embedded nitrogen-rich carbon nanotubes efficiently catalyze hydrogen evolution reaction at all pH values.

PubMed

Zou, Xiaoxin; Huang, Xiaoxi; Goswami, Anandarup; Silva, Rafael; Sathe, Bhaskar R; Mikmeková, Eliška; Asefa, Tewodros

2014-04-22

Despite being technically possible, splitting water to generate hydrogen is still practically unfeasible due mainly to the lack of sustainable and efficient catalysts for the half reactions involved. Herein we report the synthesis of cobalt-embedded nitrogen-rich carbon nanotubes (NRCNTs) that 1) can efficiently electrocatalyze the hydrogen evolution reaction (HER) with activities close to that of Pt and 2) function well under acidic, neutral or basic media alike, allowing them to be coupled with the best available oxygen-evolving catalysts-which also play crucial roles in the overall water-splitting reaction. The materials are synthesized by a simple, easily scalable synthetic route involving thermal treatment of Co(2+) -embedded graphitic carbon nitride derived from inexpensive starting materials (dicyandiamide and CoCl2 ). The materials' efficient catalytic activity is mainly attributed to their nitrogen dopants and concomitant structural defects. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Scalable and balanced dynamic hybrid data assimilation

NASA Astrophysics Data System (ADS)

Kauranne, Tuomo; Amour, Idrissa; Gunia, Martin; Kallio, Kari; Lepistö, Ahti; Koponen, Sampsa

2017-04-01

Scalability of complex weather forecasting suites is dependent on the technical tools available for implementing highly parallel computational kernels, but to an equally large extent also on the dependence patterns between various components of the suite, such as observation processing, data assimilation and the forecast model. Scalability is a particular challenge for 4D variational assimilation methods that necessarily couple the forecast model into the assimilation process and subject this combination to an inherently serial quasi-Newton minimization process. Ensemble based assimilation methods are naturally more parallel, but large models force ensemble sizes to be small and that results in poor assimilation accuracy, somewhat akin to shooting with a shotgun in a million-dimensional space. The Variational Ensemble Kalman Filter (VEnKF) is an ensemble method that can attain the accuracy of 4D variational data assimilation with a small ensemble size. It achieves this by processing a Gaussian approximation of the current error covariance distribution, instead of a set of ensemble members, analogously to the Extended Kalman Filter EKF. Ensemble members are re-sampled every time a new set of observations is processed from a new approximation of that Gaussian distribution which makes VEnKF a dynamic assimilation method. After this a smoothing step is applied that turns VEnKF into a dynamic Variational Ensemble Kalman Smoother VEnKS. In this smoothing step, the same process is iterated with frequent re-sampling of the ensemble but now using past iterations as surrogate observations until the end result is a smooth and balanced model trajectory. In principle, VEnKF could suffer from similar scalability issues as 4D-Var. However, this can be avoided by isolating the forecast model completely from the minimization process by implementing the latter as a wrapper code whose only link to the model is calling for many parallel and totally independent model runs, all of them implemented as parallel model runs themselves. The only bottleneck in the process is the gathering and scattering of initial and final model state snapshots before and after the parallel runs which requires a very efficient and low-latency communication network. However, the volume of data communicated is small and the intervening minimization steps are only 3D-Var, which means their computational load is negligible compared with the fully parallel model runs. We present example results of scalable VEnKF with the 4D lake and shallow sea model COHERENS, assimilating simultaneously continuous in situ measurements in a single point and infrequent satellite images that cover a whole lake, with the fully scalable VEnKF.

Scalable and responsive event processing in the cloud

PubMed Central

Suresh, Visalakshmi; Ezhilchelvan, Paul; Watson, Paul

2013-01-01

Event processing involves continuous evaluation of queries over streams of events. Response-time optimization is traditionally done over a fixed set of nodes and/or by using metrics measured at query-operator levels. Cloud computing makes it easy to acquire and release computing nodes as required. Leveraging this flexibility, we propose a novel, queueing-theory-based approach for meeting specified response-time targets against fluctuating event arrival rates by drawing only the necessary amount of computing resources from a cloud platform. In the proposed approach, the entire processing engine of a distinct query is modelled as an atomic unit for predicting response times. Several such units hosted on a single node are modelled as a multiple class M/G/1 system. These aspects eliminate intrusive, low-level performance measurements at run-time, and also offer portability and scalability. Using model-based predictions, cloud resources are efficiently used to meet response-time targets. The efficacy of the approach is demonstrated through cloud-based experiments. PMID:23230164

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE PAGES

Shen, Yiwen; Hattink, Maarten; Samadi, Payman; ...

2018-04-13

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Yiwen; Hattink, Maarten; Samadi, Payman

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Optimization of Multicomponent Behavioral and Biobehavioral Interventions for the Prevention and Treatment of HIV/AIDS

PubMed Central

Collins, Linda M.; Kugler, Kari C.; Gwadz, Marya Viorst

2015-01-01

To move society toward an AIDS-free generation, behavioral interventions for prevention and treatment of HIV/AIDS must be not only effective, but also cost-effective, efficient, and readily scalable. The purpose of this article is to introduce to the HIV/AIDS research community the multiphase optimization strategy (MOST), a new methodological framework inspired by engineering principles and designed to develop behavioral interventions that have these important characteristics. Many behavioral interventions comprise multiple components. In MOST, randomized experimentation is conducted to assess the individual performance of each intervention component, and whether its presence/absence/setting has an impact on the performance of other components. This information is used to engineer an intervention that meets a specific optimization criterion, defined a priori in terms of effectiveness, cost, cost-effectiveness, and/or scalability. MOST will enable intervention science to develop a coherent knowledge base about what works and does not work. Ultimately this will improve behavioral interventions systematically and incrementally. PMID:26238037

The Simulation of Read-time Scalable Coherent Interface

NASA Technical Reports Server (NTRS)

Li, Qiang; Grant, Terry; Grover, Radhika S.

1997-01-01

Scalable Coherent Interface (SCI, IEEE/ANSI Std 1596-1992) (SCI1, SCI2) is a high performance interconnect for shared memory multiprocessor systems. In this project we investigate an SCI Real Time Protocols (RTSCI1) using Directed Flow Control Symbols. We studied the issues of efficient generation of control symbols, and created a simulation model of the protocol on a ring-based SCI system. This report presents the results of the study. The project has been implemented using SES/Workbench. The details that follow encompass aspects of both SCI and Flow Control Protocols, as well as the effect of realistic client/server processing delay. The report is organized as follows. Section 2 provides a description of the simulation model. Section 3 describes the protocol implementation details. The next three sections of the report elaborate on the workload, results and conclusions. Appended to the report is a description of the tool, SES/Workbench, used in our simulation, and internal details of our implementation of the protocol.

The GBS code for tokamak scrape-off layer simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halpern, F.D., E-mail: federico.halpern@epfl.ch; Ricci, P.; Jolliet, S.

