this article describes an approach to parallelizing of data mining algorithms in logical programming framework, for distributed data processing in cluster. As an example Naive Bayes algorithm implementation in Prolog ...
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ISBN:
(纸本)9783030308599;9783030308582
this article describes an approach to parallelizing of data mining algorithms in logical programming framework, for distributed data processing in cluster. As an example Naive Bayes algorithm implementation in Prolog framework, its conversion into parallel type and execution on cluster with MPI system are described.
Given a trace of a distributed computation and a desired predicate, the predicate detection problem is to find a consistent global state that satisfies the given predicate. the predicate detection problem has many app...
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ISBN:
(纸本)9781450360944
Given a trace of a distributed computation and a desired predicate, the predicate detection problem is to find a consistent global state that satisfies the given predicate. the predicate detection problem has many applications in the testing and runtime verification of parallel and distributedsystems. We show that many problems related to predicate detection are in the parallel complexity class NC, the set of decision problems decidable in polylogarithmic time on a parallel computer with a polynomial number of processors. Given a computation on n processes with at most m local states per process, our parallel algorithm to detect a given conjunctive predicate takes O(log mn) time and O(m(3)n(3) log mn) work. the sequential algorithm takes O(mn(2)) time. For data race detection, we give a parallel algorithm that takes O(logmn log n) time, also placing that problem in NC. this is the first work, to the best of our knowledge, that places the parallel complexity of such predicate detection problems in the class NC.
there are considerations on the problem of time-consuming calculations in this article. this type of computational problems concerns to multiple aspects of earth sciences. distributedcomputing allows to perform calcu...
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ISBN:
(纸本)9783642312168
there are considerations on the problem of time-consuming calculations in this article. this type of computational problems concerns to multiple aspects of earth sciences. distributedcomputing allows to perform calculations in reasonable time. this way of processing requires a cluster architecture. the authors propose using Apache Hadoop technology to solve geophysics inversion problem. this solution is designed rather for analyzing data, but it also enables to perform computations. there is an architecture of solution proposed and real test carried out to determine the performance of method.
In this paper, we present a novel approach to optimally fuse estimates in distributed state estimation for linear and nonlinear systems. An optimal fusion requires the knowledge of the correct correlations between loc...
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ISBN:
(纸本)9780996452748
In this paper, we present a novel approach to optimally fuse estimates in distributed state estimation for linear and nonlinear systems. An optimal fusion requires the knowledge of the correct correlations between locally obtained estimates. the naive and intractable way of calculating the correct correlations would be to exchange information about every processed measurement between all nodes. Instead, we propose to obtain the correct correlations by keeping and processing a small set of deterministic samples on each node in parallel to the actual local state estimation. Sending these samples in addition to the local state estimate to the fusion center allows for correctly reconstructing the desired correlations between all estimates. In doing so, each node does not need any information about measurements processed on other nodes. We show the optimality of the proposed method by means of tracking an extended object in a multi-camera network.
We study a simple parallel algorithm for computing matchings in a graph. A variant for unweighted graphs finds a maximal matching using linear expected work and O(log(2) n) expected running time in the CREW PRAM model...
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ISBN:
(纸本)9783642400476
We study a simple parallel algorithm for computing matchings in a graph. A variant for unweighted graphs finds a maximal matching using linear expected work and O(log(2) n) expected running time in the CREW PRAM model. Similar results also apply to External Memory, MapReduce and distributed memory models. In the maximum weight case the algorithm guarantees a 1/2-approximation. Although the parallel execution time is linear for worst case weights, an experimental evaluation indicates good scalabilty on distributed memory machines and on GPUs. Furthermore, the solution quality is very good in practice.
this paper presents a control concept of virtual power plant with analysis of measured data of controlling distributed energy sources and energy storage system. the aim of the presented analysis is to demonstrate and ...
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ISBN:
(纸本)9781538646120
this paper presents a control concept of virtual power plant with analysis of measured data of controlling distributed energy sources and energy storage system. the aim of the presented analysis is to demonstrate and compare possibilities of controlling distributed energy source and energy storage system in parallel operation withthe grid.
the proceedings contain 102 papers. the special focus in this conference is on Algorithms and Architectures for parallel Processing. the topics include: Utility-Based Location Distribution Reverse Auction Incentive Me...
