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Fast GPU parallel N-Body tree traversal with Simulated Wide-Warp 20

Fast GPU parallel N-Body tree traversal with Simulated Wide-...

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20th IEEE international conference on parallel and distributed Systems, ICPADS 2014

作者： Zola, Wagner M. Nunan Bona, Luis C.E. Silva, Fabiano Federal University of Paraná Curitiba PR Brazil

ISBN: (纸本)9781479976157

The Barnes-Hut algorithm is a widely used approximation method for the N-Body simulation problem. The irregular nature of this tree walking code presents interesting challenges for its computation on parallel systems. Additional problems arise in effectively exploiting the processing capacity of GPU architectures. We propose and investigate the applicability of software Simulated Wide-Warps (SWW) in this context. To this extent, we explicitly deal with dynamic irregular patterns in data accesses with data remapping and data transformation, by controlling execution flow divergence of threads. We present a new compact data-structure for the tree layout, GPU parallel algorithms for tree transformation and parallel walking using SWW. Benefits of our techniques are in transposing the tree algorithm to execute regular patterns to match the GPU model. Our experiments show significant performance improvement over the best known GPU solutions to this algorithm. © 2014 IEEE.

关键词： parallel algorithms

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KERNEL METHODS MATCH DEEP NEURAL NETWORKS ON TIMIT

KERNEL METHODS MATCH DEEP NEURAL NETWORKS ON TIMIT

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IEEE international conference on Acoustics, Speech and Signal processing (ICASSP)

作者： Huang, Po-Sen Avron, Haim Sainath, Tara N. Sindhwani, Vikas Ramabhadran, Bhuvana Univ Illinois Dept Elect & Comp Engn 1406 W Green St Urbana IL 61801 USA IBM Corp T J Watson Res Ctr Yorktown Hts NY USA

ISBN: (纸本)9781479928934

Despite their theoretical appeal and grounding in tractable convex optimization techniques, kernel methods are often not the first choice for large-scale speech applications due to their significant memory requirements and computational expense. In recent years, randomized approximate feature maps have emerged as an elegant mechanism to scale-up kernel methods. Still, in practice, a large number of random features is required to obtain acceptable accuracy in predictive tasks. In this paper, we develop two algorithmic schemes to address this computational bottleneck in the context of kernel ridge regression. The first scheme is a specialized distributed block coordinate descent procedure that avoids the explicit materialization of the feature space data matrix, while the second scheme gains efficiency by combining multiple weak random feature models in an ensemble learning framework. We demonstrate that these schemes enable kernel methods to match the performance of state of the art Deep Neural Networks on TIMIT for speech recognition and classification tasks. In particular, we obtain the best classification error rates reported on TIMIT using kernel methods.

关键词： large-scale kernel machines random features distributed computing deep learning speech recognition

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Data Allocation techniques for Mobile Sensor Networks

Data Allocation Techniques for Mobile Sensor Networks

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28th IEEE international conference on Advanced Information Networking and applications Workshops (IEEE WAINA)

作者： Hara, Takahiro Nishio, Shojiro Osaka Univ Grad Sch Info Sci & Tech Dept Multimedia Engn Suita Osaka Japan

ISBN: (纸本)9781479926527

In mobile sensor networks (MSNs), since sensor nodes and wireless networks are highly resource constrained, it is required to manage sensor data in flexible and efficient manners. Under the MEXT research project(1) entitled "Studies on Efficient Data processing techniques for Mobile Sensor Networks," we have conducted researches on data management issues in MSNs. In this paper, we report some of our achievements in a sub-area of this project, which addresses data allocation for efficient query processing in MSNs. In particular, we first show our achievements on how to effectively allocate sensor data on mobile nodes and how to efficiently process top-k and k-nearest neighbor queries on the allocated data. Then, we also show our achievements on how to quantify the impacts of mobility on data availability and data dissemination in MSNs.

关键词： mobile sensor networks data allocation top-k query k-nearest neighbor query data replication

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Optimizing Pipelined Execution for distributed In-Memory OLAP System

Optimizing Pipelined Execution for Distributed In-Memory OLA...

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19th international conference on Database Systems for Advanced applications (DASFAA)

作者： Wang, Li Zhang, Lei Yu, Chengcheng Zhou, Aoying E China Normal Univ Inst Software Engn Shanghai 200062 Peoples R China

ISBN: (纸本)9783662439845;9783662439838

In the coming big data era, the demand for data analysis capability in real applications is growing at amazing pace. The memory's increasing capacity and decreasing price make it possible and attractive for the distributed OLAP system to load all the data into memory and thus significantly improve the data processing performance. In this paper, we model the performance of pipelined execution in distributed in-memory OLAP system and figure out that the data communication among the computation nodes, which is achieved by data exchange operator, is the performance bottleneck. Consequently, we explore the pipelined data exchange in depth and give a novel solution that is efficient, scalable, and skew-resilient. Experimental results show the effectiveness of our proposals by comparing with state-of-art techniques.

