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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

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Rewriting Complex SPARQL Analytical Queries for Efficient Cloud-based processing 3

Rewriting Complex SPARQL Analytical Queries for Efficient Cl...

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IEEE international conference on Big Data

作者： Ravindra, Padmashree Kim, HyeongSik Anyanwu, Kemafor Microsoft Corp Redmond WA 98052 USA North Carolina State Univ Raleigh NC 27695 USA

ISBN: (纸本)9781479999255

Many emerging Semantic Web applications combine and aggregate data across domains for analysis. Such analytical queries compute aggregates over multiple groupings of data, resulting in query plans with complex grouping-aggregation constraints. In the context of an RDF analytical query, each such grouping maps to a graph pattern subquery with multiple join operations, and related groups often result in overlapping graph patterns within the same query. In this paper, we propose a holistic approach to optimize RDF analytical queries by refactoring queries to achieve shared execution of common subexpressions that enables parallel evaluation of groupings as well as aggregations. Such a rewriting enables shorter execution workflows, particularly beneficial for scale-out processing on distributed Cloud systems with multiple I/O phases. Experiments on real-world and synthetic benchmarks confirm that such a rewriting can achieve more efficient execution plans when compared to relational-style SPARQL query plans executed on popular Cloud systems.

关键词： RDF Analytics Hadoop MapReduce Query Rewriting SPARQL Semantic Web

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Performance Optimization of AC-DC Bus Tie Line Bidirectional Converter for Microgrid applications

Performance Optimization of AC-DC Bus Tie Line Bidirectional...

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IEEE international conference on Signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Chaudhari, Pushkar Rane, Paris Bawankar, Amit Shete, Pranit Kalange, Kundan Lokhande, Smita Moghe, Archit Panda, Jyotiprakash Kadrolkar, Aditya Gaikwad, Kishor Bhor, Navnath Nikam, Vaibhav Coll Engn Pune Maharashtra India

ISBN: (纸本)9781479918232

COEP-Microgrid, project by the students of College of Engineering, Pune aims at establishing a microgrid in the college campus serving as a living laboratory for research and development of novel grid technologies. Proposed microgrid has a DC bus connected to solar cells, fuel cells and battery while AC-bus connected to wind power plants, pico hydro plant, Static Synchronous Compensator (STATCOM), local AC loads and to the electricity grid with an islanding scheme. To operate the energy sources at the DC bus in parallel with the electric grid, DC-AC tie line converter, i.e. grid tie inverter is required. This paper thus aims at the description of the entire design and implementation of the bidirectional grid tie inverter used in proposed microgrid application. The bidirectional grid tie inverter has a 2 level VSI topology with Sine Pulse Width Modulation (SPWM) based control strategy. Along with the design, the paper describes the synchronization techniques of the inverter with the grid through phase, frequency and voltage control methods. The proposed scheme discusses about the problems regarding its practical implementation and various optimization techniques used to improve its performance.

关键词： Bidirectional converter SPWM

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A framework to the design and programming of many-core focal-plane vision processors 13

A framework to the design and programming of many-core focal...

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13th international conference on Embedded and Ubiquitous Computing (EUC 2015)

作者： Mori, Jones Y. Llanos, Carlos Huebner, Michael Ruhr Univ Bochum Chair Embedded Syst Informat Technol ESIT Bochum Germany Univ Brasilia Dept Mech Engn BR-70910900 Brasilia DF Brazil

ISBN: (纸本)9781467382991

The Focal-Plane Image processing area aims to bring processing elements as near as possible to the pixels and to the camera's focal-plane. Most of the works reported in the literature uses only simple processing elements, in general analog ones, with few flexibility. With the technology advances, a new generation of Vision Processors is emerging. It is expected that multi/many-core systems will be integrated to the pixel sensors, offering several opportunities for parallelism exploration, resulting in high performance and flexible processing systems. The programmability is one of the main problems in this area, since most programmers are not able to create parallel algorithms and applications. In this work, we propose a methodology to the design and programming of many-core focal-plane vision processors. The application is described using a Domain Specific Language, from which the parallelism characteristics are extracted. Afterwards, a new abstract model is derived using techniques such as Program Slicing (PS) and Task-Graph Clustering (TGC). The abstract model is then transformed in a SystemC/TLM2.0 description, in order to allow for different timing accuracy simulations. The results of the simulations are used together with an ASIP design tool in order to determine both the microarchitecture of processing elements and the communication structure of the new system. Finally, from the model derived before, a new source code is generated and programmed into the new platform. In this context, the main concepts and ideas are described in this work, as well as some partial results.

