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Heterogeneous parallel and distributed Optimization of K-means Algorithm on Sunway Supercomputer 15

Heterogeneous Parallel and Distributed Optimization of K-mea...

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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： Chen, Jiawei Tan, Rong Zhang, Yiwen Washington Univ St Louis MO 63130 USA Cornell Univ Ithaca NY USA Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781538637906

Clustering plays an essential role in large-volume data analysis areas such as bioinformatics, statistic, pattern recognition and so on. K-means is one of most effective clustering algorithms, which is relatively easy to implement. Most real world applications usually involve a huge amount of data. Thus, how to improve applications' efficiency while maintaining accuracy becomes a significant and considerable issue. In this paper, a K-means clustering algorithm, which uses heterogeneous parallel computing technology on Computing processing elements and distributed computing technology, is proposed. This algorithm is applied in unique Sunway architecture based on "Sunway TaihuLight" Supercomputer-the world's fastest supercomputer with peak performance over 100PFLOPS. The testing results suggest that this improved algorithm is stable, fast and efficient. Conclusively, it has a great improvement in computation performance, especially with large volumes of data.

关键词： Clustering algorithms Computer architecture Computational modeling Program processors Supercomputers Big Data Data models

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Analyzing the Energy Efficiency of the Memory Subsystem in Multicore Processors 12

Analyzing the Energy Efficiency of the Memory Subsystem in M...

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12th IEEE international symposium on parallel and distributed processing with applications (ispa)

作者： Catalan, Sandra Gonzalez-Dominguez, Jorge Mayo, Rafael Quintana-Orti, Enrique S. Univ Jaume 1 Depto Ingn & Ciencia Comp Castellon de La Plana 12071 Spain Johannes Gutenberg Univ Mainz Parallel & Distributed Architectures Grp D-55122 Mainz Germany

ISBN: (纸本)9781479942930

In this paper we analyze the energy overhead incurred when operating with data stored in different levels of the memory subsystem (cache levels and DDR chips) of current multicore architectures. Our approach builds upon servet, a portable framework for the memory characterization of multicore processors, extending this suite with a power-related test that, when applied to a platform equipped with a power measurement mechanism, provides information on the efficiency of memory energy usage. As additional contributions, i) we provide a complete experimental study of the impact that the CPU performance states (also known as P-states) exert on the memory energy efficiency of a collection of recent server-oriented and low-power cores;and ii) we show how this framework carries over to cover also the scalability analysis of the memory energy performance on multicore processors.

关键词： Power efficiency high performance computing profiling and tracing power consumption multicore processors

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parallel Subgraph Counting for Multicore Architectures 12

Parallel Subgraph Counting for Multicore Architectures

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12th IEEE international symposium on parallel and distributed processing with applications (ispa)

作者： Aparicio, David Ribeiro, Pedro Silva, Fernando Univ Porto CRACS P-4169007 Oporto Portugal Univ Porto INESC TEC LA Fac Ciencias P-4169007 Oporto Portugal

ISBN: (纸本)9781479942930

Computing the frequency of small subgraphs on a large network is a computationally hard task. This is, however, an important graph mining primitive, with several applications, and here we present a novel multicore parallel algorithm for this task. At the core of our methodology lies a state-of-the-art data structure, the g-trie, which represents a collection of subgraphs and allows for a very efficient sequential search. Our implementation was done using Pthreads and can run on any multicore personal computer. We employ a diagonal work sharing strategy to dynamically and effectively divide work among threads during the execution. We assess the performance of our Pthreads implementation on a set of representative networks from various domains and with diverse topological features. For most networks, we obtain a speedup of over 50 for 64 cores and an almost linear speedup up to 32 cores, showcasing the flexibility and scalability of our algorithm. This paves the way for the usage of such counting algorithms on larger subgraph and network sizes without the obligatory access to a cluster.

关键词： parallel Algorithms Adaptive Load Balancing Complex Networks Graph Mining G-Tries

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Dynamic Frequency Scaling for Energy Consumption Reduction in Synchronous distributed applications 12

Dynamic Frequency Scaling for Energy Consumption Reduction i...