2016-06-15

We describe a new version of GBS, a 3D global, flux-driven plasma turbulence code to simulate the turbulent dynamics in the tokamak scrape-off layer (SOL), superseding the code presented by Ricci et al. (2012) [14]. The present work is driven by the objective of studying SOL turbulent dynamics in medium size tokamaks and beyond with a high-fidelity physics model. We emphasize an intertwining framework of improved physics models and the computational improvements that allow them. The model extensions include neutral atom physics, finite ion temperature, the addition of a closed field line region, and a non-Boussinesq treatment of the polarizationmore » drift. GBS has been completely refactored with the introduction of a 3-D Cartesian communicator and a scalable parallel multigrid solver. We report dramatically enhanced parallel scalability, with the possibility of treating electromagnetic fluctuations very efficiently. The method of manufactured solutions as a verification process has been carried out for this new code version, demonstrating the correct implementation of the physical model.« less

Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daily, Jeffrey A.; Lewis, Robert R.

2011-11-30

Global Arrays is a software system from Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate distributed dense arrays. The NumPy module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. NumPy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, NumPy is inherently serial. Using a combination of Global Arrays and NumPy, we have reimplemented NumPy as a distributed drop-in replacement calledmore » Global Arrays in NumPy (GAiN). Serial NumPy applications can become parallel, scalable GAiN applications with only minor source code changes. Scalability studies of several different GAiN applications will be presented showing the utility of developing serial NumPy codes which can later run on more capable clusters or supercomputers.« less

BlueSky Cloud Framework: An E-Learning Framework Embracing Cloud Computing

NASA Astrophysics Data System (ADS)

Dong, Bo; Zheng, Qinghua; Qiao, Mu; Shu, Jian; Yang, Jie

Currently, E-Learning has grown into a widely accepted way of learning. With the huge growth of users, services, education contents and resources, E-Learning systems are facing challenges of optimizing resource allocations, dealing with dynamic concurrency demands, handling rapid storage growth requirements and cost controlling. In this paper, an E-Learning framework based on cloud computing is presented, namely BlueSky cloud framework. Particularly, the architecture and core components of BlueSky cloud framework are introduced. In BlueSky cloud framework, physical machines are virtualized, and allocated on demand for E-Learning systems. Moreover, BlueSky cloud framework combines with traditional middleware functions (such as load balancing and data caching) to serve for E-Learning systems as a general architecture. It delivers reliable, scalable and cost-efficient services to E-Learning systems, and E-Learning organizations can establish systems through these services in a simple way. BlueSky cloud framework solves the challenges faced by E-Learning, and improves the performance, availability and scalability of E-Learning systems.

Scalable focused ion beam creation of nearly lifetime-limited single quantum emitters in diamond nanostructures

PubMed Central

Schröder, Tim; Trusheim, Matthew E.; Walsh, Michael; Li, Luozhou; Zheng, Jiabao; Schukraft, Marco; Sipahigil, Alp; Evans, Ruffin E.; Sukachev, Denis D.; Nguyen, Christian T.; Pacheco, Jose L.; Camacho, Ryan M.; Bielejec, Edward S.; Lukin, Mikhail D.; Englund, Dirk

2017-01-01

The controlled creation of defect centre—nanocavity systems is one of the outstanding challenges for efficiently interfacing spin quantum memories with photons for photon-based entanglement operations in a quantum network. Here we demonstrate direct, maskless creation of atom-like single silicon vacancy (SiV) centres in diamond nanostructures via focused ion beam implantation with ∼32 nm lateral precision and <50 nm positioning accuracy relative to a nanocavity. We determine the Si+ ion to SiV centre conversion yield to be ∼2.5% and observe a 10-fold conversion yield increase by additional electron irradiation. Low-temperature spectroscopy reveals inhomogeneously broadened ensemble emission linewidths of ∼51 GHz and close to lifetime-limited single-emitter transition linewidths down to 126±13 MHz corresponding to ∼1.4 times the natural linewidth. This method for the targeted generation of nearly transform-limited quantum emitters should facilitate the development of scalable solid-state quantum information processors. PMID:28548097

Scalable focused ion beam creation of nearly lifetime-limited single quantum emitters in diamond nanostructures

DOE PAGES

Schroder, Tim; Trusheim, Matthew E.; Walsh, Michael; ...

2017-05-26

The controlled creation of defect centre—nanocavity systems is one of the outstanding challenges for efficiently interfacing spin quantum memories with photons for photon-based entanglement operations in a quantum network. Here we demonstrate direct, maskless creation of atom-like single silicon vacancy (SiV) centres in diamond nanostructures via focused ion beam implantation with ~32 nm lateral precision and <50 nm positioning accuracy relative to a nanocavity. We determine the Si+ ion to SiV centre conversion yield to be ~2.5% and observe a 10-fold conversion yield increase by additional electron irradiation. Low-temperature spectroscopy reveals inhomogeneously broadened ensemble emission linewidths of ~51 GHz andmore » close to lifetime-limited single-emitter transition linewidths down to 126±13 MHz corresponding to ~1.4 times the natural linewidth. Furthermore, this method for the targeted generation of nearly transform-limited quantum emitters should facilitate the development of scalable solid-state quantum information processors.« less

Scalable focused ion beam creation of nearly lifetime-limited single quantum emitters in diamond nanostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schroder, Tim; Trusheim, Matthew E.; Walsh, Michael

The controlled creation of defect centre—nanocavity systems is one of the outstanding challenges for efficiently interfacing spin quantum memories with photons for photon-based entanglement operations in a quantum network. Here we demonstrate direct, maskless creation of atom-like single silicon vacancy (SiV) centres in diamond nanostructures via focused ion beam implantation with ~32 nm lateral precision and <50 nm positioning accuracy relative to a nanocavity. We determine the Si+ ion to SiV centre conversion yield to be ~2.5% and observe a 10-fold conversion yield increase by additional electron irradiation. Low-temperature spectroscopy reveals inhomogeneously broadened ensemble emission linewidths of ~51 GHz andmore » close to lifetime-limited single-emitter transition linewidths down to 126±13 MHz corresponding to ~1.4 times the natural linewidth. Furthermore, this method for the targeted generation of nearly transform-limited quantum emitters should facilitate the development of scalable solid-state quantum information processors.« less

Optimization of Multicomponent Behavioral and Biobehavioral Interventions for the Prevention and Treatment of HIV/AIDS.

PubMed

Collins, Linda M; Kugler, Kari C; Gwadz, Marya Viorst

2016-01-01

To move society toward an AIDS-free generation, behavioral interventions for prevention and treatment of HIV/AIDS must be not only effective, but also cost-effective, efficient, and readily scalable. The purpose of this article is to introduce to the HIV/AIDS research community the multiphase optimization strategy (MOST), a new methodological framework inspired by engineering principles and designed to develop behavioral interventions that have these important characteristics. Many behavioral interventions comprise multiple components. In MOST, randomized experimentation is conducted to assess the individual performance of each intervention component, and whether its presence/absence/setting has an impact on the performance of other components. This information is used to engineer an intervention that meets a specific optimization criterion, defined a priori in terms of effectiveness, cost, cost-effectiveness, and/or scalability. MOST will enable intervention science to develop a coherent knowledge base about what works and does not work. Ultimately this will improve behavioral interventions systematically and incrementally.

