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2014 ACM SIGPLAN conference on Systems, Programming, and applications: Software for Humanity, SPLASH 2014

作者： Jannesari, Ali Wolf, Felix Tichy, Walter F. German Research School for Simulation Sciences RWTH Aachen University Germany Germany

ISBN: (纸本)9781450332088

The first international workshop on Software Engineering for parallel Systems (SEPS) will be held in Portland, Oregon, USA on October 21, 2014 and co-located with the ACM SIGPLAN conference on Systems, Programming, Languages and applications: Software for Humanity (SPLASH 2014). The purpose of this workshop is to provide a stable forum for researchers and practitioners dealing with compelling challenges of the software development life cycle on modern parallel platforms. The increased complexity of parallel applications on modern parallel platforms (e.g. multicore, manycore, distributed or hybrid) requires more insight into development processes, and necessitates the use of advanced methods and techniques supporting developers in creating parallel applications or parallelizing and reengineering sequential legacy applications. We aim to advance the state of the art in different phases of parallel software development, covering software engineering aspects such as requirements engineering and software specification;design and implementation;program analysis, profiling and tuning;testing and debugging. Copyright is held by the owner/author(s).

关键词： parallel programming

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Comparison of parallel Discrete Fourier Transform Implementations for Modelling of Optical Communication Systems 12

Comparison of Parallel Discrete Fourier Transform Implementa...

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12th IEEE international conference on Emerging eLearning Technologies and applications (ICETA)

作者： Grondzak, K. Kortis, P. Univ Zilina Fac Management Sci & Informat Dept Informat Zilina Slovakia Univ Zilina Fac Elect Engn Dept Telecommun & Multimedia Zilina Slovakia

ISBN: (纸本)9781479977406

Discrete Fourier Transform (DFT) is a well-known mathematical tool used for scientific and engineering purposes. One of the areas, where DFT is frequently used is digital signal processing (DSP). The application of DSP techniques is used in many diverse areas, from telecommunication sector through medical data processing up to modern home entertainment systems. Many of the DSP applications require real time data processing. In the scientific area the DFT is frequently used for modelling of electrical circuits, communication systems and other areas, where the direct (from time domain to frequency domain) and inverse transformations are performed. This contribution presents two available libraries to accelerate DFT using parallelization. Presented libraries are implemented for use on recent computer processors (Central processing Unit, CPU), as well as for the calculation of the graphics cards (Graphic processing Unit, GPU). We briefly introduce the libraries and then present the comparison of their performance.

关键词： discrete Fourier transform Modeling Digital signal processing telecommunications sector COMMUNICATION SYSTEMS Libraries OPTICAL COMMUNICATION SYSTEMS Desmoplakin Gene graphic images central processing units Optical communication TIME-DOMAIN Frequency-domain analysis PROCESSOR

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Priority-based Resource Scheduling in distributed Stream processing Systems for Big Data applications 14

Priority-based Resource Scheduling in Distributed Stream Pro...

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IEEE/ACM 7th international conference on Utility and Cloud Computing (UCC)

作者： Bellavista, Paolo Corradi, Antonio Reale, Andrea Ticca, Nicola Univ Bologna Dept Comp Sci & Engn Bologna Italy

ISBN: (纸本)9781479978816

distributed Stream processing Systems (DSPSs) are attracting increasing industrial and academic interest as flexible tools to implement scalable and cost-effective on-line analytics applications over Big Data streams. Often hosted in private/public cloud deployment environments, DSPSs offer datastream processing services that transparently exploit the distributed computing resources made available to them at runtime. Given the volume of data of interest, possible (hard/soft) real-time processing requirements, and the time-variable characteristics of input datastreams, it is very important for DSPSs to use smart and innovative scheduling techniques that allocate computing resources properly and avoid static over-provisioning. In this paper, we originally investigate the suitability of exploiting application-level indications about differentiated priorities of different stream processing tasks to enable application-specific DSPS resource scheduling, e.g., capable of re-shaping processing resources in order to dynamically follow input data peaks of prioritized tasks, with no static over-provisioning. We originally propose a general and simple technique to design and implement priority-based resource scheduling in flow-graph-based DSPSs, by allowing application developers to augment DSPS graphs with priority metadata and by introducing an extensible set of priority schemas to be automatically handled by the extended DSPS. In addition, we show the effectiveness of our approach via its implementation and integration in our Quasit DSPS and through experimental evaluation of this prototype on a real-world stream processing application of Big Data vehicular traffic analysis.

关键词： distributed Stream processing Big Data Priority-based Resource Scheduling Application-level and Application-specific Scheduling Cloud Computing Optimization Vehicular Traffic Analysis

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Predicting Cache Contention for Multithread applications at Compile Time 28

Predicting Cache Contention for Multithread Applications at ...