关键词： Real-Time computer vision embedded computing focal-plane image processing many-core architecture Embedded computing images computer vision Programming communication structure core construction PROCESSOR Sight pixel processing Element Microarchitecture parallel algorithms Real time

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Design Space Exploration for Efficient Computing in Solid State Drives with the Storage processing Unit 10

Design Space Exploration for Efficient Computing in Solid St...

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IEEE international conference on Networking, Architecture and Storage (NAS 2015)

作者： Minglani, Manas Nagarajan, Ashwin Deshapande, Sneha Everson, Luke Lilja, David J. Univ Minnesota Twin Cities Dept Elect & Comp Engn Minneapolis MN 55455 USA

ISBN: (纸本)9781467378918

Computer architects face two major challenges in building future exa-scale systems: high energy consumption and the increasing gap between processor and storage speeds. Moving the processing closer to the data, inside the persistent storage, will help mitigate these challenges. This will result in a hierarchical compute structure across the system with a major component of the processing hierarchy inside the Solid State Drive. This new architecture is called the Storage processing Unit. We perform design space exploration and propose several optimizations to the application space and the architectural space. This research significantly improves the energy use and performance of the system. We observe energy savings from 11 - 423X and performance gains from 4 - 66X for applications including k-means, Sparse BLAS, and others.

关键词： Active flash storage systems SSD architecture energy-efficient computing hierarchical computation performance evaluation

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GPU-Accelerated Progressive Gaussian Filtering with applications to Extended Object Tracking 18

GPU-Accelerated Progressive Gaussian Filtering with Applicat...

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18th international conference on Information Fusion (Fusion)

作者： Steinbring, Jannik Hanebeck, Uwe D. Karlsruhe Inst Technol KIT Inst Anthropomat & Robot ISAS Karlsruhe Germany

ISBN: (纸本)9780982443866

Since the last years, Graphics processing Units (GPUs) have massive parallel execution capabilities even for non-graphic related applications. The field of nonlinear state estimation is no exception here. Particle Filters have already been successfully ported to GPUs. In this paper, we propose a GPU-accelerated variant of the Progressive Gaussian Filter (PGF). This allows us to combine the advantages of the particle flow with the ability to process thousands of measurements at once in order to improve state estimation quality. To get a meaningful comparison between its CPU and GPU variants, we additionally propose a likelihood for tracking a sphere and its extent in 3D based on noisy point measurements. The likelihood considers the physical relationship between sensor, measurement, and sphere to best exploit the information of the received measurements. We evaluate the GPU implementation of the PGF using the proposed likelihood in combination with tens of thousands of measurements. Although the CPU implementation fully exploits parallelization techniques such as SSE and OpenMP, the GPU-accelerated PGF reaches speedups over 20 and real-time tracking can nearly be achieved.

关键词： PGF GPU OpenCL Extended Object Tracking

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Design and Development of Domain Specific Active Libraries with Proxy applications

Design and Development of Domain Specific Active Libraries w...

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IEEE international conference on Cluster Computing (CLUSTER)

作者： Reguly, I. Z. Mudalige, G. R. Giles, M. B. Univ Oxford Oxford E Res Ctr Oxford OX1 2JD England Pazmany Peter Catholic Univ Fac Informat Technol & Bion Budapest Hungary