Single-photon imager based on a superconducting nanowire delay line

NASA Astrophysics Data System (ADS)

Zhao, Qing-Yuan; Zhu, Di; Calandri, Niccolò; Dane, Andrew E.; McCaughan, Adam N.; Bellei, Francesco; Wang, Hao-Zhu; Santavicca, Daniel F.; Berggren, Karl K.

2017-03-01

Detecting spatial and temporal information of individual photons is critical to applications in spectroscopy, communication, biological imaging, astronomical observation and quantum-information processing. Here we demonstrate a scalable single-photon imager using a single continuous superconducting nanowire that is not only a single-photon detector but also functions as an efficient microwave delay line. In this context, photon-detection pulses are guided in the nanowire and enable the readout of the position and time of photon-absorption events from the arrival times of the detection pulses at the nanowire's two ends. Experimentally, we slowed down the velocity of pulse propagation to ∼2% of the speed of light in free space. In a 19.7 mm long nanowire that meandered across an area of 286 × 193 μm2, we were able to resolve ∼590 effective pixels with a temporal resolution of 50 ps (full width at half maximum). The nanowire imager presents a scalable approach for high-resolution photon imaging in space and time.

Scalable, efficient ASICS for the square kilometre array: From A/D conversion to central correlation

NASA Astrophysics Data System (ADS)

Schmatz, M. L.; Jongerius, R.; Dittmann, G.; Anghel, A.; Engbersen, T.; van Lunteren, J.; Buchmann, P.

2014-05-01

The Square Kilometre Array (SKA) is a future radio telescope, currently being designed by the worldwide radio-astronomy community. During the first of two construction phases, more than 250,000 antennas will be deployed, clustered in aperture-array stations. The antennas will generate 2.5 Pb/s of data, which needs to be processed in real time. For the processing stages from A/D conversion to central correlation, we propose an ASIC solution using only three chip architectures. The architecture is scalable - additional chips support additional antennas or beams - and versatile - it can relocate its receiver band within a range of a few MHz up to 4GHz. This flexibility makes it applicable to both SKA phases 1 and 2. The proposed chips implement an antenna and station processor for 289 antennas with a power consumption on the order of 600W and a correlator, including corner turn, for 911 stations on the order of 90 kW.

Toward Scalable Boson Sampling with Photon Loss

NASA Astrophysics Data System (ADS)

Wang, Hui; Li, Wei; Jiang, Xiao; He, Y.-M.; Li, Y.-H.; Ding, X.; Chen, M.-C.; Qin, J.; Peng, C.-Z.; Schneider, C.; Kamp, M.; Zhang, W.-J.; Li, H.; You, L.-X.; Wang, Z.; Dowling, J. P.; Höfling, S.; Lu, Chao-Yang; Pan, Jian-Wei

2018-06-01

Boson sampling is a well-defined task that is strongly believed to be intractable for classical computers, but can be efficiently solved by a specific quantum simulator. However, an outstanding problem for large-scale experimental boson sampling is the scalability. Here we report an experiment on boson sampling with photon loss, and demonstrate that boson sampling with a few photons lost can increase the sampling rate. Our experiment uses a quantum-dot-micropillar single-photon source demultiplexed into up to seven input ports of a 16 ×16 mode ultralow-loss photonic circuit, and we detect three-, four- and fivefold coincidence counts. We implement and validate lossy boson sampling with one and two photons lost, and obtain sampling rates of 187, 13.6, and 0.78 kHz for five-, six-, and seven-photon boson sampling with two photons lost, which is 9.4, 13.9, and 18.0 times faster than the standard boson sampling, respectively. Our experiment shows an approach to significantly enhance the sampling rate of multiphoton boson sampling.

Toward Scalable Boson Sampling with Photon Loss.

PubMed

Wang, Hui; Li, Wei; Jiang, Xiao; He, Y-M; Li, Y-H; Ding, X; Chen, M-C; Qin, J; Peng, C-Z; Schneider, C; Kamp, M; Zhang, W-J; Li, H; You, L-X; Wang, Z; Dowling, J P; Höfling, S; Lu, Chao-Yang; Pan, Jian-Wei

2018-06-08

Boson sampling is a well-defined task that is strongly believed to be intractable for classical computers, but can be efficiently solved by a specific quantum simulator. However, an outstanding problem for large-scale experimental boson sampling is the scalability. Here we report an experiment on boson sampling with photon loss, and demonstrate that boson sampling with a few photons lost can increase the sampling rate. Our experiment uses a quantum-dot-micropillar single-photon source demultiplexed into up to seven input ports of a 16×16 mode ultralow-loss photonic circuit, and we detect three-, four- and fivefold coincidence counts. We implement and validate lossy boson sampling with one and two photons lost, and obtain sampling rates of 187, 13.6, and 0.78 kHz for five-, six-, and seven-photon boson sampling with two photons lost, which is 9.4, 13.9, and 18.0 times faster than the standard boson sampling, respectively. Our experiment shows an approach to significantly enhance the sampling rate of multiphoton boson sampling.

Energy-efficient quantum computing

NASA Astrophysics Data System (ADS)

Ikonen, Joni; Salmilehto, Juha; Möttönen, Mikko

2017-04-01

In the near future, one of the major challenges in the realization of large-scale quantum computers operating at low temperatures is the management of harmful heat loads owing to thermal conduction of cabling and dissipation at cryogenic components. This naturally raises the question that what are the fundamental limitations of energy consumption in scalable quantum computing. In this work, we derive the greatest lower bound for the gate error induced by a single application of a bosonic drive mode of given energy. Previously, such an error type has been considered to be inversely proportional to the total driving power, but we show that this limitation can be circumvented by introducing a qubit driving scheme which reuses and corrects drive pulses. Specifically, our method serves to reduce the average energy consumption per gate operation without increasing the average gate error. Thus our work shows that precise, scalable control of quantum systems can, in principle, be implemented without the introduction of excessive heat or decoherence.

Scalable Production of Mechanically Robust Antireflection Film for Omnidirectional Enhanced Flexible Thin Film Solar Cells.

PubMed

Wang, Min; Ma, Pengsha; Yin, Min; Lu, Linfeng; Lin, Yinyue; Chen, Xiaoyuan; Jia, Wei; Cao, Xinmin; Chang, Paichun; Li, Dongdong

2017-09-01

Antireflection (AR) at the interface between the air and incident window material is paramount to boost the performance of photovoltaic devices. 3D nanostructures have attracted tremendous interest to reduce reflection, while the structure is vulnerable to the harsh outdoor environment. Thus the AR film with improved mechanical property is desirable in an industrial application. Herein, a scalable production of flexible AR films is proposed with microsized structures by roll-to-roll imprinting process, which possesses hydrophobic property and much improved robustness. The AR films can be potentially used for a wide range of photovoltaic devices whether based on rigid or flexible substrates. As a demonstration, the AR films are integrated with commercial Si-based triple-junction thin film solar cells. The AR film works as an effective tool to control the light travel path and utilize the light inward more efficiently by exciting hybrid optical modes, which results in a broadband and omnidirectional enhanced performance.

Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets.

PubMed

Datta, Abhirup; Banerjee, Sudipto; Finley, Andrew O; Gelfand, Alan E

2016-01-01

Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provide fully model-based inference for large geostatistical datasets. We establish that the NNGP is a well-defined spatial process providing legitimate finite-dimensional Gaussian densities with sparse precision matrices. We embed the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed without storing or decomposing large matrices. The floating point operations (flops) per iteration of this algorithm is linear in the number of spatial locations, thereby rendering substantial scalability. We illustrate the computational and inferential benefits of the NNGP over competing methods using simulation studies and also analyze forest biomass from a massive U.S. Forest Inventory dataset at a scale that precludes alternative dimension-reducing methods. Supplementary materials for this article are available online.

Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets

PubMed Central

Datta, Abhirup; Banerjee, Sudipto; Finley, Andrew O.; Gelfand, Alan E.

2018-01-01

Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provide fully model-based inference for large geostatistical datasets. We establish that the NNGP is a well-defined spatial process providing legitimate finite-dimensional Gaussian densities with sparse precision matrices. We embed the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed without storing or decomposing large matrices. The floating point operations (flops) per iteration of this algorithm is linear in the number of spatial locations, thereby rendering substantial scalability. We illustrate the computational and inferential benefits of the NNGP over competing methods using simulation studies and also analyze forest biomass from a massive U.S. Forest Inventory dataset at a scale that precludes alternative dimension-reducing methods. Supplementary materials for this article are available online. PMID:29720777

Scalable Production of Mechanically Robust Antireflection Film for Omnidirectional Enhanced Flexible Thin Film Solar Cells

PubMed Central

Wang, Min; Ma, Pengsha; Lu, Linfeng; Lin, Yinyue; Chen, Xiaoyuan; Jia, Wei; Cao, Xinmin; Chang, Paichun

2017-01-01

Antireflection (AR) at the interface between the air and incident window material is paramount to boost the performance of photovoltaic devices. 3D nanostructures have attracted tremendous interest to reduce reflection, while the structure is vulnerable to the harsh outdoor environment. Thus the AR film with improved mechanical property is desirable in an industrial application. Herein, a scalable production of flexible AR films is proposed with microsized structures by roll‐to‐roll imprinting process, which possesses hydrophobic property and much improved robustness. The AR films can be potentially used for a wide range of photovoltaic devices whether based on rigid or flexible substrates. As a demonstration, the AR films are integrated with commercial Si‐based triple‐junction thin film solar cells. The AR film works as an effective tool to control the light travel path and utilize the light inward more efficiently by exciting hybrid optical modes, which results in a broadband and omnidirectional enhanced performance. PMID:28932667

Precise and Efficient Static Array Bound Checking for Large Embedded C Programs

NASA Technical Reports Server (NTRS)

Venet, Arnaud

2004-01-01

In this paper we describe the design and implementation of a static array-bound checker for a family of embedded programs: the flight control software of recent Mars missions. These codes are large (up to 250 KLOC), pointer intensive, heavily multithreaded and written in an object-oriented style, which makes their analysis very challenging. We designed a tool called C Global Surveyor (CGS) that can analyze the largest code in a couple of hours with a precision of 80%. The scalability and precision of the analyzer are achieved by using an incremental framework in which a pointer analysis and a numerical analysis of array indices mutually refine each other. CGS has been designed so that it can distribute the analysis over several processors in a cluster of machines. To the best of our knowledge this is the first distributed implementation of static analysis algorithms. Throughout the paper we will discuss the scalability setbacks that we encountered during the construction of the tool and their impact on the initial design decisions.

Molecular metal-Nx centres in porous carbon for electrocatalytic hydrogen evolution

NASA Astrophysics Data System (ADS)

Liang, Hai-Wei; Brüller, Sebastian; Dong, Renhao; Zhang, Jian; Feng, Xinliang; Müllen, Klaus

2015-08-01

Replacement of precious platinum with efficient and low-cost catalysts for electrocatalytic hydrogen evolution at low overpotentials holds tremendous promise for clean energy devices. Here we report a novel type of robust cobalt-nitrogen/carbon catalyst for the hydrogen evolution reaction (HER) that is prepared by the pyrolysis of cobalt-N4 macrocycles or cobalt/o-phenylenediamine composites and using silica colloids as a hard template. We identify the well-dispersed molecular CoNx sites on the carbon support as the active sites responsible for the HER. The CoNx/C catalyst exhibits extremely high turnover frequencies per cobalt site in acids, for example, 0.39 and 6.5 s-1 at an overpotential of 100 and 200 mV, respectively, which are higher than those reported for other scalable non-precious metal HER catalysts. Our results suggest the great promise of developing new families of non-precious metal HER catalysts based on the controlled conversion of homogeneous metal complexes into solid-state carbon catalysts via economically scalable protocols.

SCTP as scalable video coding transport

NASA Astrophysics Data System (ADS)

Ortiz, Jordi; Graciá, Eduardo Martínez; Skarmeta, Antonio F.

2013-12-01

This study presents an evaluation of the Stream Transmission Control Protocol (SCTP) for the transport of the scalable video codec (SVC), proposed by MPEG as an extension to H.264/AVC. Both technologies fit together properly. On the one hand, SVC permits to split easily the bitstream into substreams carrying different video layers, each with different importance for the reconstruction of the complete video sequence at the receiver end. On the other hand, SCTP includes features, such as the multi-streaming and multi-homing capabilities, that permit to transport robustly and efficiently the SVC layers. Several transmission strategies supported on baseline SCTP and its concurrent multipath transfer (CMT) extension are compared with the classical solutions based on the Transmission Control Protocol (TCP) and the Realtime Transmission Protocol (RTP). Using ns-2 simulations, it is shown that CMT-SCTP outperforms TCP and RTP in error-prone networking environments. The comparison is established according to several performance measurements, including delay, throughput, packet loss, and peak signal-to-noise ratio of the received video.

Frequency-domain nonlinear optics in two-dimensionally patterned quasi-phase-matching media.

PubMed

Phillips, C R; Mayer, B W; Gallmann, L; Keller, U

2016-07-11

Advances in the amplification and manipulation of ultrashort laser pulses have led to revolutions in several areas. Examples include chirped pulse amplification for generating high peak-power lasers, power-scalable amplification techniques, pulse shaping via modulation of spatially-dispersed laser pulses, and efficient frequency-mixing in quasi-phase-matched nonlinear crystals to access new spectral regions. In this work, we introduce and demonstrate a new platform for nonlinear optics which has the potential to combine these separate functionalities (pulse amplification, frequency transfer, and pulse shaping) into a single monolithic device that is bandwidth- and power-scalable. The approach is based on two-dimensional (2D) patterning of quasi-phase-matching (QPM) gratings combined with optical parametric interactions involving spatially dispersed laser pulses. Our proof of principle experiment demonstrates this technique via mid-infrared optical parametric chirped pulse amplification of few-cycle pulses. Additionally, we present a detailed theoretical and numerical analysis of such 2D-QPM devices and how they can be designed.

