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A Programming Language Approach to Internet-Based Virtual Computing Environment

Journal of Computer science & technology 2011年第4期26卷 600-615页

作者：王戟沈锐王怀民 National Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology

There is an increasing need to build scalable distributed systems over the Internet infrastructure. However the development of distributed scalable applications suffers from lack of a wide accepted virtual computing environment. Users have to take great efforts on the management and sharing of the involved resources over Internet, whose characteristics are intrinsic growth, autonomy and diversity. To deal with this challenge, Internet-based Virtual Computing Environment （iVCE） is proposed and developed to serve as a platform for distributed scalable applications over the open infrastructure, whose kernel mechanisms are on-demand aggregation and autonomic collaboration of resources. In this paper, we present a programming language for iVCE named Owlet. Owlet conforms with the conceptual model of iVCE, and exposes the iVCE to application developers. As an interaction language based on peer-to-peer content-based publish/subscribe scheme, Owlet abstracts the Internet as an environment for the roles to interact, and uses roles to build a relatively stable view of resources for the on-demand resource aggregation. It provides language constructs to use 1） distributed event driven rules to describe interaction protocols among different roles, 2） conversations to correlate events and rules into a common context, and 3） resource pooling to do fault tolerance and load balancing among networked nodes. We have implemented an Owlet compiler and its runtime environment according to the architecture of iVCE, and built several Owlet applications, including a peer-to-peer file sharing application. Experimental results show that, with iVCE, the separation of resource aggregation logic and business logic significantly eases the process of building scalable distributed applications.

关键词： distributed architecture distributed programming on demand aggregation virtual computing

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Security Issues and Solutions in Cloud Computing

Security Issues and Solutions in Cloud Computing

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International Conference on distributed Computing Systems Workshop

作者： Pengfei You Yuxing Peng Weidong Liu Shoufu Xue National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China Jiangsu Automation Research Institute Jiangsu China CPLA Air Defence Forces Command Academy Zhengzhou Henan China

Recently, Cloud computing, as one of the hottest words in IT world, has drawn great attention. Many IT companies such as IBM, Google, Amazon, Microsoft, Yahoo and others vigorously develop cloud computing systems and related products to customers. However, there are still some difficulties for customers to adopt cloud computing, in which many security issues exist, because data for a customer is stored and processed in cloud, not in a local machine. This paper briefly introduces cloud computing and its key concepts. In particularly, we intend to discuss security requirements and security issues involving data, application and virtualization in cloud computing, as well as current solutions to these issues.

关键词： Cloud computing Computational modeling Virtual machine monitors Operating systems Cryptography

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Heterogeneity-aware Peak Power Management for Accelerator-based Systems

Heterogeneity-aware Peak Power Management for Accelerator-ba...

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17th IEEE International Conference on parallel and distributed Systems (ICPADS)

作者： Wang, Guibin Lin, Yisong National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

ISBN: (纸本)9780769545769

Power management has become one of the first-order considerations in high performance computing field. Many recent studies focus on optimizing the performance of a computer system within a given power budget. However, most existing solutions adopt fixed period control mechanism and are transparent to the running applications. Although the application-transparent control mechanism has relatively good portability, it exhibits low efficiency in accelerator-based heterogeneous parallel systems. In typical accelerator-based parallel systems, different processing units have largely different processing speeds and power consumption. Under a given power constraint, how to choose the processor to be slowed down and how to schedule a parallel task onto different processors for the maximum performance are different from those in homogeneous systems and have not been well studied. From the motivating example in this paper, we could find that in order to efficiently harness the heterogeneous parallel processing, one should not only perform dynamic voltage/frequency scaling (DVFS) to meet the power budget, but also tune the parallel task scheduling to adapt to the changes. In this paper, we propose a heterogeneity-aware peak power management, which extends existing application-transparent power controller with an application-aware power controller. Firstly, we theoretically analyze the conditions for the maximum performance given a power budget for heterogeneous systems. Based on this result, we provide a power-constrained parallel task partition algorithm, which coordinates parallel task partition and voltage scaling for heterogeneous processing units to achieve the optimal performance given a system power budget. Finally, we evaluate the proposed method on a typical CPU-GPU heterogeneous system, and validate the superiority of application-aware power controller over the existing method.

关键词： Accelerator-based Systems Peak Power Management GPU

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PS-SIM: An Execution-Driven Performance Simulation technology Based on Process-Switch

PS-SIM: An Execution-Driven Performance Simulation Technolog...

