Recently self-simulation algorithms have been developed to execute algorithms on a reconfigurable mesh (RM) of size smaller than recommended in those algorithms. Optimal slowdown, in self-simulation, has been achieved...
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Recently self-simulation algorithms have been developed to execute algorithms on a reconfigurable mesh (RM) of size smaller than recommended in those algorithms. Optimal slowdown, in self-simulation, has been achieved withthe compromise that the resultant algorithms fail to remain AT(2) optimal. In this paper, we introduce, for the first time, the idea of adaptive algorithm which runs on RM of variable sizes without compromising the AT(2) optimality. We support our idea by developing adaptive algorithms for sorting items and computingthe contour of maximal elements of a set of planar points on RM. (C) 2000 Published by Elsevier Science B.V. All rights reserved.
this research presents a novel wavelet transform and machine learning-based method to microgrid protection, with a focus on the Unified Power Flow Controller (UPFC). Microgrid components such as distribution generator...
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ISBN:
(纸本)9798350385939;9798350385922
this research presents a novel wavelet transform and machine learning-based method to microgrid protection, with a focus on the Unified Power Flow Controller (UPFC). Microgrid components such as distribution generators are critical to enhancing the reliability of electricity networks. For different sources and loads to integrate smoothly, effective defect identification is required. the technique uses wavelet transform to extract meaningful information from failure signals, which is then fed into a machine learning model for real-time identification. this method analyzes current signals from both ends of the transmission line using wavelet-based multi-resolution analysis, and then compares the results to preset thresholds to generate fault indices. this approach offers a reliable microgrid protection solution with lower losses and increased dependability.
We develop a parallel algorithm, by using CUDA, for calculating the concentration of multifunctional magnetic nanoparticles in capillaries under the influences of magnetic force, blood flow and diffusion process. the ...
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ISBN:
(纸本)9781479908066;9781479908059
We develop a parallel algorithm, by using CUDA, for calculating the concentration of multifunctional magnetic nanoparticles in capillaries under the influences of magnetic force, blood flow and diffusion process. the task of computing particle, concentration on the considered plane is distributed to computational threads. the continuity equation describing the time rate of change of the multifunctional particle concentration in each small element on the considered plane is solved via the explicit finite different method. the simulation results show the distributions of particle concentration on the focused plane in the blood vessel which are useful visualization for the biomedical researchers. the performance of parallelcomputing is also examined.
High-speed, large-scale networks present new challenges to an intrusion detection system. these challenges include: the volume of data that must be analyzed, the high-speed data stream that IDS must deal with. To adap...
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ISBN:
(纸本)0769524052
High-speed, large-scale networks present new challenges to an intrusion detection system. these challenges include: the volume of data that must be analyzed, the high-speed data stream that IDS must deal with. To adapt these new demands, this paper propose a novel architecture for Large-scale distributed Intrusion Detection Systems(LDIDS) that can be applied to large-scale networks. this architecture is based on hierarchy, which consists of a root node, several branch nodes and leaf nodes. In this architecture, each node is an independent IDS, all IDSs constituting the whole LDIDS. the main advantage of this architecture is scalability and collaboration. We describe the framework of the nodes in detail. We also present an implementation of LDIDS which is designed according to the architecture.
Agent-based systems are inherently distributed and parallel by a distributed memory model, but agent-based simulation is often characterised by a shared memory model. this paper discusses the challenges of and solutio...
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ISBN:
(纸本)9789897585289
Agent-based systems are inherently distributed and parallel by a distributed memory model, but agent-based simulation is often characterised by a shared memory model. this paper discusses the challenges of and solution for large-scale distributed agent-based simulation using virtual machines. Simulation of large-scale multi-agent systems with more than 10000 agents on a single processor node requires high computational times that can be far beyond the constraints set by the users, e.g., in real-time capable simulations. parallel and distributed simulation involves the transformation of shared to a communication-based distributed memory model that can create a significant communication overhead. In this work, instead distributing an originally monolithic simulator with visualisation, a loosely coupled distributed agent process platform cluster network performing the agent processing for simulation is monitored by a visualisation and simulation control service. A typical use case of traffic simulation in smart city context is used for evaluation the performance of the proposed DSEJAMON architecture.
the design of a debugging and performance analysis system that includes a specification language for process-level events and hardware for nonintrusive identification of these events during the execution of parallel a...