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12th IEEE international symposium on parallel and distributed processing with applications (ispa)

作者： Charr, Jean-Claude Couturier, Raphael Fanfakh, Ahmed Giersch, Arnaud Univ Franche Comte FEMTO ST Inst IUT Belfort Montbeliard F-90016 Belfort France

ISBN: (纸本)9781479942930

Dynamic Voltage Frequency Scaling (DVFS) can be applied to modern CPUs. This technique is usually used to reduce the energy consumed by a CPU while computing. Thus, decreasing the frequency reduces the power consumed by the CPU. However, it can also significantly affect the performance of the executed program if it is compute bound and if a low CPU frequency is selected. Therefore, the chosen scaling factor must give the best possible trade-off between energy reduction and performance. In this paper we present an algorithm that predicts the energy consumed with each frequency gear and selects the one that gives the best ratio between energy consumption reduction and performance. This algorithm works online without training or profiling and has a very small overhead. It also takes into account synchronous communications between the nodes that are executing the distributed algorithm. The algorithm has been evaluated over the SimGrid simulator while being applied to the NAS parallel benchmark programs. The results of the experiments show that it outperforms other existing scaling factor selection algorithms.

关键词： Benchmarktesting Degradation Energyconsumption Predictionalgorithms Programprocessors Time-frequencyanalysis Dynamicvoltagefrequencyscaling homogeneouscluster messagepassingprograms central processing units energy consumption Energy sources dynamic frequency deterioration Scale factor Energy conservation

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An Efficient Scheduling Algorithm for Energy Consumption Constrained parallel applications on Heterogeneous distributed Systems 15

An Efficient Scheduling Algorithm for Energy Consumption Con...

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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： Song, Jinlin Xie, Guoqi Li, Renfa Chen, Xiaoming Hunan Univ Coll Comp Sci & Elect Engn Changsha Hunan Peoples R China Key Lab Embedded & Network Comp Hunan Prov Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

As the explosive growth of energy consumption in current heterogeneous distributed systems, energy consumption constraint has been one of the primary design issues Minimizing the schedule length while satisfying the energy consumption constraint of parallel applications is one of the most important problem which has been studied recently. Previous studies have proposed a preassignment approach which tried to presuppose the minimum energy consumption assignment for unassigned tasks to solve the problem based on the dynamic voltage and frequency scaling (DVFS) technique. However, the preassignment of unassigned tasks with the minimum energy consumption does not necessarily lead to the minimization of the schedule length. In this study, we propose an efficient scheduling algorithm using a relative average assignments for tasks. The results of experiments on two real parallel applications validate that the proposed algorithm can obtain shorter schedule length while satisfying the energy consumption constraint compared with the state-ofthe-art methods in various situations.

关键词： dynamic voltage and frequency scaling (DVFS) energy consumption constraint heterogeneous distributed systems parallel application schedule length

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Blockchain-based Security Architecture for distributed Cloud Storage 15

Blockchain-based Security Architecture for Distributed Cloud...

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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： Li, Jiaxing Liu, Zhusong Chen, Long Chen, Pinghua Wu, Jigang Guangdong Univ Technol Sch Comp Sci & Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538637906

With the development of ICT industry, the volume of produced data is experiencing tremendous growth, which motivates more demands of storage capacity. Because of the limited storage capacity of users' terminals, more and more applications prefer to upload data to cloud platforms. However, it is well known that security should not be neglected in existing cloud storage architectures. Motivated by the increasing popularity of emerging blockchain technology, we propose a blockchain-based security architecture for distributed cloud storage. Moreover, we customize a genetic algorithm to solve the file block replica placement problem between multiple users and multiple data centers in the distributed cloud storage environment. Numerical experimental results show that the proposed architecture outperforms the traditional cloud storage architectures in terms of security, with acceptable network transmission delay.

关键词： cloud storage security blockchain architecture distributed

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NetANNS: A High-Performance distributed Search Framework Based On In-Network Computing 19

NetANNS: A High-Performance Distributed Search Framework Bas...