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28th IEEE international parallel & distributed processing Symposium Workshops (IPDPSW)

作者： Tolubaeva, Munara Yan, Yonghong Chapman, Barbara Univ Houston Dept Comp Sci Houston TX 77004 USA

ISBN: (纸本)9781479941162

Shared cache in multicore processors is an important hardware resource that should be utilized effectively to achieve high performance for parallel applications. It is critical to coordinate accesses by multiple threads to data that reside in shared cache to reduce cache contentions, and to improve cache hit rates of both shared and private data of threads. Poorly scheduled threads with regards to their memory access patterns can cause severe cache interference among each other, thus increasing the number of cache misses greatly and causing overall application performance degradation. To evaluate the cache contention behavior of multithread applications, we propose a new method to predict number of cache misses that would happen due to cache sharing and/ or contention at compile time. The method utilizes compiler analysis techniques to generate memory access traces for each thread under no cache sharing. Then a small number of combinations of threads' memory access traces are randomly selected among all combinations as an input to predict cache misses of the threads using the proposed method. We have shown that our method can predict the number of cache misses very fast without losing accuracy. Our approach is very generic and can predict cache contention and/or sharing impact of parallel applications on both homogeneous and heterogeneous systems. We evaluated the method with a simulation case study and two scientific benchmarks. The results showed that our method can accurately predict the impact of cache contention and sharing at compile time.

关键词： Shared cache cache contention performance model and prediction compiler analysis

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Exploiting computing power of Xeon and Intel Xeon Phi for a Molecular Dynamics Application 15

Exploiting computing power of Xeon and Intel Xeon Phi for a ...

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Simulation Multiconference

作者： Benny Mathew Nitin Rai Apaar Gupta Amit Harode Tata Consultancy Services

ISBN: (纸本)9781510801011

Molecular Dynamics (MD) is a computational technique with applicability in fields as diverse as material science, biomolecules and chemical physics. Assisted Model Building with Energy Refinement (AMBER) is an MD package and it uses Message Passing Interface (MPI) to scale in multi-core and cluster environments. In our earlier work [1], we modified one of AMBER's algorithms called Generalized Born (GB) algorithm to run optimally on the Xeon Phi co-processor. This improved performance by 277% on the co-processor. The same changes improved performance on the host server by 80%. In this paper, we extend our earlier work and implement a symmetric solution using both the host server and the co-processor. Since the calculations in GB algorithm involve interactions between all possible atom combinations, it has been very difficult to scale GB algorithm in distributed memory. We evaluate various alternate techniques using combination of MPI and Open Multi-processing (OpenMP) to get a scalable solution that utilizes the computing power of both the host server as well as the co-processor.

关键词： Molecular dynamics AMBER HPC Performance Intel Xeon Phi Nucleosome Generalized Born parallel programming OpenMP MPI message passing amber Coprocessors mannose phosphate isomerase remote procedure calls parallel programming Molecular Dynamics Nucleosomes High Performance Computing computational power

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Increasing the efficiency of using hardware resources for time-frequency correlation function computation

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Advanced Materials Research 2014年 1040卷 969-974页

作者： Avramchuka, Valeriy V. Luneva, Elena E. Cheremnov, Alexander G. National Research Tomsk Polytechnic University 30 Lenin Avenue Tomsk Russia

ISBN: (纸本)9783038352648

In the article the techniques of increasing efficient of using multi-core processors for the task of calculating the fast Fourier transform were considered. The fast Fourier transform is led on the basis of calculating a time time-frequency correlation function. The time-frequency correlation function allows increasing the information content of the analysis as compared with the classic correlation function. The significant computational capabilities are required to calculate the time-frequency correlation function, that by reason of the necessity of multiple computing fast Fourier transform. For algorithm of calculating the time-frequency correlation function parallel computing technique was used that experimentally allowed obtaining the data defining the optimal number of iterations for each core of the CPU, depending on the sample size. The results of experiments allowed developing special software that automatically select the effective amount of subtasks for parallel processing as well as provides the choice of sequential or parallel computations mode. © (2014) Trans Tech Publications, Switzerland.

关键词： Digital signal processing

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UNBIASED NOISE ESTIMATION AND DENOISING IN parallel MAGNETIC RESONANCE IMAGING

UNBIASED NOISE ESTIMATION AND DENOISING IN PARALLEL MAGNETIC...