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the design of a debugging and performance analysis system that includes a specification language for process-level events and hardware for nonintrusive identification of these events during the execution of parallel and distributedapplications for a nonshared memory system is presented. the design is based on a formal event/action model and a layered architecture model that have been previously presented. Background, related work, and specification, and identification of events are discussed.
the emergence of the Internet of things (IoT) has raised several issues related to the development and deployment of IoT applications within IT infrastructures. In this context, cloud computing is often faced with lat...
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ISBN:
(纸本)9781665496070
the emergence of the Internet of things (IoT) has raised several issues related to the development and deployment of IoT applications within IT infrastructures. In this context, cloud computing is often faced with latency issues when hosting such applications, even though the cloud environment offers promising opportunities to increase productivity and reduce costs significantly. therefore, it is important to review the current conformance scheme in the cloud environments by considering the coordination challenges during data processing. For this purpose, we suggest an architecture for conformance testing of IoT based implementations in the Cloud. the idea is to set parallel testers to handle the conformance of the distributed implementation with respect to the specification. In this case, the testing process must support coordination between the different distributed components in order to detect the resulting faults. therefore, the main contribution of this work is to propose a new architecture based on Markov decision processes with an adaptive controller to monitor and optimize the overall testing process in the distributed Cloud.
One important way of solving 110 bottleneck is to develop parallel file system. Research showed that the strided file access pattern in scientific applications combined with current file system methods to perform thes...
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ISBN:
(纸本)9780769527369
One important way of solving 110 bottleneck is to develop parallel file system. Research showed that the strided file access pattern in scientific applications combined with current file system methods to perform these accesses lead to unacceptable performance for large data access. To enhance performance of discontiguous data access, we have created a new high performance 110 method: the user-defined file view and combining 110 requests (UFCR). We have implemented our ideas on WPFS. Experimentation results showed that our method can substantially enhance the performance of scientific applications.
Huge energy consumption of large-scale cloud data centers damages the environment with excessive carbon emission. More and more data center operators are seeking to reduce carbon footprint via various types of renewab...
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ISBN:
(纸本)9781509050819
Huge energy consumption of large-scale cloud data centers damages the environment with excessive carbon emission. More and more data center operators are seeking to reduce carbon footprint via various types of renewable energy sources. However, the intermittent availability of renewable energy source makes it quite challenging to cooperate the dynamic workload arrivals. In this paper, we investigate how to coordinate multi type renewable energy (e.g. wind power and solar power) in order to reduce the long-term energy cost with spatio-temporal diversity of electricity price for geo-distributed cloud data centers under the constraints of service level agreement (SLA) and carbon footprints. To tackle the randomness of workload arrival, dynamic electricity price change and renewable energy generation, we first formulate the minimizing energy cost problem into a constrained stochastic optimization problem. then, based on Lyapunov optimization technique, we design an online control algorithm which can work without long-term future system information for solving the problem. Finally, we evaluate the effectiveness of the algorithm with extensive simulations based on real-world workload traces, electricity price and historic climate data.
Graphics processing units (GPUs) are powerful computational devices tailored towards the needs of the 3-D gaming industry for high-performance, real-time graphics engines. Nvidia Corporation released a new generation ...
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ISBN:
(纸本)9780769536422
Graphics processing units (GPUs) are powerful computational devices tailored towards the needs of the 3-D gaming industry for high-performance, real-time graphics engines. Nvidia Corporation released a new generation of GPUs designed for general-purpose computing in 2006, and it released a GPU programming language called CUDA in 2007. the DNA microarray technology is a high throughput tool for assaying mRNA abundance in cell samples. In. data analysis, scientists often apply hierarchical clustering of the genes, where a fundamental operation is to calculate all pairwise distances. If there are n genes, it takes O(n(2)) time. In this work, GPUs and the CUDA language are used to calculate pairwise distances. For Manhattan distance, GPU/CUDA achieves a 40 to 90 times speed-up compared to the central processing unit implementation;for Pearson correlation coefficient, the speed-up is 28 to 38 times.
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