ISBN: (纸本)9781467365987

Representative applications are versatile tools to evaluate new programming approaches, techniques and optimisations as a way to ensure continued high performance on future computing architectures. They make experimentation much easier before adopting changes/insights into the large scientific codes. In this paper we demonstrate the important role played by representative/proxy applications in designing and developing two high-level programming approaches: namely the OP2 and OPS domain specific (active) libraries. OP2 and OPS utilizes code generation techniques to produce automatic parallelisations from a high-level abstract problem declaration. The strategy delivers significant developer productivity to the domain scientist, while at the same time allowing computational experts to adopt the latest programming models and hardware-specific optimisations into the library and code generation tools to achieve near optimal performance. We show how representative applications have been a cornerstone in the development of OP2 and OPS and chart our experiences. In particular, we demonstrate how the range of hand-tuned optimized parallelisations of the CloverLeaf hydrodynamics mini-app allowed us to gain clear evidence that the OPS based code generated parallelisations were indeed as optimal as the hand-tuned versions. Additionally, with the use of a representative application from the CFD domain we demonstrate how the optimisations discovered and applied to proxy apps are indeed directly transferable to a large-scale industrial application at Rolls Royce plc. These results provide significant evidence into the utility of representative applications to improve productivity, enable performance portability and ultimately future-proof scientific applications.

关键词： computational fluid dynamics hydrodynamics parallel programming program compilers software libraries CFD domain CloverLeaf hydrodynamics mini-app OPS domain specific active libraries Rolls Royce plc automatic parallelisations code generation technique computing architecture developer productivity future-proof scientific application hand-tuned optimized parallelisation hardware-specific optimisation high-level abstract problem declaration high-level programming approach large-scale industrial application near optimal performance performance portability programming model proxy application representative applications scientific codes Automotive components Computational modeling Computer architecture Graphics processing units Libraries Optimization Programming

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HeteroSpark: A Heterogeneous CPU/GPU Spark Platform for Machine Learning Algorithms 10

HeteroSpark: A Heterogeneous CPU/GPU Spark Platform for Mach...

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IEEE international conference on Networking, Architecture and Storage (NAS 2015)

作者： Li, Peilong Luo, Yan Zhang, Ning Cao, Yu Univ Massachusetts Lowell Dept Elect & Comp Engn Lowell MA 01852 USA Univ Massachusetts Lowell Dept Comp Sci Lowell MA 01852 USA

ISBN: (纸本)9781467378918

Analytics algorithms on big data sets require tremendous computational capabilities. Spark is a recent development that addresses big data challenges with data and computation distribution and in-memory caching. However, as a CPU only framework, Spark cannot leverage GPUs and a growing set of GPU libraries to achieve better performance and energy efficiency. We present HeteroSpark, a GPU-accelerated heterogeneous architecture integrated with Spark, which combines the massive compute power of GPUs and scalability of CPUs and system memory resources for applications that are both data and compute intensive. We make the following contributions in this work: ( 1) we integrate the GPU accelerator into current Spark framework to further leverage data parallelism and achieve algorithm acceleration;( 2) we provide a plug-n-play design by augmenting Spark platform so that current Spark applications can choose to enable/disable GPU acceleration;( 3) application acceleration is transparent to developers, therefore existing Spark applications can be easily ported to this heterogeneous platform without code modifications. The evaluation of HeteroSpark demonstrates up to 18x speedup on a number of machine learning applications.

关键词： Acceleration Big data Computer architecture Graphics processing units Libraries Machine learning algorithms Sparks

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Multimedia data integration and processing for E-government 21

Multimedia data integration and processing for E-government

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21st international conference on distributed Multimedia Systems, DMS 2015

作者： Amato, Flora Colace, Francesco Greco, Luca Moscato, Vincenzo Picariello, Antonio Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione University of Naples Federico II Italy Dipartimento di Ingegneria dell'Informazione Ingegneria Elettrica e Matematica Applicata University of Salerno Italy

ISBN: (纸本)1891706381

Knowledge management has become a challenge for almost all E-government based applications where one of the main problem is the efficient management of great amounts of data. In order to efficiently access the information embedded in very large document repositories, techniques for semantic document management are required. They ensure improvement for a large and intense process of dematerialization and aim at eliminating or at least reducing, the amount of paper documents. In this work, we present a novel model of digital documents for the improvement of the dematerialization effectiveness. This model represents the starting point for an information system that is able to manage the document streams in an efficient way. It takes into account E-government applications needs like the compliance with the laws and regulations in force and the adaptability to evolving technologies. At the best of our knowledge, the proposed model is one of the first attempts to give a single and unified characterization for the management of multimedia documents, pertaining to a bureaucratic domain as the E-government one, on which semantic procedures are used for the transformation of non structured documents (pertaining to specialized domain) into structured data, suitable for automatic processing. Furthermore, an architecture for the management of documents life cycle is proposed, which provides advanced functionalities for semantic processing, such as giving formal structure to document informative content, information extraction, semantic retrieval, indexing, storage, presentation, together with long-term preservation.