Landscape Ecology and Epidemiology of Malaria Associated with Rubber Plantations in Thailand: Integrated Approaches to Malaria Ecotoping

PubMed Central

Kaewwaen, Wuthichai

2015-01-01

The agricultural land use changes that are human-induced changes in agroforestry ecosystems and in physical environmental conditions contribute substantially to the potential risks for malaria transmission in receptive areas. Due to the pattern and extent of land use change, the risks or negatively ecosystemic outcomes are the results of the dynamics of malaria transmission, the susceptibility of human populations, and the geographical distribution of malaria vectors. This review focused basically on what are the potential effects of agricultural land use change as a result of the expansion of rubber plantations in Thailand and how significant the ecotopes of malaria-associated rubber plantations (MRP) are. More profoundly, this review synthesized the novel concepts and perspectives on applied landscape ecology and epidemiology of malaria, as well as approaches to determine the degree to which an MRP ecotope as fundamental landscape scale can establish malaria infection pocket(s). Malaria ecotoping encompasses the integrated approaches and tools applied to or used in modeling malaria transmission. The scalability of MRP ecotope depends upon its unique landscape structure as it is geographically associated with the infestation or reinfestation of Anopheles vectors, along with the attributes that are epidemiologically linked with the infections. The MRP ecotope can be depicted as the hotspot such that malaria transmission is modeled upon the MRP factors underlying human settlements and movement activities, health behaviors, land use/land cover change, malaria vector population dynamics, and agrienvironmental and climatic conditions. The systemic and uniform approaches to malaria ecotoping underpin the stratification of the potential risks for malaria transmission by making use of remotely sensed satellite imagery or landscape aerial photography using unmanned aerial vehicle (UAV), global positioning systems (GPS), and geographical information systems (GIS). PMID:25838822

Wood-Graphene Oxide Composite for Highly Efficient Solar Steam Generation and Desalination.

PubMed

Liu, Keng-Ku; Jiang, Qisheng; Tadepalli, Sirimuvva; Raliya, Ramesh; Biswas, Pratim; Naik, Rajesh R; Singamaneni, Srikanth

2017-03-01

Solar steam generation is a highly promising technology for harvesting solar energy, desalination and water purification. We introduce a novel bilayered structure composed of wood and graphene oxide (GO) for highly efficient solar steam generation. The GO layer deposited on the microporous wood provides broad optical absorption and high photothermal conversion resulting in rapid increase in the temperature at the liquid surface. On the other hand, wood serves as a thermal insulator to confine the photothermal heat to the evaporative surface and to facilitate the efficient transport of water from the bulk to the photothermally active space. Owing to the tailored bilayer structure and the optimal thermo-optical properties of the individual components, the wood-GO composite structure exhibited a solar thermal efficiency of ∼83% under simulated solar excitation at a power density of 12 kW/m 2 . The novel composite structure demonstrated here is highly scalable and cost-efficient, making it an attractive material for various applications involving large light absorption, photothermal conversion and heat localization.

Ultrafast laser direct hard-mask writing for high efficiency c-Si texture designs

NASA Astrophysics Data System (ADS)

Kumar, Kitty; Lee, Kenneth K. C.; Nogami, Jun; Herman, Peter R.; Kherani, Nazir P.

2013-03-01

This study reports a high-resolution hard-mask laser writing technique to facilitate the selective etching of crystalline silicon (c-Si) into an inverted-pyramidal texture with feature size and periodicity on the order of the wavelength which, thus, provides for both anti-reflection and effective light-trapping of infrared and visible light. The process also enables engineered positional placement of the inverted-pyramid thereby providing another parameter for optimal design of an optically efficient pattern. The proposed technique, a non-cleanroom process, is scalable for large area micro-fabrication of high-efficiency thin c-Si photovoltaics. Optical wave simulations suggest the fabricated textured surface with 1.3 μm inverted-pyramids and a single anti-reflective coating increases the relative energy conversion efficiency by 11% compared to the PERL-cell texture with 9 μm inverted pyramids on a 400 μm thick wafer. This efficiency gain is anticipated to improve further for thinner wafers due to enhanced diffractive light trapping effects.

Reflecting anastigmatic optical systems: a retrospective

NASA Astrophysics Data System (ADS)

Rakich, Andrew

2017-11-01

Reflecting anastigmatic optical systems hold several inherent advantages over refracting equivalents; such as compactness, absence of color, high "refractive efficiency", wide bandwidth, and size-scalability to enormous apertures. Such advantages have led to these systems becoming, increasingly since their first deliberate development in 1905, the "go-to" solution for various classes of optical design problem. This paper describes in broad terms the history of the development of this class of optical system, with an emphasis on the early history.

Packet-aware transport for video distribution [Invited

NASA Astrophysics Data System (ADS)

Aguirre-Torres, Luis; Rosenfeld, Gady; Bruckman, Leon; O'Connor, Mannix

2006-05-01

We describe a solution based on resilient packet rings (RPR) for the distribution of broadcast video and video-on-demand (VoD) content over a packet-aware transport network. The proposed solution is based on our experience in the design and deployment of nationwide Triple Play networks and relies on technologies such as RPR, multiprotocol label switching (MPLS), and virtual private LAN service (VPLS) to provide the most efficient solution in terms of utilization, scalability, and availability.

Supporting Social Data Observatory with Customizable Index Structures on HBase - Architecture and Performance

DTIC Science & Technology

2013-01-01

commercial NoSQL database system. The results show that In-dexedHBase provides a data loading speed that is 6 times faster than Riak, and is...compare it with Riak, a widely adopted commercial NoSQL database system. The results show that In- dexedHBase provides a data loading speed that is 6...events. This chapter describes our research towards building an efficient and scalable storage platform for Truthy. Many existing NoSQL databases

Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

PubMed Central

Zhu, Xiang; Zhang, Dianwen

2013-01-01

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel

Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less

Possibly scalable solar hydrogen generation with quasi-artificial leaf approach.

PubMed

Patra, Kshirodra Kumar; Bhuskute, Bela D; Gopinath, Chinnakonda S

2017-07-26

Any solar energy harvesting technology must provide a net positive energy balance, and artificial leaf concept provided a platform for solar water splitting (SWS) towards that. However, device stability, high photocurrent generation, and scalability are the major challenges. A wireless device based on quasi-artificial leaf concept (QuAL), comprising Au on porous TiO 2 electrode sensitized by PbS and CdS quantum dots (QD), was demonstrated to show sustainable solar hydrogen (490 ± 25 µmol/h (corresponds to 12 ml H 2 h -1 ) from ~2 mg of photoanode material coated over 1 cm 2 area with aqueous hole (S 2- /SO 3 2- ) scavenger. A linear extrapolation of the above results could lead to hydrogen production of 6 L/h.g over an area of ~23 × 23 cm 2 . Under one sun conditions, 4.3 mA/cm 2 photocurrent generation, 5.6% power conversion efficiency, and spontaneous H 2 generation were observed at no applied potential (see S1). A direct coupling of all components within themselves enhances the light absorption in the entire visible and NIR region and charge utilization. Thin film approach, as in DSSC, combined with porous titania enables networking of all the components of the device, and efficiently converts solar to chemical energy in a sustainable manner.

