General purpose GPU's (GPGPU) appearance made it possible that heterogeneous computing can be used by human beings. And it's also produce a reform for GPU's general purpose computing and parallel computing...
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General purpose GPU's (GPGPU) appearance made it possible that heterogeneous computing can be used by human beings. And it's also produce a reform for GPU's general purpose computing and parallel computing. Heterogeneous Systems has been adopted by large-scale of high-performance computers. Nowadays, fault tolerance technique is necessary among these large-scale kinds of scientific computing, but in a few years of GPGPU and heterogeneous system appearance, there is not an effective fault tolerance method come out, therefore, towards this situation, this paper will apply the traditional fault tolerance technique—application-level checkpointing to heterogeneous system. Cause the main solution of reducing overhead of the application-level checkpointing is reducing checkpoint data size, so after analyzing the heterogeneous system and GPGPU program, we propose a method to optimize the data storage of application-level checkpointing technique and validate its optimization by experiments.
In this paper, we consider novel anycast-based integrated routing protocol (AIRP) to reduce the cost in delay performance of communications in multihop WSNs. Without tight time synchronization or known geographic info...
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In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such ...
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ISBN:
(纸本)9781479909735
In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such as link prediction, friend recommendation and personalized searching. Personalized Page Rank, which ranks nodes according to the probabilities that a random walk starting from a personalized node stops at all nodes, is one of the most popular metrics for influence analysis. In this paper, we study the problem of inverse influence in online social networks. Different from Personalized Page Rank, the inverse influence for a personalized node ranks nodes according to the probabilities that all nodes stop at the personalized node in limited steps. We propose two computation models for inverse influence, i.e., the random walk based and the path based. Both of the models have high computation complexity, and cannot be used in large graphs, so we propose a Monte Carlo based approximation algorithm. Experiments from synthetic and real world datasets show that, our algorithm has equivalent or even better accuracy than related researches in link prediction, and thus can be used in friend recommendation in online social networks.
Continued increasing of fault rate in integrate circuit makes processors more susceptible to errors, especially many-core processor. Meanwhile, most systems or applications do not need full fault coverage, which has e...
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ISBN:
(纸本)9781479909735
Continued increasing of fault rate in integrate circuit makes processors more susceptible to errors, especially many-core processor. Meanwhile, most systems or applications do not need full fault coverage, which has excessive overhead. So on-demand fault tolerance is desired for these applications. In this paper, we propose an adaptive low-overhead fault tolerance mechanism for many-core system, called Device View Redundancy (DVR). It treats fault tolerance as a device that can be configured and used by application when high reliability is needed. Nevertheless, DVR exploits the idle resources for low-overhead fault tolerance, which is based on the observation that the utilization of many-core system is low due to lack of parallelism in application. Finally, the experiment shows that the performance overhead of DVR is reduced by 16% to 98% compared with full Dual Modular Redundancy (DMR).
Data skew is an important reason for the emergence of stragglers in MapReduce-like cloud systems. In this paper, we propose a Skew-Aware Task Scheduling (SATS) mechanism for iterative applications in MapReduce-like sy...
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ISBN:
(纸本)9781467356596
Data skew is an important reason for the emergence of stragglers in MapReduce-like cloud systems. In this paper, we propose a Skew-Aware Task Scheduling (SATS) mechanism for iterative applications in MapReduce-like systems. The mechanism utilizes the similarity of data distribution in adjacent iterations of iterative applications to reduce the straggle problem caused by data skew. It collects the data distribution information during the execution of tasks for the current iteration, and uses the information to guide data partitioning in tasks for the next iteration. We implement the mechanism in the HaLoop system and deploy it in a cluster. Experiments show that the proposed mechanism could deal with the data skew and improve the load balancing effectively.
parallel query processing over data streams in cloud computing environments has attracted considerable attention recently in various fields, due to the huge potential value of analyzing massive data or big data in a l...
