distributed vertex-centric graph processing systems have been recently proposed to perform different types of analytics on large graphs. these systems utilize the parallelism of shared nothing clusters. In this work w...
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ISBN:
(纸本)9781631900433
distributed vertex-centric graph processing systems have been recently proposed to perform different types of analytics on large graphs. these systems utilize the parallelism of shared nothing clusters. In this work we propose a novel model for the performance cost of such clusters. We also define novel metrics related to the workload balance and network communication cost of clusters processing massive real graph datasets. We empirically investigate the effects of different graph partitioning mechanisms and their tradeoff for two different categories of graph processing algorithms.
A distributed scheduling algorithm is proposed for achieving end-to-end flow max-min fairness in wireless multi-hop networks. the problem is modeled as an optimization problem by taking into account the MAC-layer cons...
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ISBN:
(纸本)9780769530499
A distributed scheduling algorithm is proposed for achieving end-to-end flow max-min fairness in wireless multi-hop networks. the problem is modeled as an optimization problem by taking into account the MAC-layer constraints. With dual programming and Lagrange relaxation, the problem is decomposed into two subproblems, one is for transport layer at the source node, and the other for MAC layer in the network. A max-price based max-min fair rate allocation algorithm is adopled for the transport layer subproblem and an algorithm based on integer programming is designed for scheduling link activities at MAC layer Simulation results show that the proposed algorithm can achieve conflict-free schedule for wireless links and provide max-min fairness for end-to-end flows efficiently.
the problem is that the parallel scheduling strategies are minimally supported in distributed environments. the well-known Coffman-Graham algorithm is highly effective but applied only for the sample case when all tas...
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ISBN:
(纸本)9780769527369
the problem is that the parallel scheduling strategies are minimally supported in distributed environments. the well-known Coffman-Graham algorithm is highly effective but applied only for the sample case when all tasks have the same execution time and not applied for the distributed systems. In this paper, an expanding task graph and an expanding Coffman-Graham algorithm, which orients to the distributed systems and can be applied for the case when the tasks have the different execution time, are proposed Like the well-known Coffman-Graham algorithm, the ECG algorithm is proved to be an efficient scheduling algorithm for the distributed systems, through presenting and deducting one theorem and two corollaries.
An interesting challenge in E-health is to perform real-time diagnosis. In many distributedcomputing systems the data processing stage, generally assigned on standard computational CPU environments, is a critical asp...
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ISBN:
(纸本)9781467394734
An interesting challenge in E-health is to perform real-time diagnosis. In many distributedcomputing systems the data processing stage, generally assigned on standard computational CPU environments, is a critical aspect. In particular, the analysis of magnetic resonance imaging (MRI) for improving the quality of images and helping the diagnosis requires an high computational complexity. Using Graphics Processing Units (GPUs) on High Performance computing (HPC), the images processing step can be accelerated by speeding the whole diagnosis procedure. In this paper, we propose a parallel algorithm, on a GPU environment, for MRI denoising in order to make the diagnostic system more efficient. As case study, we consider the Optimized Blockwise Non Local Means (OB-NLM) method. Its intrinsic nature makes it perfectly suited for parallelization and multithreading implementation, especially for GPUs architectures. the results show a significant improvement of the entire healthcare practice procedure in terms of performances.
AGEL-SVM is an extension to a kernel Support Vector Machine (SVM) and is designed for distributedcomputing using Approximate Global Exhaustive Local sampling (AGEL)-SVM. the dual form of SVM is typically solved using...
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ISBN:
(纸本)9781450355490
AGEL-SVM is an extension to a kernel Support Vector Machine (SVM) and is designed for distributedcomputing using Approximate Global Exhaustive Local sampling (AGEL)-SVM. the dual form of SVM is typically solved using sequential minimal optimization (SMO) which iterates very fast if the full kernel matrix can fit in a computer's memory. AGEL-SVM aims to partition the feature space into sub problems such that the kernel matrix per problem can fit in memory by approximating the data outside each partition. AGEL-SVM has similar Cohen's Kappa and accuracy metrics as the underlying SMO implementation. AGEL-SVM's training times greatly decreased when running on a 128 worker MATLAB pool on Amazon's EC2. Predictor evaluation times are also faster due to a reduction in support vectors per partition.
