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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Wang, Nao Wang, Gaocai Xie, Tianxiao Wu, Hongjia Guangxi Univ Sch Comp & Elect Informat Nanning Guangxi Peoples R China Guangxi Univ Guangxi Coll Nanning Guangxi Peoples R China Guangxi Univ Univ Key Lab Parallel & Distributed Comp Technol Nanning Guangxi Peoples R China

ISBN: (纸本)9781538637906

the limited battery lifetime of a wireless device, which is directly related to the better experience of the wireless network's users, imposes a constraint on network performance. thus, one of the most significant objectives in wireless networks is to reduce energy consumption of wireless terminals. Considering that the communication is much more energy efficient when the channel conditions are good, we design and propose an energy consumption optimization strategy for data transmission based on optimal stopping theory, with a view of minimizing the energy consumption of a wireless device and prolonging its battery lifetime. Wireless terminals periodically detect the channel to find the moment when the channel state is the best to transmit data under a given transmission delay demand in wireless links. However, the increasing number of channel detection causes the delay of transmitting data, so we introduce a discount function to convert this problem into a discounted secretary problem and finally find out the optimal stopping rule. Simulation results show that the proposed strategy offers significant average energy efficiency of unit data and is quite promising for the research on the energy efficiency of wireless networks.

关键词： channel awareness optimal stopping theory discounted secretary problem energy consumption optimization

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A Reconfigurable High Performance ASIP Engine for Image Signal processing

A Reconfigurable High Performance ASIP Engine for Image Sign...

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26th ieee international parallel and distributed processing symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Liao, Hsuanchun Asri, Mochamad Isshiki, Tsuyoshi Li, Dongju Kunieda, Hiroaki Tokyo Inst Technol Dept Commun & Integrated Syst Tokyo 152 Japan

ISBN: (纸本)9780769546766

Emerging digital television applications and the conventional MPSoC architectures encounter drastically increasing performance and flexibility requirement. To display high quality of images on the display devices, several image processing has to be performed. However, these algorithms are nonstandard and change case by case. It is difficult to achieve real time processing by using general purpose processor or DSP. In this paper, we present a reconfigurable Application Specific Instruction-set Processor (ASIP) which can perform several image processing algorithms by using the same datapath. It can complete several 1D filtering processing within 8 cycle/pixel;performing 16 times higher performance compare to conventional RISC processor. the performance of this ASIP can achieve the requirement of FullHD(1920x1080) application.

关键词： ASIP Image processing

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Fault Modeling of Extreme Scale applications using Machine Learning 30

Fault Modeling of Extreme Scale Applications using Machine L...

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30th ieee international parallel and distributed processing symposium (IPDPS)

作者： Vishnu, Abhinav van Dam, Hubertus Tallent, Nathan R. Kerbyson, Darren J. Hoisie, Adolfy Pacific Northwest Natl Lab Richland WA 99352 USA Brookhaven Natl Lab Upton NY 11973 USA

ISBN: (纸本)9781509021406

Faults are commonplace in large scale systems. these systems experience a variety of faults such as transient, permanent and intermittent. Multi-bit faults are typically not corrected by the hardware resulting in an error. this paper attempts to answer an important question: Given a multi-bit fault in main memory, will it result in an application error and hence a recovery algorithm should be invoked - or can it be safely ignored? We propose an application fault modeling methodology to answer this question. Given a fault signature (a set of attributes comprising of system and application state), we use machine learning to create a model which predicts whether a multi-bit permanent/transient main memory fault will likely result in error. We present the design elements such as the fault injection methodology for covering important data structures, the application and system attributes which should be used for learning the model, the supervised learning algorithms (and potentially ensembles), and important metrics. We use three applications - NWChem, LULESH and SVM - as examples for demonstrating the effectiveness of the proposed fault modeling methodology.

关键词： applications Exascale Fault Machine Learning Modeling

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Near-optimal all-to-all broadcast in multidimensional all-port meshes and tori

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ieee TRANSACTIONS ON parallel AND distributed SYSTEMS 2002年第2期13卷 128-141页

作者： Yang, YY Wang, JC SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA DataTreasury Corp Melville NY 11747 USA

All-to-all communication is one of the most dense collective communication patterns and occurs in many important applications in parallel and distributed computing. In this paper, we present a new all-to-all broadcast algorithm in multidimensional all-port mesh and torus networks. We propose a broadcast pattern which ensures a balanced traffic load in all dimensions in the network so that the all-to-all broadcast algorithm can achieve a very tight near-optimal transmission time. the algorithm also takes advantage of overlapping of message switching time and transmission time, and the total communication delay asymptotically matches the lower bound of all-to-all broadcast. Finally, the algorithm is conceptually simple and symmetrical for every message and every node so that it can be easily implemented in hardware and achieves the near-optimum in practice.