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International Conference on Advances in Computer science, Environment, Ecoinformatics, and Education

作者： Guo, Xiaowei Lin, Yufei Xu, Xinhai Zhang, Xin National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

ISBN: (纸本)9783642233234

Nowadays, the performance of large-scale parallel computer system improves continuously, and the system scale becomes extremely large. Performance prediction has become an important approach to guide system design, implementation and optimization. Simulation method is the most widely used performance prediction technology for large-scale parallel computer system. In this paper, after analyzing the extant problems, we proposed a novel execution-driven performance simulation technology based on process-switch. We designed a simulation framework named PS-SIM, and implemented a prototype system based on MPICH2. Finally, we verified the proposed approach by experiments. Experimental results show that the approach has high accuracy and simulation performance.

关键词： Performance Prediction Large-Scale parallel Computer System Execution-Driven Simulation MPICH

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A performance study of CSMA in wireless networks with successive interference cancellation

A performance study of CSMA in wireless networks with succes...

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IEEE International Conference on Communications (ICC)

作者： Shaohe Lv Weihua Zhuang Xiaodong Wang Chi Liu Xiaofeng Hu Yipin Sun Xingming Zhou Institute of Network Information and Security National University of Defense Technology Changsha China Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada Central South University Changsha China National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

Successive interference cancellation (SIC) is an effective way of multipacket reception to combat interference. As conventional CSMA (Carrier Sense Multiple Access) is designed for single packet reception, it is unclear whether or not CSMA performs well to exploit the SIC capability. In this paper, we analyze the performance of a simple CSMA protocol in a network with SIC. For a given link, we derive the residing areas of an interfering node when simultaneous transmission is allowed and when the interference is harmful, respectively. We show that, though SIC provides many new transmission opportunities, CSMA cannot effectively exploit them. There is a fundamental tradeoff in a CSMA protocol between exploiting the transmission opportunities from SIC and capturing the harmful interference. In many cases, when CSMA achieves its best performance, almost all new transmission opportunities are not exploited. It is therefore very necessary to design a new distributed access protocol in wireless networks with SIC.

关键词： Silicon carbide Multiaccess communication Interference Receivers Propagation losses Protocols Wireless networks

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P-Tracer: Path-Based Performance Profiling in Cloud Computing Systems

P-Tracer: Path-Based Performance Profiling in Cloud Computin...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Haibo Mi Huaimin Wang Hua Cai Yangfan Zhou Michael R. Lyu Zhenbang Chen National Lab for Parallel & Distributed Processing National Univ. of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Company Hangzhou China Dept. of Computer Science & Engineering The Chinese Univ. of Hong Kong Hong Kong

In large-scale cloud computing systems, the growing scale and complexity of component interactions pose great challenges for operators to understand the characteristics of system performance. Performance profiling has long been proved to be an effective approach to performance analysis; however, existing approaches do not consider two new requirements that emerge in cloud computing systems. First, the efficiency of the profiling becomes of critical concern; second, visual analytics should be utilized to make profiling results more readable. To address the above two issues, in this paper, we present P-Tracer, an online performance profiling approach specifically tailored for large-scale cloud computing systems. P-Tracer constructs a specific search engine that adopts a proactive way to process performance logs and generates particular indices for fast queries; furthermore, PTracer provides users with a suite of web-based interfaces to query statistical information of all kinds of services, which helps them quickly and intuitively understand system behavior. The approach has been successfully applied in Alibaba Cloud Computing Inc. to conduct online performance profiling both in production clusters and test clusters. Experience with one real-world case demonstrates that P-Tracer can effectively and efficiently help users conduct performance profiling and localize the primary causes of performance anomalies.

关键词： Cloud computing Instruments Postal services Search engines Shape System performance Production

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Towards estimating expected sizes of probabilistic skylines

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science China(Information sciences) 2011年第12期54卷 2574-2584页

作者： YANG YongTao & WANG YiJie National Key laboratory for parallel and distributed processing, School of Computer, National University of Defense technology, Changsha 410073, China 1. National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

We consider the maximal vector problem on uncertain data, which has been recently posed by the study on processing skyline queries over a probabilistic data stream in the database context. Let D n be a set of n points in a d-dimensional space and q (0 < q 1) be a probability threshold; each point in D n has a probability to occur. Our problem is concerned with how to estimate the expected size of the probabilistic skyline, which consists of all the points that are not dominated by any other point in D n with a probability not less than q. We prove that the upper bound of the expected size is O(min{n, (- ln q)(ln n) d-1 }) under the assumptions that the value distribution on each dimension is independent and the values of the points along each dimension are distinct. The main idea of our proof is to find a recurrence about the expected size and solve it. Our results reveal the relationship between the probability threshold q and the expected size of the probabilistic skyline, and show that the upper bound is poly-logarithmic when q is not extremely small.