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parallel query processing over data streams in cloud computing environments has attracted considerable attention recently in various fields, due to the huge potential value of analyzing massive data or big data in a large number of streaming applications. Nevertheless, existing studies on queries primarily focus on the algorithms for the specific query types with the lack of the general framework for processing various queries. Moreover, existing parallel frameworks in cloud such as MapReduce and its variations are not suitable for many complex queries over complex data streams. In this paper, we extensively discuss the problem of designing the general framework for parallel queries over data streams in cloud. Particularly, we propose and implement a framework called GPS, which can be well adapted to various queries over complex data streams like the uncertain data streams. Furthermore, we further propose a hierarchical and general parallel model for queries over data streams based on the proposed framework, which is more flexible than the MapReduce model. The skyline queries over uncertain data streams based on our proposed framework with real deployment are conducted as an example to verify the performances of our proposals.
A general hardware structure was proposed to accelerate variable data set management, which was designed to accept instructions flexibly and accomplish the commonly used functions and some more complicated functions o...
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A general hardware structure was proposed to accelerate variable data set management, which was designed to accept instructions flexibly and accomplish the commonly used functions and some more complicated functions of the linked-list data structure .The structure can access the data based on both pointer and address mechanism. In order to fully utilize the limited memory resources, we proposed a memory recycle scheme to reuse the memory space where the data have been deleted. Experimental results on FPGA show that our proposal can accelerate the variable data set management. Only few hardware resources were used and it consumed pretty low power. Compared with the software linked-list structure in PC, our proposal in FPGA achieved high speedups.
As the fourth passive circuit component, a memristor is a nonlinear resistor that can "remember" the amount of charge passing through it. The characteristic of "remembering" the charge and non-volatility makes mem...
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As the fourth passive circuit component, a memristor is a nonlinear resistor that can "remember" the amount of charge passing through it. The characteristic of "remembering" the charge and non-volatility makes memristors great potential candidates in many fields. Nowadays, only a few groups have the ability to fabricate memristors, and most researchers study them by theoretic analysis and simulation. In this paper, we first analyse the theoretical base and characteristics of memristors, then use a simulation program with integrated circuit emphasis as our tool to simulate the theoretical model of memristors and change the parameters in the model to see the influence of each parameter on the characteristics. Our work supplies researchers engaged in memristor-based circuits with advice on how to choose the proper parameters.
In light of GPUs’ powerful floating-point operation capacity,heterogeneous parallel systems incorporating general purpose CPUs and GPUs have become a highlight in the research field of high performance computing(HPC)...
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In light of GPUs’ powerful floating-point operation capacity,heterogeneous parallel systems incorporating general purpose CPUs and GPUs have become a highlight in the research field of high performance computing(HPC).However,due to the complexity of programming on GPUs,porting a large number of existing scientific computing applications to the heterogeneous parallel systems remains a big *** OpenMP programming interface is widely adopted on multi-core CPUs in the field of scientific *** effectively inherit existing OpenMP applications and reduce the transplant cost,we extend OpenMP with a group of compiler directives,which explicitly divide tasks among the CPU and the GPU,and map time-consuming computing fragments to run on the GPU,thus dramatically simplifying the *** have designed and implemented MPtoStream,a compiler of the extended OpenMP for AMD’s stream processing *** experimental results show that programming with the extended directives deviates from programming with OpenMP by less than 11% modification and achieves significant speedup ranging from 3.1 to 17.3 on a heterogeneous system,incorporating an Intel Xeon E5405 CPU and an AMD FireStream 9250 GPU,over the execution on the Xeon CPU alone.
Force-directed approach is one of the most widely used methods in graph drawing research. There are two main problems with the traditional force-directed algorithms. First, there is no mature theory to ensure the conv...
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Force-directed approach is one of the most widely used methods in graph drawing research. There are two main problems with the traditional force-directed algorithms. First, there is no mature theory to ensure the convergence of iteration sequence used in the algorithm and further, it is hard to estimate the rate of convergence even if the convergence is satisfied. Second, the running time cost is increased intolerablely in drawing largescale graphs, and therefore the advantages of the force-directed approach are limited in practice. This paper is focused on these problems and presents a sufficient condition for ensuring the convergence of iterations. We then develop a practical heuristic algorithm for speeding up the iteration in force-directed approach using a successive over-relaxation (SOR) strategy. The results of computational tests on the several benchmark graph datasets used widely in graph drawing research show that our algorithm can dramatically improve the performance of force-directed approach by decreasing both the number of iterations and running time, and is 1.5 times faster than the latter on average.
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