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

作者： Borrelli, Pasquale Palma, Giuseppe Comerci, Marco Alfano, Bruno Univ Naples Federico II Dept Adv Biomed Sci Via Pansini 5 I-80131 Naples Italy Natl Res Council Italy Inst Biostruct & Bioimaging I-80145 Naples Italy

ISBN: (纸本)9781479928934

In magnetic resonance (MR) clinical practice, noise estimation is usually performed on Rayleigh-distributed background (no signal area) of magnitude images. Although noise variance in quadrature MR images is considered spatially independent, parallel MRI (pMRI) techniques as SENSE or GRAPPA generate spatially varying noise (SVN) distribution. In this scenario noise estimation from background may produce biased results. To address these limitations we introduce a novel noise estimation scheme based on local statistics. Our method turns out to be more accurate than the other pMRI noise estimation schemes previously described in the literature. Denoising performances, measured by visual inspection and peak signal-to-noise ratio (PSNR), of Non-Local Means denoising filters (NLM) are considerably improved using SVN-NLM in case of inhomogeneous noise. Furthermore, SVN-NLM behaves as well as standard NLM when homogeneous noise was added, thus proving to be a robust and powerful denoising algorithm for arbitrary MRI datasets.

关键词： Noise estimation denoising parallel MRI non-local means Rician noise

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Fast parallel Algorithms for Edge-Switching to Achieve a Target Visit Rate in Heterogeneous Graphs 43

Fast Parallel Algorithms for Edge-Switching to Achieve a Tar...

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43rd Annual international conference on parallel processing (ICPP)

作者： Bhuiyan, Hasanuzzaman Chen, Jiangzhuo Khan, Maleq Marathe, Madhav V. Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Virginia Tech Virginia Bioinformat Inst Network Dynam & Simulat Sci Lab Blacksburg VA 24061 USA

ISBN: (纸本)9781479956180

An edge switch is an operation on a network (graph) where two edges are selected randomly and one of their end vertices are swapped with each other. Usually, a sequence of these operations are performed to generate network perturbations having the same degree sequence of the original network. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks (e.g., peer-to-peer networks), studying various dynamic phenomena over a network (e.g., disease dynamics over a social contact network). The growth of real-world networks motivates the need to develop efficient parallel algorithms for performing a large sequence of edge switch operations. The dependencies among successive edge switch operations and the requirement of keeping the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors. In this paper, we present a distributed memory parallel algorithm for switching edges in massive networks (networks with billions of edges) and achieve a speedup factor of 85 with 1024 processors. One of the steps in our edge switch algorithm requires the computation of multinomial random variables in parallel. The paper presents the first non-trivial parallel algorithm for the problem. The algorithm achieves a speedup of 925 using 1024 processors.

关键词： edge switch massive networks multinomial distribution parallel algorithms

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Detecting a Large Number of Objects in Real-time Using Apache Storm 5

Detecting a Large Number of Objects in Real-time Using Apach...

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5th international conference on Information and Communication Technology Convergence (ICTC)

作者： Im, Dong-Hyuck Cho, Cheol-Hye Jung, IlGu ETRI Broadcasting & Telecommun Media Res Lab Daejeon South Korea

ISBN: (纸本)9781479967865

Object detection is an important function for intelligent multimedia processing, but its computational complexity prevented its pervasive uses in consumer electronics. To process large-scale datasets in real-time, more resources and reliable infrastructures are required for spreading the data and running the applications across multiple machines in parallel. In order to detect a large number of objects in real-time, a task-parallel processing framework based on Storm is proposed.

关键词： object detection parallel computing distributed computing Storm

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SEU-TOLERANT RESTRICTED BOLTZMANN MACHINE LEARNING ON DSP-BASED FAULT DETECTION 12

SEU-TOLERANT RESTRICTED BOLTZMANN MACHINE LEARNING ON DSP-BA...

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12th IEEE international conference on Signal processing (ICSP)

作者： Jian SongLei Jiang JingFei Lu Kai Zhang YanPing Natl Univ Def Technol Sci & Technol Parallel & Distributed Proc Lab Changsha Hunan Peoples R China

ISBN: (纸本)9781479921867

Restricted Boltzmann Machine (RBM) is the main building block of many deep learning models which are now becoming one of the most important kind of algorithms in machine leaning community. With the growing demand for information processing in aerospace computer, RBM can be used as a promising block supporting intelligent applications such as space self-control, intelligent recognition, and target classification. As for aerospace computer, a common challenge is the Single Event Upset (SEU) effect, which would change the state of some information bits stochastically and lead to error results. Due to the time-consuming and data-intensive computation of aerospace computer, digital signal processing (DSP) is the most suitable for aerospace computation. In this paper, we first implement representative RBM learning algorithm in a power efficient DSP platform. Then, we explore the possible SEU effects in our hardware architecture and RBM learning algorithm. Further, we integrate three software fault detection techniques (i.e. duplication, increasing data diversity, shortening life cycle of variable) into RBM learning. In the experiment, we utilize the simulated fault injection technique to evaluate fault detective RBM learning. The evaluation shows that our fault detection designs effectively detect SEU-induced error during RBM learning in DSP with low computational complexity.

关键词： RBM SEU software fault detection DSP

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