Development of permanent magnet MnAlC/polymer composites and flexible filament for bonding and 3D-printing technologies

PubMed Central

Rial, Javier; de Vicente, Javier; Skårman, Björn; Vidarsson, Hilmar; Larsson, Per-Olof

2018-01-01

Abstract Searching for high-performance permanent magnets components with no limitation in shape and dimensions is highly desired to overcome the present design and manufacturing restrictions, which affect the efficiency of the final devices in energy, automotive and aerospace sectors. Advanced 3D-printing of composite materials and related technologies is an incipient route to achieve functional structures avoiding the limitations of traditional manufacturing. Gas-atomized MnAlC particles combined with polymer have been used in this work for fabricating scalable rare earth-free permanent magnet composites and extruded flexible filaments with continuous length exceeding 10 m. Solution casting has been used to synthesize homogeneous composites with tuned particles content, made of a polyethylene (PE) matrix embedding quasi-spherical particles of the ferromagnetic τ-MnAlC phase. A maximum filling factor of 86.5 and 72.3% has been obtained for the composite and the filament after extrusion, respectively. The magnetic measurements reveal no deterioration of the properties of the MnAlC particles after the composite synthesis and filament extrusion. The produced MnAlC/PE materials will serve as precursors for an efficient and scalable design and fabrication of end-products by different processing techniques (polymerized cold-compacted magnets and 3D-printing, respectively) in view of technological applications (from micro electromechanical systems to energy and transport applications). PMID:29887921

A massively parallel strategy for STR marker development, capture, and genotyping.

PubMed

Kistler, Logan; Johnson, Stephen M; Irwin, Mitchell T; Louis, Edward E; Ratan, Aakrosh; Perry, George H

2017-09-06

Short tandem repeat (STR) variants are highly polymorphic markers that facilitate powerful population genetic analyses. STRs are especially valuable in conservation and ecological genetic research, yielding detailed information on population structure and short-term demographic fluctuations. Massively parallel sequencing has not previously been leveraged for scalable, efficient STR recovery. Here, we present a pipeline for developing STR markers directly from high-throughput shotgun sequencing data without a reference genome, and an approach for highly parallel target STR recovery. We employed our approach to capture a panel of 5000 STRs from a test group of diademed sifakas (Propithecus diadema, n = 3), endangered Malagasy rainforest lemurs, and we report extremely efficient recovery of targeted loci-97.3-99.6% of STRs characterized with ≥10x non-redundant sequence coverage. We then tested our STR capture strategy on P. diadema fecal DNA, and report robust initial results and suggestions for future implementations. In addition to STR targets, this approach also generates large, genome-wide single nucleotide polymorphism (SNP) panels from flanking regions. Our method provides a cost-effective and scalable solution for rapid recovery of large STR and SNP datasets in any species without needing a reference genome, and can be used even with suboptimal DNA more easily acquired in conservation and ecological studies. Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

DOE PAGES

Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel; ...

2017-03-08

Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less

Broadband and scalable mobile satellite communication system for future access networks

NASA Astrophysics Data System (ADS)

Ohata, Kohei; Kobayashi, Kiyoshi; Nakahira, Katsuya; Ueba, Masazumi

2005-07-01

Due to the recent market trends, NTT has begun research into next generation satellite communication systems, such as broadband and scalable mobile communication systems. One service application objective is to provide broadband Internet access for transportation systems, temporal broadband access networks and telemetries to remote areas. While these are niche markets the total amount of capacity should be significant. We set a 1-Gb/s total transmission capacity as our goal. Our key concern is the system cost, which means that the system should be unified system with diversified services and not tailored for each application. As satellites account for a large portion of the total system cost, we set the target satellite size as a small, one-ton class dry mass with a 2-kW class payload power. In addition to the payload power and weight, the mobile satellite's frequency band is extremely limited. Therefore, we need to develop innovative technologies that will reduce the weight and maximize spectrum and power efficiency. Another challenge is the need for the system to handle up to 50 dB and a wide data rate range of other applications. This paper describes the key communication system technologies; the frequency reuse strategy, multiplexing scheme, resource allocation scheme, and QoS management algorithm to ensure excellent spectrum efficiency and support a variety of services and quality requirements in the mobile environment.

SAChES: Scalable Adaptive Chain-Ensemble Sampling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swiler, Laura Painton; Ray, Jaideep; Ebeida, Mohamed Salah

We present the development of a parallel Markov Chain Monte Carlo (MCMC) method called SAChES, Scalable Adaptive Chain-Ensemble Sampling. This capability is targed to Bayesian calibration of com- putationally expensive simulation models. SAChES involves a hybrid of two methods: Differential Evo- lution Monte Carlo followed by Adaptive Metropolis. Both methods involve parallel chains. Differential evolution allows one to explore high-dimensional parameter spaces using loosely coupled (i.e., largely asynchronous) chains. Loose coupling allows the use of large chain ensembles, with far more chains than the number of parameters to explore. This reduces per-chain sampling burden, enables high-dimensional inversions and the usemore » of computationally expensive forward models. The large number of chains can also ameliorate the impact of silent-errors, which may affect only a few chains. The chain ensemble can also be sampled to provide an initial condition when an aberrant chain is re-spawned. Adaptive Metropolis takes the best points from the differential evolution and efficiently hones in on the poste- rior density. The multitude of chains in SAChES is leveraged to (1) enable efficient exploration of the parameter space; and (2) ensure robustness to silent errors which may be unavoidable in extreme-scale computational platforms of the future. This report outlines SAChES, describes four papers that are the result of the project, and discusses some additional results.« less

Development of permanent magnet MnAlC/polymer composites and flexible filament for bonding and 3D-printing technologies.

PubMed

Palmero, Ester M; Rial, Javier; de Vicente, Javier; Camarero, Julio; Skårman, Björn; Vidarsson, Hilmar; Larsson, Per-Olof; Bollero, Alberto

2018-01-01

Searching for high-performance permanent magnets components with no limitation in shape and dimensions is highly desired to overcome the present design and manufacturing restrictions, which affect the efficiency of the final devices in energy, automotive and aerospace sectors. Advanced 3D-printing of composite materials and related technologies is an incipient route to achieve functional structures avoiding the limitations of traditional manufacturing. Gas-atomized MnAlC particles combined with polymer have been used in this work for fabricating scalable rare earth-free permanent magnet composites and extruded flexible filaments with continuous length exceeding 10 m. Solution casting has been used to synthesize homogeneous composites with tuned particles content, made of a polyethylene (PE) matrix embedding quasi-spherical particles of the ferromagnetic τ -MnAlC phase. A maximum filling factor of 86.5 and 72.3% has been obtained for the composite and the filament after extrusion, respectively. The magnetic measurements reveal no deterioration of the properties of the MnAlC particles after the composite synthesis and filament extrusion. The produced MnAlC/PE materials will serve as precursors for an efficient and scalable design and fabrication of end-products by different processing techniques (polymerized cold-compacted magnets and 3D-printing, respectively) in view of technological applications (from micro electromechanical systems to energy and transport applications).