关键词： Semantics

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15th international conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

15th International Conference on Algorithms and Architecture...

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15th international conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

ISBN: (纸本)9783319271187

The proceedings contain 58 papers. The special focus in this conference is on parallel and distributed Architectures. The topics include: parallelizing block cryptography algorithms on speculative multicores;performance characterization and optimization for intel xeon phi coprocessor;an extended MDS code to improve single write performance of disk arrays for correcting triple disk failures;a distributed location-based service discovery protocol for vehicular ad-hoc networks;unified virtual memory support for deep CNN accelerator on SoC FPGA;dynamic time slice scheduler for virtual machine monitor;memory-aware NoC application mapping based on adaptive genetic algorithm;a study on non-volatile 3D stacked memory for big data applications;parallel implementation of dense optical flow computation on many-core processor;a power-conserving online scheduling scheme for video streaming services;prevent deadlock and remove blocking for self-timed systems;improving the memory efficiency of in-memory mapreduce based HPC systems;dual best-first search mapping algorithm for shared-cache multicore processors;energy efficient network-on-chip router with heterogeneous virtual channels;availability and network-aware mapreduce task scheduling over the internet;an optimized algorithm based on CRS codes in big data storage systems;quantum computer simulation on multi-GPU incorporating data locality;query execution optimization based on incremental update in database distributed middleware;coding-based cooperative caching in data broadcast environments;usage history-directed power management for smartphones;a mobile application distribution method and a clustering algorithm based on rough sets for the recommendation domain in trust-based access control.

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FAST: A Fog Computing Assisted distributed Analytics System to Monitor Fall for Stroke Mitigation 10

FAST: A Fog Computing Assisted Distributed Analytics System ...

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IEEE international conference on Networking, Architecture and Storage (NAS 2015)

作者： Cao, Yu Chen, Songqing Hou, Peng Brown, Donald Univ Massachusetts Dept Comp Sci Lowell MA 01854 USA George Mason Univ Dept Comp Sci Fairfax VA 22030 USA

ISBN: (纸本)9781467378918

Fog computing is a recently proposed computing paradigm that extends Cloud computing and services to the edge of the network. The new features offered by fog computing (e.g., distributed analytics and edge intelligence), if successfully applied for pervasive health monitoring applications, has great potential to accelerate the discovery of early predictors and novel biomarkers to support smart care decision making in a connected health scenarios. While promising, how to design and develop real-word fog computing-based pervasive health monitoring system is still an open question. As a first step to answer this question, in this paper, we employ pervasive fall detection for stroke mitigation as a case in study. There are four major contributions in this paper: (1) to investigate and develop a set of new fall detection algorithms, including new fall detection algorithms based on acceleration magnitude values and non-linear time series analysis techniques, as well as new filtering techniques to facilitate fall detection process;(2) to design and employ a real-time fall detection system employing fog computing paradigm, which distribute the analytics throughout the network by splitting the detection task between the edge devices (e.g., smartphones attached to the user) and the server (e.g., servers in the cloud);(3) we carefully exam the special needs and constraints of stroke patients and propose patient-centered design that is minimal intrusive to patients. This type of patient-centered design is currently lacking in most of the existing work;and (4) our experiments with real-word data show that our proposed system achieves the high sensitivity (low missing rate) while it also achieves the high specificity (low false alarm rate). At the same time, the response time and energy consumption of our system are close to the minimum of the existing approaches.

关键词： Accelerometers Brain models Detection algorithms Monitoring Sensors Smart phones

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