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19th IEEE international symposium on parallel and distributed processing with applications (IEEE ispa)

作者： Zhang, Penghao Pan, Heng Li, Zhenyu Xie, Gaogang Cui, Penglai Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Purple Mt Labs Nanjing Peoples R China Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China

ISBN: (纸本)9781665435741

Approximate nearest neighbor search (ANNS) is the most basic and important algorithm in Database, Machine Learning and other applications. With the expansion of cloud computing, the academia focuses on the study of how to optimize distributed frameworks based on approximate nearest neighbor search such as MapReduce, and Memcached. We implement a new distributed ANNS search framework (NetANNS). The main contributions of NetANNS are to accelerate the data preprocessing with programmable switch, and integrate a variety of efficient ANNS algorithms so that it can choose the most suitable algorithm for each datasets. The experiments show that the search efficiency of NetANNS is about 2x than the common distributed ANNS frameworks which are implemented based on the framework of MapReduce.

关键词： approximate nearest neighbor search distributed search in-network computation

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parallel Huffman Decoding: Presenting a Fast and Scalable Algorithm for Increasingly Multicore Devices 15

Parallel Huffman Decoding: Presenting a Fast and Scalable Al...

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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： Johnston, Beau McCreath, Eric C. Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia

ISBN: (纸本)9781538637906

Huffman encoding provides a simple approach for lossless compression of sequential data. The length of encoded symbols varies and these symbols are tightly packed in the compressed data. Thus, Huffman decoding is not easily parallelisable. This is unfortunate since it is desirable to have a parallel algorithm which scales with the increased core count of modern systems. This paper presents a parallel approach for decoding Huffman codes which work by decoding from every location in the bit sequence then concurrently combining the results into the uncompressed sequence. Although requiring more operations than serial approaches the presented approach is able to produce results marginally faster, on sufficiently large data sets, then that of a simple serial implementation. This is achieved by using the large number of threads available on modern GPUs. A variety of implementations, primarily OpenCL, are presented to demonstrate the scaling of this algorithm on CPU and GPU hardware in response to cores available. As devices with more cores become available, the importance of such an algorithm will increase.

关键词： Decoding Program processors Hardware Partitioning algorithms Multicore processing Encoding Image coding

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Efficient Decentralized Attribute-Based Encryption with Outsourced Computation for Mobile Cloud Computing 15

Efficient Decentralized Attribute-Based Encryption with Outs...

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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： Shao, Jiaye Zhu, Yanqin Ji, Qijin Soochow Univ Sch Comp Sci & Technol Suzhou Jiangsu Peoples R China

ISBN: (纸本)9781538637906

Multi-authority attribute-based encryption (ABE) is regarded as one of the most promising techniques to handle the problem of the access control of shared data because it provides fine-grained access control of encrypted data in cloud storge. However, most existing multi-authority ABE schemes suffer from expensive computational cost on the user side, which increases with the complexity of access structures. In this paper, we present a novel large universe decentralized ABE scheme with outsourced encryption and decryption based on the multi-authority system for mobile cloud computing. A majority of complex and expensive computation operations are migrated to the encryption and decryption proxy server respectively, so we can minimize the computation overhead for the data users simultaneously. The theoretical analysis indicates that our scheme is correct with static security in the random oracle model. Furthermore, the analytical comparison and extensive experimental results demonstrate that our scheme is efficient.

关键词： distributed processing Conferences Ubiquitous computing

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A speculative parallel intrusion prevention system based on Apache Spark 15

A speculative parallel intrusion prevention system based on ...

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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, Zhoukai Zhao, Yinliang Wang, Zhaorong Li, Yuxiang Xi An Jiao Tong Univ Dept Comp Sci & Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781538637906

Intrusion prevention system is the most important and popular tool in information security. It has been widely used to identify potential threats and respond to them swiftly. However, the existing IPS based on regular expression matching is time consuming and do not support large data well, since it scans and processes input linearly. To enhance conventional approach's parallelism and improve its efficiency for processing problems with large-scale data, this paper raised a speculative parallel intrusion prevention system based on Apache Spark. In the proposed system, the input packets are speculatively divided into several chunks, and then distributed into Apache Spark for parallel processing. After processing, the results are collected and evaluated to eliminate incorrect speculations. Experiments show that for large-scale data, by comparing with the conventional approach, the proposed system could markedly shorten the execution time for intrusion prevention. It can be proved that by adopting our novel system, the efficiency of intrusion prevention can be significantly enhanced.

关键词： Intrusion prevention system parallelization Software Thread-Level Speculation Apache Spark

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