关键词： parallel computing collective communication all-to-all communication all-to-all broadcast gossip broadcast tree routing interprocessor communication mesh torus

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An Optimization and Auto-tuning Method for Scale-free Graph Algorithms on SIMD Architectures 15

An Optimization and Auto-tuning Method for Scale-free Graph ...

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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Lin, Jie Tan, Yusong Wu, Qingbo Li, Xiaoling Yu, Jie Zhang, Qi Natl Univ Def Technol Coll Comp Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

the advent of heterogeneous HPC systems, such as the Intel Xeon Phi with many integrated cores and wide SIMD lanes, has been widely used by researchers to accelerate scale-free graph algorithms. However, existing methods are not efficiently considering both the grouping strategy and the selection of the optimizing size for tiling the graph, which would decrease the efficiency of the graph computation. In this paper, we propose a novel Optimization and Auto-Tuning Method on SIMD architecture for scale-free graph algorithms, which is comprised of two sections. Firstly, in the Bucket Grouping Approach, an algorithm-based optimization has been employed to transform the scale-free graph data to conflict-free groups, which can decrease the preprocessing time and improve the SIMD efficiency of scale-free graph applications. Secondly, as optimal tile sizes are changing for different applications of different input graphs, an Auto-Tuning Strategy to optimize tile size achieves effective execution of graph computations. Two typical scale-free graph algorithms, Bellman-Ford and PageRank, are selected to evaluate the performance of OATM. According to the experiment results, OATM performs much better than existing methods, obtaining an average speedup of 1.1x, on these two applications both, by using OATM, comparing to the state-of-the-art methods.

关键词： Bucket grouping Auto-tuning Scale-free graph SIMD architecture

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Tweeting from Left to Right: Tracing the Dynamics of Emotional Messaging and Public Engagement During the 2018 vs. 2022 US Campaigns 21

Tweeting from Left to Right: Tracing the Dynamics of Emotion...

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21st ieee international symposium on parallel and distributed processing with applications, 13th ieee international Conference on Big Data and Cloud Computing, 16th ieee international Conference on Social Computing and Networking and 13th international Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Wang, Meng-Jie University of Canterbury School of Psychology Speech and Hearing Christchurch New Zealand

ISBN: (纸本)9798350329223

Despite numerous studies delving into social media politicking, there is, thus far, little understanding of how distinct emotions spread online. Much of the prior work has focused on positive vs. negative diffusion or measured emotional rhetoric without considering public engagement on such sites. Since elected officials increasingly turn to social media, even less is known about the impact of distinct emotional messaging on mobilizing users, attracting supporters, or disseminating political speeches. Moving beyond merely a valence-based approach, the study here seeks to address this gap by analyzing over 23,000 tweets posted by Senate candidates during the 2018 and 2022 US midterm elections through natural language processing. Specifically, leveraging the IBM Tone Analyzer, the present work implements a cross-sectional examination to explore: a) whether certain emotions - joy, confidence, anger, fear, and sadness - conveyed in candidates' tweets might be more likely to garner public attention;and b) if so, does this pattern vary across the political spectrum, illuminating the ways in which Democratic vs. Republican candidates adopt to expand their online reach over time? © 2023 ieee.

关键词： Natural language processing systems

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TwigMRR: distributed XML twig query processing 13

TwigMRR: distributed XML twig query processing

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13th international symposium on distributed Computing and applications to Business, Engineering and Science (DCABES)

作者： He, Zhixue Liao, Husheng Su, Hang Beijing Univ Technol Beijing Peoples R China North China Inst Aerosp Engn Langfang Langfang Peoples R China

ISBN: (纸本)9781479941698

Twig query is considered the core query pattern in most XML query language. With the XML document size becoming larger, single site cannot deal with such volume data in storage capacity and compute ability. Partitioning the large data and distributed parallel processing query is an efficient and effective way. this paper proposes TwigMRR algorithm for evaluating XML twig query over large XML data that is encoded by Dewey, partitioned horizontally and distributed storage in a cluster. TwigMRR is based on MapReduce and extended a new model Map-Reduce-Reduce to get the final results for twig query. the experimental results show that our approach is scalable and efficient on this problem.