WearETE: A Scalable Wearable E-Textile Triboelectric Energy Harvesting System for Human Motion Scavenging

PubMed Central

Li, Xian

2017-01-01

In this paper, we report the design, experimental validation and application of a scalable, wearable e-textile triboelectric energy harvesting (WearETE) system for scavenging energy from activities of daily living. The WearETE system features ultra-low-cost material and manufacturing methods, high accessibility, and high feasibility for powering wearable sensors and electronics. The foam and e-textile are used as the two active tribomaterials for energy harvester design with the consideration of flexibility and wearability. A calibration platform is also developed to quantify the input mechanical power and power efficiency. The performance of the WearETE system for human motion scavenging is validated and calibrated through experiments. The results show that the wearable triboelectric energy harvester can generate over 70 V output voltage which is capable of powering over 52 LEDs simultaneously with a 9 × 9 cm2 area. A larger version is able to lighten 190 LEDs during contact-separation process. The WearETE system can generate a maximum power of 4.8113 mW from hand clapping movements under the frequency of 4 Hz. The average power efficiency can be up to 24.94%. The output power harvested by the WearETE system during slow walking is 7.5248 µW. The results show the possibility of powering wearable electronics during human motion. PMID:29149035

Efficient dehydration and recovery of ionic liquid after lignocellulosic processing using pervaporation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Jian; Shi, Jian; Murthy Konda, N. V. S. N.

Background Biomass pretreatment using certain ionic liquids (ILs) is very efficient, generally producing a substrate that is amenable to saccharification with fermentable sugar yields approaching theoretical limits. Although promising, several challenges must be addressed before an IL pretreatment technology can become commercially viable. One of the most significant challenges is the affordable and scalable recovery and recycle of the IL itself. Pervaporation (PV) is a highly selective and scalable membrane separation process for quantitatively recovering volatile solutes or solvents directly from non-volatile solvents that could prove more versatile for IL dehydration. Results We evaluated a commercially available PV system formore » IL dehydration and recycling as part of an integrated IL pretreatment process using 1-ethyl-3-methylimidazolium acetate ([C 2 C 1 Im][OAc] ) that has been proven to be very effective as a biomass pretreatment solvent. Separation factors as high as 1500 were observed. We demonstrate that > 99.9 wt% [C 2 C 1 Im][OAc] can be recovered from aqueous solution (≤20 wt% IL) and recycled five times. A preliminary technoeconomic analysis validated the promising role of PV in improving overall biorefinery process economics, especially in the case where other IL recovery technologies might lead to significant losses. Conclusions These findings establish the foundation for further development of PV as an effective method of recovering and recycling ILs using a commercially viable process technology.« less

Efficient dehydration and recovery of ionic liquid after lignocellulosic processing using pervaporation

DOE PAGES

Sun, Jian; Shi, Jian; Murthy Konda, N. V. S. N.; ...

2017-06-15

Background Biomass pretreatment using certain ionic liquids (ILs) is very efficient, generally producing a substrate that is amenable to saccharification with fermentable sugar yields approaching theoretical limits. Although promising, several challenges must be addressed before an IL pretreatment technology can become commercially viable. One of the most significant challenges is the affordable and scalable recovery and recycle of the IL itself. Pervaporation (PV) is a highly selective and scalable membrane separation process for quantitatively recovering volatile solutes or solvents directly from non-volatile solvents that could prove more versatile for IL dehydration. Results We evaluated a commercially available PV system formore » IL dehydration and recycling as part of an integrated IL pretreatment process using 1-ethyl-3-methylimidazolium acetate ([C 2 C 1 Im][OAc] ) that has been proven to be very effective as a biomass pretreatment solvent. Separation factors as high as 1500 were observed. We demonstrate that > 99.9 wt% [C 2 C 1 Im][OAc] can be recovered from aqueous solution (≤20 wt% IL) and recycled five times. A preliminary technoeconomic analysis validated the promising role of PV in improving overall biorefinery process economics, especially in the case where other IL recovery technologies might lead to significant losses. Conclusions These findings establish the foundation for further development of PV as an effective method of recovering and recycling ILs using a commercially viable process technology.« less

N- and S-doped high surface area carbon derived from soya chunks as scalable and efficient electrocatalysts for oxygen reduction

NASA Astrophysics Data System (ADS)

Rana, Moumita; Arora, Gunjan; Gautam, Ujjal K.

2015-02-01

Highly stable, cost-effective electrocatalysts facilitating oxygen reduction are crucial for the commercialization of membrane-based fuel cell and battery technologies. Herein, we demonstrate that protein-rich soya chunks with a high content of N, S and P atoms are an excellent precursor for heteroatom-doped highly graphitized carbon materials. The materials are nanoporous, with a surface area exceeding 1000 m2 g-1, and they are tunable in doping quantities. These materials exhibit highly efficient catalytic performance toward oxygen reduction reaction (ORR) with an onset potential of -0.045 V and a half-wave potential of -0.211 V (versus a saturated calomel electrode) in a basic medium, which is comparable to commercial Pt catalysts and is better than other recently developed metal-free carbon-based catalysts. These exhibit complete methanol tolerance and a performance degradation of merely ˜5% as compared to ˜14% for a commercial Pt/C catalyst after continuous use for 3000 s at the highest reduction current. We found that the fraction of graphitic N increases at a higher graphitization temperature, leading to the near complete reduction of oxygen. It is believed that due to the easy availability of the precursor and the possibility of genetic engineering to homogeneously control the heteroatom distribution, the synthetic strategy is easily scalable, with further improvement in performance.

Feeder & basic fibroblast growth factor-free culture of human embryonic stem cells: Role of conditioned medium from immortalized human feeders.

PubMed

Teotia, Pooja; Sharma, Shilpa; Airan, Balram; Mohanty, Sujata

2016-12-01

Human embryonic stem cell (hESC) lines are commonly maintained on inactivated feeder cells, in the medium supplemented with basic fibroblast growth factor (bFGF). However, limited availability of feeder cells in culture, and the high cost of growth factors limit their use in scalable expansion of hESC cultures for clinical application. Here, we describe an efficient and cost-effective feeder and bFGF-free culture of hESCs using conditioned medium (CM) from immortalized feeder cells. KIND-1 hESC cell line was cultured in CM, collected from primary mouse embryonic fibroblast, human foreskin fibroblast (HFF) and immortalized HFF (I-HFF). Pluripotency of KIND-1 hESC cell line was confirmed by expression of genes, proteins and cell surface markers. In culture, these cells retained normal morphology, expressed all cell surface markers, could differentiate to embryoid bodies upon culture in vitro. Furthermore, I-HFF feeder cells without supplementation of bFGF released ample amount of endogenous bFGF to maintain stemness of hESC cells. The study results described the use of CM from immortalized feeder cells as a consistent source and an efficient, inexpensive feeder-free culture system for the maintenance of hESCs. Moreover, it was possible to maintain hESCs without exogenous supplementation of bFGF. Thus, the study could be extended to scalable expansion of hESC cultures for therapeutic purposes.