关键词： Electronic data interchange

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Modified MapReduce Framework for Enhancing Performance of Graph Based Algorithms by Fast Convergence in distributed Environment 3

Modified MapReduce Framework for Enhancing Performance of Gr...

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3rd international conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Singhal, Hitesh Guddeti, Ram Mohana Reddy Natl Inst Technol Kamataka Dept Informat Technol Mangalore India

ISBN: (纸本)9781479930807

The amount of data which is produced is huge in current world and more importantly it is increasing exponentially. Traditional data storage and processing techniques are ineffective in handling such huge data [10]. Many real life applications require iterative computations in general and in particular used in most of machine learning and data mining algorithms over large datasets, such as web link structures and social network graphs. MapReduce is a software framework for easily writing applications which process large amount of data (multi-terabyte) in parallel on large clusters (thousands of nodes) of commodity hardware. However, because of batch oriented processing of MapReduce we are unable to utilize the benefits of MapReduce in iterative computations. Our proposed work is mainly focused on optimizing three factors resulting in performance improvement of iterative algorithms in MapReduce environment. In this paper, we address the key issues based on execution of tasks, the unnecessary creation of new task in each iteration and excessive shuffling of data in each iteration. Our preliminary experiments have shown promising results over the basic MapReduce framework. The comparative study with existing solutions based on MapReduce framework like HaLoop, has also shown better performance w.r.t algorithm run time and amount of data traffic over Hadoop Cluster.

关键词： MapReduce Graph algorithms Iterative Computations

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Comparison of performance of threads and forks parallel programming techniques and application in image processing 41

Comparison of performance of threads and forks parallel prog...

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41st EPS conference on Plasma Physics, EPS 2014

作者： Moraes, Femanda D. Gioani, M. Ahes, N. De Albuquerque, Marcelo Portes De Albuquerque, Márcio P. Centro Brasileiro de Peaquisas Fíaicaa - CBPF Rua De Xavier Sigaud 150 Urca Rio de Janeiro - RJ Brazil

Several algorithms applied to the solution of specific problems in ph sics require high performance computing. This is the case, for exanjple, in the field of digital image processing, where the required performance in terms of speed, and sometimes running an a real time environment, leads to the use of parallel programrmng tools. To meet this demand it is important to understand these tools, highlighting differences and their possible applications. Moreover, research centers around the world has available a clusters of computer, or a multi-core platform. with a strong potential of using parallel programming techniques. Ibis study aims to charaetertre threads and forks parallel programming techniques. Both techniques allow the develcpnient of parallel codes, which with its own restrictions on the inter process comniunication and programming format. This Technical Note aims to highlight the use of each of these techniques, and to present an agplication in the area of image processing in which they were used. The application part of this work was develctped in the international collaboration with the JET Laboratory (Join European Torus of the European Atomic Energy Community I EURATOM). The TET Laboratory investigates the process of forming the plasma and its nstability, which appears as a toroidal ring of increased radiation, known as MARFE (Multifaceted Asymmetric Radiation From The Edge). The activities have explored the techniques of parallel programming algorithms in digital image processing. The presented algorithms allow achieving a processing rate higher than 10 000 images per second and use threads and shared memory communication between independent processes, which is equivalent to fork.

关键词： parallel programming

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Scalable and Efficient parallel Selection

Scalable and Efficient Parallel Selection

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Siebert, Christian Rhein Westfal TH Aachen Dept Comp Sci Lab Parallel Programming Aachen Germany

ISBN: (纸本)9783642552243

Selection algorithms find the kth smallest element from a set of elements. Although there are optimal parallel selection algorithms available for theoretical machines, these algorithms are not only difficult to implement but also inefficient in practice. Consequently, scalable applications can only use few special cases such as minimum and maximum, where efficient implementations exist. To overcome such limitations, we propose a general parallel selection algorithm that scales even on today's largest supercomputers. Our approach is based on an efficient, unbiased median approximation method, recently introduced as median-of-3 reduction, and Hoare's sequential QuickSelect idea from 1961. The resulting algorithm scales with a time complexity of O(log(2) n) for n distributed elements while needing only O(1) space. Furthermore, we prove it to be a practical solution by explaining implementation details and showing performance results for up to 458, 752 processor cores.

关键词： Selection QuickSelect Median parallel algorithms MPI

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'NoSQL' and Electronic Patient Record Systems: Opportunities and Challenges 9

'NoSQL' and Electronic Patient Record Systems: Opportunities...