ISBN:
(纸本)9783030389604
the proceedings contain 102 papers. the special focus in this conference is on Algorithms and Architectures for parallel Processing. the topics include: Utility-Based Location Distribution Reverse Auction Incentive Mechanism for Mobile Crowd Sensing Network;safeguarding Against Active Routing Attack via Online Learning;reliability Aware Cost Optimization for Memory Constrained Cloud Workflows;null Model and Community Structure in Heterogeneous Networks;an Asynchronous Algorithm to Reduce the Number of Data Exchanges;two-Stage Clustering Hot Event Detection Model for Micro-blog on Spark;mobility-Aware Workflow Offloading and Scheduling Strategy for Mobile Edge computing;HSPP: Load-Balanced and Low-Latency File Partition and Placement Strategy on distributed Heterogeneous Storage with Erasure Coding;adaptive Clustering for Outlier Identification in High-Dimensional Data;Improving the parallelism of CESM on GPU;penguin Search Aware Proactive Application Placement;a Data Uploading Strategy in Vehicular Ad-hoc Networks Targeted on Dynamic Topology: Clustering and Cooperation;Cloud Server Load Turning Point Prediction Based on Feature Enhanced Multi-task LSTM;Neuron Fault Tolerance Capability Based Computation Reuse in DNNs;reliability Enhancement of Neural Networks via Neuron-Level Vulnerability Quantization;A Fault Detection Algorithm for Cloud computing Using QPSO-Based Weighted One-Class Support Vector Machine;paraMoC: A parallel Model Checker for Pushdown systems;FastDRC: Fast and Scalable Genome Compression Based on distributed and parallel Processing;a parallel Approach to Advantage Actor Critic in Deep Reinforcement Learning;Blockchain-PUF-Based Secure Authentication Protocol for Internet of things;parallel Approach to Sliding Window Sums;selective Velocity distributed Indexing for Continuously Moving Objects Model;a New Bitcoin Address Association Method Using a Two-Level Learner Model.
A recently developed parallel asynchronous solver for systems of ordinary differential equations (ODEs) is used to simulate flows along the channels in a river network. In our model, precipitation is applied over the ...
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ISBN:
(纸本)9780889869257
A recently developed parallel asynchronous solver for systems of ordinary differential equations (ODEs) is used to simulate flows along the channels in a river network. In our model, precipitation is applied over the hillslopes adjacent to the river network links and water movement from hillsope to link and along the river network is represented as a system of ODEs. the numerical solver is based on dense output Runge-Kutta methods that allow for asynchronous integration. A static partition method is used to distribute the workload among different processes, enabling a parallel implementation that capitalizes on a distributed memory system. Communication between processes is performed asynchronously. We illustrate the solver capabilities by integrating flow transport equations for a ∼32,000 km2 river basin subdivided into 574,000 sub-watersheds that are interconnected by the river network. We show that the runtime for an eight month-long simulation forced by 1-km resolution NEXRAD rainfall is completed in under 4 minutes using 64 computing nodes. In addition, we include equations to simulate small reservoirs spread throughout the river network and estimate changes in hydrographs at multiple locations. Our results provide a firm theoretical basis for the concept of distributed flood control systems.
Attribute-based communication provides a novel mechanism to dynamically select groups of communicating entities by relying on predicates over their exposed attributes. In this paper, we embed the basic primitives for ...
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ISBN:
(纸本)9783319597461;9783319597454
Attribute-based communication provides a novel mechanism to dynamically select groups of communicating entities by relying on predicates over their exposed attributes. In this paper, we embed the basic primitives for attribute-based communication into the functional concurrent language Erlang to obtain what we call AErlang, for attribute Erlang. To evaluate our prototype in terms of performance overhead and scalability we consider solutions of the Stable Marriage Problem based on predicates over attributes and on the classical preference lists, and use them to compare the runtime performance of AErlang withthose of Erlang and X10. the outcome of the comparison shows that the overhead introduced by the new communication primitives is acceptable, and our prototype can compete performance-wise with an ad-hoc parallel solution in X10.
Today healthcare industries are maintaining COVID-19 patients' information electronically which includes patients' diagnostic reports, patients' private information, and doctor prescriptions. However, the ...
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