Enhanced Mixed Feedstock Processing Using Ionic Liquids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmons, Blake A

2016-10-22

Biomass pretreatment using certain ionic liquids (ILs) is very efficient, generally producing a substrate that is amenable to saccharification with fermentable sugar yields approaching theoretical limits. Although promising, several challenges must be addressed before IL pretreatment technology becomes commercially viable. Once of the most significant challenges is the affordable and scalable recovery and recycle or the IL itself. Pervaporation is a highly selective and scalable membrane separation process for quantitatively recovering volatile solutes or solvents directly from non-volatile solvents that could prove more versatile for IL dehydration than traditional solvent extraction processes, as well as efficient and energetically more advantageousmore » than standard evaporative techniques. In this study we evaluated a commercially available pervaporation system for IL dehydration and recycling as part of an integrated IL pretreatment process using 1-ethyl-3-methylimidazolium acetate ([C2C1Im][OAc]) that has been proven to be very effective as a biomass pretreatment solvent. We demonstrate that >99.9 wt% [C2C1Im][OAc] can be recovered from aqueous solution and recycled at least five times. A preliminary techno-economic analysis validated the promising role of pervaporation in improving overall biorefinery process economics, especially in the case where other IL recovery technologies might lead to significant losses. These findings establish the foundation for further development of pervaporation as an effective method of recovering and recycling ILs using a commercially viable process technology.« less

A Scalable Context-Aware Objective Function (SCAOF) of Routing Protocol for Agricultural Low-Power and Lossy Networks (RPAL).

PubMed

Chen, Yibo; Chanet, Jean-Pierre; Hou, Kun-Mean; Shi, Hongling; de Sousa, Gil

2015-08-10

In recent years, IoT (Internet of Things) technologies have seen great advances, particularly, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL), which provides a powerful and flexible routing framework that can be applied in a variety of application scenarios. In this context, as an important role of IoT, Wireless Sensor Networks (WSNs) can utilize RPL to design efficient routing protocols for a specific application to increase the ubiquity of networks with resource-constrained WSN nodes that are low-cost and easy to deploy. In this article, our work starts with the description of Agricultural Low-power and Lossy Networks (A-LLNs) complying with the LLN framework, and to clarify the requirements of this application-oriented routing solution. After a brief review of existing optimization techniques for RPL, our contribution is dedicated to a Scalable Context-Aware Objective Function (SCAOF) that can adapt RPL to the environmental monitoring of A-LLNs, through combining energy-aware, reliability-aware, robustness-aware and resource-aware contexts according to the composite routing metrics approach. The correct behavior of this enhanced RPL version (RPAL) was verified by performance evaluations on both simulation and field tests. The obtained experimental results confirm that SCAOF can deliver the desired advantages on network lifetime extension, and high reliability and efficiency in different simulation scenarios and hardware testbeds.

A Scalable Context-Aware Objective Function (SCAOF) of Routing Protocol for Agricultural Low-Power and Lossy Networks (RPAL)

PubMed Central

Chen, Yibo; Chanet, Jean-Pierre; Hou, Kun-Mean; Shi, Hongling; de Sousa, Gil

2015-01-01

In recent years, IoT (Internet of Things) technologies have seen great advances, particularly, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL), which provides a powerful and flexible routing framework that can be applied in a variety of application scenarios. In this context, as an important role of IoT, Wireless Sensor Networks (WSNs) can utilize RPL to design efficient routing protocols for a specific application to increase the ubiquity of networks with resource-constrained WSN nodes that are low-cost and easy to deploy. In this article, our work starts with the description of Agricultural Low-power and Lossy Networks (A-LLNs) complying with the LLN framework, and to clarify the requirements of this application-oriented routing solution. After a brief review of existing optimization techniques for RPL, our contribution is dedicated to a Scalable Context-Aware Objective Function (SCAOF) that can adapt RPL to the environmental monitoring of A-LLNs, through combining energy-aware, reliability-aware, robustness-aware and resource-aware contexts according to the composite routing metrics approach. The correct behavior of this enhanced RPL version (RPAL) was verified by performance evaluations on both simulation and field tests. The obtained experimental results confirm that SCAOF can deliver the desired advantages on network lifetime extension, and high reliability and efficiency in different simulation scenarios and hardware testbeds. PMID:26266411

N- and S-doped high surface area carbon derived from soya chunks as scalable and efficient electrocatalysts for oxygen reduction

PubMed Central

Rana, Moumita; Arora, Gunjan; Gautam, Ujjal K

2015-01-01

Highly stable, cost-effective electrocatalysts facilitating oxygen reduction are crucial for the commercialization of membrane-based fuel cell and battery technologies. Herein, we demonstrate that protein-rich soya chunks with a high content of N, S and P atoms are an excellent precursor for heteroatom-doped highly graphitized carbon materials. The materials are nanoporous, with a surface area exceeding 1000 m2 g−1, and they are tunable in doping quantities. These materials exhibit highly efficient catalytic performance toward oxygen reduction reaction (ORR) with an onset potential of −0.045 V and a half-wave potential of −0.211 V (versus a saturated calomel electrode) in a basic medium, which is comparable to commercial Pt catalysts and is better than other recently developed metal-free carbon-based catalysts. These exhibit complete methanol tolerance and a performance degradation of merely ∼5% as compared to ∼14% for a commercial Pt/C catalyst after continuous use for 3000 s at the highest reduction current. We found that the fraction of graphitic N increases at a higher graphitization temperature, leading to the near complete reduction of oxygen. It is believed that due to the easy availability of the precursor and the possibility of genetic engineering to homogeneously control the heteroatom distribution, the synthetic strategy is easily scalable, with further improvement in performance. PMID:27877746

Recent Advances in Design of Low Cost Film Concentrator and Low Pressure Free Piston Stirling Engines for Solar Power

NASA Technical Reports Server (NTRS)

Kleinwaechter, J.; Kleinwaechter, H.; Beale, W.

1984-01-01

The free piston Stirling-linear alternator was shown to be scalable to power levels of tens of kilowatts in a form which is simple, efficient, long lived and relatively inexpensive. It avoids entirely the vexing problem of high pressure shaft, and its control requirements are not severe nor do they represent a significant threat to durability. Linear alternators have demonstrated high efficiency and moderate weight, and are capable of delivering 3 phase power from single machines without great increases of cost or complexity. There remains no apparent impediments to the commercial exploitation of the free piston engine for solar electric power generation.