A parallel Strength Pareto Multi-objective Evolutionary Algorithm (PSPMEA) is proposed. PSPMEA is a parallelcomputing model designed for solving Pareto-based multi-objective optimization problems by using an evolutio...
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ISBN:
(纸本)0780378407
A parallel Strength Pareto Multi-objective Evolutionary Algorithm (PSPMEA) is proposed. PSPMEA is a parallelcomputing model designed for solving Pareto-based multi-objective optimization problems by using an evolutionary procedure. In this procedure, both global parallelization and island parallel evolutionary algorithm models are used. Each subpopulation evolves separately with different crossover and mutation probability, but they exchange individuals in the elitist archive. the benchmark problems numerical experiment results demonstrate that the proposed method can rapidly converge to the Pareto optimal front and spread widely along the front.
Mobile computing systems have many constraints such as low battery power low bandwidth, high mobility and lack of stable storage which are not presented in static distributed systems. In this paper we propose an effic...
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ISBN:
(纸本)0769524052
Mobile computing systems have many constraints such as low battery power low bandwidth, high mobility and lack of stable storage which are not presented in static distributed systems. In this paper we propose an efficient communication-induced checkpointing protocol for mobile computing systems. We also propose an asynchronous recovery protocol based on the checkpointing protocol. Mobile support stations control major parts of the checkpointing and recovery such as storing and tracing the checkpoints, requesting rollback and logging messages, so that mobile hosts do not incur much overhead. the recovery algorithm has no domino effect and a failed process needs to roll back to its latest checkpoint and request only a subset of the processes to rollback to a consistent checkpoint. Our recovery protocol uses selective message logging at the mobile support station to handle the messages lost due to rollback.
Improvements in computer and networking technologies over the past decades produced new type of collaborative computing environment called Gild Networks. Grid is a parallel and distributedcomputing network system tha...
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ISBN:
(纸本)9781424419678
Improvements in computer and networking technologies over the past decades produced new type of collaborative computing environment called Gild Networks. Grid is a parallel and distributedcomputing network system that provides the ability to perform higher throughput computing by taking advantage of many computing resources available in the network. therefore, to achieve a scalable and reliable Grid network system, we need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a distributed and scalable load-balancing framework for Gild Networks. the generated network system is self-organized and depends only on local information for load distribution and resource discovery. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.
this paper presents an analytical comparison of parallel join algorithms in a generalized multiprocessor framework and a simplified, heterogenous Grid Environment. We develop a concise but comprehensive analytical mod...
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ISBN:
(纸本)9780769530499
this paper presents an analytical comparison of parallel join algorithms in a generalized multiprocessor framework and a simplified, heterogenous Grid Environment. We develop a concise but comprehensive analytical model for the well-known Hash Join algorithm and compare it to Nested-Loop and Sort-Merge Join algorithms. We concentrate on a limited number of characteristic parameters to keep the analytical model clear and focused. We justify that a meaningful model can be built upon only three characteristic parameter sets, describing node processing performance, the I/O and the disk bandwidth, which are the parameters for the optimization the Grid workflow by a smart brokerage mechanism. Based on these results the paper proves that by a smart enhancement of the algorithms exploiting the specifics of the Grid the known performance results for a homogenous multi-processor architecture are to be revised for a heterogenous Grid environment.
Numerical methods based on interval arithmetic ore efficient means to reliably solve nonlinear systems of equations. Algorithm bc3revise is an interval method that tightens variables' domains by enforcing a proper...
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ISBN:
(纸本)9780769534435
Numerical methods based on interval arithmetic ore efficient means to reliably solve nonlinear systems of equations. Algorithm bc3revise is an interval method that tightens variables' domains by enforcing a property called box consistency. It has been successfully used on difficult problems whose solving eluded traditional numerical methods. We present a new algorithm to enforce box consistency that is simpler than bc3revise, faster and easily data parallelizable. A parallel implementation with Intel SSE2 SIMD instructions shows that an increase in performance of up to an order of magnitude and more is achievable.
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