关键词： probabilistic skyline probabilistic data streams expected size

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Memory access characterization of scientific applications on GPU and its implication on low power optimization

Memory access characterization of scientific applications on...

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2011 International Conference on Computational and Information sciences, ICCIS 2011

作者： Wang, Guibin National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

ISBN: (纸本)9780769545011

Following current IC design technology trend, modern GPUs integrate more and more processing cores, and the speed gap between processor and memory system becomes even larger. As the number of cores continually increases, the available bandwidth per core decreases correspondingly. Therefore, memory access performance has been one of the most critical bottlenecks for better performance. This paper analyzes the impact of memory system on performance and scalability for GPU with several scientific applications using a cycle-accurate simulator. Two observations we make are (1) that memory bandwidth has relatively greater impact on performance than memory latency, because the latter factor could be well hidden with tremendous concurrent executing threads supported in modern GPU architecture, and (2) that through examining the performance scalability of variable active cores, using the maximum hardware-supported cores may not bring in better performance, especially for the memory-intensive applications. In the end we suggest a better power-efficient exploitation of GPU is to make judicious concurrency-throttling based on the memory usage in application. © 2011 IEEE.

关键词： Graphics processing unit

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Data parallelism exploiting for H.264 encoder

Data parallelism exploiting for H.264 encoder

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International Conference on Multimedia and Signal processing

作者： Wen, Mei Ren, Ju Wu, Nan Su, Huayou Xun, Changqing Zhang, Chunyuan Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9780769543567

Real-time H.264 encoding of high-definition (HD) video (up to 1080p) is a challenge workload to most existing programmable processors. Instead, the novel programmable parallel processors such as stream processor, Graphic processor unit (GPU) and DSP offer a different and very promising technology for these demands. Thus, parallel computing for H.264 encoding on these processors is becoming a hot research point. It's challenged, because most emerging parallel processors focus on supporting Data Level parallel (DLP), while the dependency inherently existing in traditional H.264 encoding algorithm significantly restricts exploiting DLP. Facing the challenge, this paper presents data parallel processing methods for key modules of H.264 encoder which can eliminate the dependency restriction. The result shows that key modules including Intra-prediction, Inter-prediction and CAVLC achieve significant speedup on stream processor by using these data parallel processing methods.© 2011 IEEE.

关键词： parallel processing systems

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Communication-aware task partition and voltage scaling for energy minimization on heterogeneous parallel systems

Communication-aware task partition and voltage scaling for e...

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2011 12th International Conference on parallel and distributed Computing, Applications and Technologies, PDCAT 2011

作者： Wang, Guibin Song, Wei National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

ISBN: (纸本)9780769545646

Heterogeneous parallel systems have become popular in general purpose computing and even high performance computing fields. There are many studies focused on harnessing heterogeneous parallel processing for better performance. However the energy optimization for heterogeneous system has not been well studied. Owing to the differences in performance and energy consumption, the energy optimization technique for heterogeneous system is different from the existing methods designed for homogeneous system. Besides typical voltage scaling method, reasonable task partitioning is also an essential method for optimizing energy consumption on heterogeneous systems. Through partitioning a data parallel task and mapping sub-tasks onto several processors, one could achieve better performance and reduced energy consumption. As the computation cost reduces with specific accelerators, the communication overhead becomes more prominent. Therefore, the task partition optimization should holistically consider the computation improvement and communication overhead to achieve higher energy efficiency. Typically, task partition and voltage scaling are not orthogonal and influence the effect of each other in the energy optimization problem. In order to harness both two knobs efficiently, this paper proposes an integer linear programming (ILP) based energy-optimal solution designed for heterogeneous system. We present a case study of optimizing MGRID benchmark on a typical CPU-GPU heterogeneous system. The experimental results demonstrate that the proposed method could exploit the heterogeneity in different processors and achieve improved energy efficiency. © 2011 IEEE.

关键词： Energy efficiency

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