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NINTH international conference ON P2P, parallel, GRID, CLOUD AND INTERNET COMPUTING (3PGCIC)

作者： Moore, Philip Qassem, Tarik Xhafa, Fatos Lanzhou Univ Sch Informat Sci & Engn Lanzhou Peoples R China Univ Warwick Warwick Med Sch Coventry W Midlands England Tech Univ Catalonia Barcelona 08034 Spain

ISBN: (纸本)9781479941711

Research into electronic health record systems can be traced back over four decades however the penetration of records which incorporate more than simply basic information into healthcare organizations is relatively limited. There is a great (and largely unsatisfied) demand for effective health record systems;such systems are very difficult to build with data generally stored in highly distributed states in a diverse range of formats as unstructured data with access and updating achieved over online systems. Internet application design must reflect three trends in the computing landscape: (1) growing numbers of users applications must support (along with growing user performance expectations), (2) growth in the volume and range and diversity in the data that developers accommodate, and (3) and the rise of Cloud Computing (which relies on a distributed three-tier Internet architecture). The traditional approach to data storage has generally employed Relational Database Systems however to address the evolving paradigm interest has been shown in alternative database systems including NoSQL technologies which are gaining traction in Internet based enterprise systems. This paper considers the requirements of distributed health record systems in online applications and database systems. The analysis supports the conclusion that NoSQL database systems provide a potentially useful approach to the implementation of HR systems in online applications.

关键词： unstructured data database systems 'NoSQL' Electronic Patient Health Records online transaction processing

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ScalScheduling: A Scalable Scheduling Architecture for MPI-based Interactive Analysis Programs 23

ScalScheduling: A Scalable Scheduling Architecture for MPI-b...

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23rd international conference on Computer Communication and Networks (ICCCN)

作者： Yin, Jiangling Foran, Andrew Zhang, Xuhong Wang, Jun Univ Cent Florida EECS Orlando FL 32826 USA

ISBN: (纸本)9781479935727

In today's large scale clusters, running tasks with high degrees of parallelism allows interactive data visualization/analysis to complete in seconds. However, conventional, centralized scheduling poses significant challenges for these interactive applications. As the amount of data to be processed grows, it becomes too heavy to move across the network. Thus, data processing tasks should be scheduled such that the amount of transferred data is minimized, i.e., realizing data locality computation. To implement this, a scheduler process should collect and analyze data distribution metadata prior to making scheduling decisions, which usually causes milliseconds or seconds of latency. Such scheduling delay is unacceptable for interactive data applications. In this paper, we present a Scalable Scheduling Architecture for conventional interactive data programs and refer to it as ScalScheduling. ScalScheduling is proposed to reduce task scheduling latency, while ensuring the worker processes achieve a high degree of data locality computation and load balance in heterogeneous environments. In our proposed architecture, each worker process uses a novel Modulo-based priority method to schedule its local tasks independently. Multiple scheduler processes are employed according to the number of worker processes to resolve the issue of concurrent requests and assign remote tasks with respect to load balance. We perform experiments using thousands of parallel processes, and the experimental results show the benefits of our proposed scheduling architecture as well as its potential for future oversize task scheduling problems on largescale clusters.

关键词： Computer architecture Data processing distributed databases Process control Processor scheduling Schedules Scheduling distributed databases scheduling of multiprocessor Computer Architecture Process control Interactive Load balancing Automatic data processing data processing Building construction ARCHITECTURE

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VLSI Implementation of Efficient Split Radix FFT Based on distributed Arithmetic

VLSI Implementation of Efficient Split Radix FFT Based on Di...

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international conference on Green Computing Communication and Electrical Engineering (ICGCCEE)

作者： Laguri, Nisha Anusudha, K. Pondicherry Univ Dept Elect Engn Pondicherry India

ISBN: (纸本)9781479949816

Fast Fourier Transform (FFT) is a very common operation used for various signal processing units. Many efficient algorithms are being designed to improve the architecture of FFT. Among the different algorithms, split-radix FFT has shown considerable improvement in terms of reducing hardware complexity of the architecture compared to radix-2 and radix-4 FFT algorithm. The performance in terms of throughput of the processor is limited by the multiplication. Therefore multiplier is optimized to make the input to output delay as short as possible. distributed arithmetic (DA) is one of the most used techniques in implementing multiplier-less architectures of many digital systems. In this paper a Split Radix FFT without the use of multiplier is designed. All the complex multiplications are done by using distributed Arithmetic (DA) technique. For faster calculation parallel prefix adder is used. These algorithms reduces overall arithmetic operations in FFT, but increases the number of operations and complexity of each butterfly. In Split Radix FFT, mixed-radix approach helps to achieve low number of multiplications and additions. The advantage of DA is its efficiency of mechanization. A method is incorporated to overcome the overflow problem introduced by DA method.

关键词： Fast Fourier Transform (FFT) Split Radix DA parallel Prefix Adder

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