关键词： partitioned XML document twig queries distribute query processing

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Balanced Coloring for parallel Computing applications 29

Balanced Coloring for Parallel Computing Applications

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29th ieee international parallel and distributed processing symposium (IPDPS)

作者： Lu, Hao Halappanavar, Mahantesh Chavarria-Miranda, Daniel Gebremedhin, Assefaw Kalyanaraman, Ananth Washington State Univ Pullman WA 99164 USA Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9781479986484

Graph coloring is used to identify subsets of independent tasks in parallel scientific computing applications. Traditional coloring heuristics aim to reduce the number of colors used as that number also corresponds to the number of parallel steps in the application. However, if the color classes produced have a skew in their sizes, utilization of hardware resources becomes inefficient, especially for the smaller color classes. Equitable coloring is a theoretical formulation of coloring that guarantees a perfect balance among color classes, and its practical relaxation is referred to as balanced coloring. In this paper, we revisit the problem of balanced coloring in the context of parallel computing. the goal is to achieve a balanced coloring of an input graph without increasing the number of colors that an algorithm oblivious to balance would have used. We propose and study multiple heuristics that aim to achieve such a balanced coloring, present parallelization approaches for multi-core and manycore architectures, and cross-evaluate their effectiveness with respect to the quality of balance achieved and performance. Furthermore, we study the impact of the proposed balanced coloring heuristics on a concrete application - viz. parallel community detection, which is an example of an irregular application. the thorough treatment of balanced coloring presented in this paper from algorithms to application is expected to serve as a valuable resource to parallel application developers who seek to improve parallel performance of their applications using coloring.

关键词： Balanced coloring Tilera manycore architecture community detection graph algorithms

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PCGraph: Accelerating GNN Inference on Large Graphs via Partition Caching 19

PCGraph: Accelerating GNN Inference on Large Graphs via Part...

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19th ieee international symposium on parallel and distributed processing with applications (ieee ISPA)

作者： Zhang, Lizhi Lai, Zhiquan Tang, Yu Li, Dongsheng Liu, Feng Luo, Xiaochun Natl Univ Def Technol Comp Coll Natl Lab Parallel & Distributed Proc PDL Changsha Hunan Peoples R China PLA News Media Ctr Beijing Peoples R China

ISBN: (纸本)9781665435741

Graph neural networks (GNNs) have been emerging as powerful learning tools for unstructured data and successfully applied to many graph-based application domains. Sampling-based GNN inference is commonly adopted in existing graph learning frameworks to handle large-scale graphs. However, this approach is restricted by the problems of redundant vertex embedding computation in GPU and inefficient loading of vertex features from CPU to GPU. In this paper, we propose PC-Graph, a system that supports adaptive GNN inference and feature partition caching. PCGraph significantly reduces the vertex embedding computation time by adaptive GNN inference technology, which selects the optimal inference algorithm and minimizes vertex embedding computation. PCGraph also reduces the redundant data transfer between the CPU and GPU by partition the target vertices and caching their corresponding partitions in turn. We evaluate PCGraph against two state-of-the-art industrial GNN frameworks, i.e., PyG and DGL, on a diverse array of benchmarks. Experimental results show that PCGraph reduces up to 99% vertex embedding computation and 98.5% data loading time, and achieves up to 360x performance speedup over the state-of-the-art baselines.

关键词： graph neural networks inference embedding computation feature caching pipeline parallel

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Beam-tracing domain decomposition method for urban acoustic pollution 13

Beam-tracing domain decomposition method for urban acoustic ...

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13th international symposium on distributed Computing and applications to Business, Engineering and Science (DCABES)

作者： Gbikpi-Benissan, Guillaume Magoules, Frederic Ecole Cent Paris Chatenay Malabry France

ISBN: (纸本)9781479941698

this paper covers the fast solution of large acoustic problems on low-resources parallel platforms. A domain decomposition method is coupled with a dynamic load balancing scheme to efficiently accelerate a geometrical acoustic method. the geometrical method studied implements a beam-tracing method where intersections are handled as in a ray-tracing method. Beyond the distribution of the global processing upon multiple sub-domains, a second parallelization level is operated by means of multi-threading and shared memory mechanisms. Numerical experiments show that this method allows to handle large scale open domains for parallel computing purposes on few machines. Urban acoustic pollution arrising from car traffic was simulated on a large model of the Shinjuku district of Tokyo, Japan. the good speed-up results illustrate the performance of this new domain decomposition method.

关键词： Domain decomposition methods parallel and distributed computing Acoustics Ray-tracing methods Beam-tracing methods

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