In recent times, Machine Learning has played an important role in developing novel advanced tools for threat detection and mitigation. Intrusion Detection, Misinformation, Malware, and Fraud Detection are just some ex...
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As computational clusters rapidly grow in both size and complexity, system reliability and, in particular, application resilience have become increasingly important factors to consider in maintaining efficiency and pr...
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ISBN:
(纸本)9781605589428
As computational clusters rapidly grow in both size and complexity, system reliability and, in particular, application resilience have become increasingly important factors to consider in maintaining efficiency and providing improved computational performance over predecessor systems. One commonly used mechanism for providing application fault tolerance in parallel systems is the use of checkpointing. By making use of a multi-cluster simulator, we study the impact of sub-optimal checkpoint intervals on overall application efficiency. By using a model of a 1926 node cluster and workload statistics from Los Alamos National laboratory to parameterize the simulator, we find that dramatically over-estimating the AMTTI has a fairly minor impact on application efficiency while potentially having a much more severe impact on user-centric performance metrics such a queueing delay. We compare and contrast these results with the trends predicted by an analytical model. Copyright 2010 ACM.
The computing power provided by highperformance and low cost PC-based clusters and Grid computing platforms are attractive and they are equal or superior to supercomputers and mainframes. In parallel, discussions on ...
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Scientific applications running on heterogeneous computing systems, which often have unpredictable behavior, enhance their performance by employing loop scheduling techniques as methods to avoid load imbalance through...
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The emergence of pay-as-you-use compute clouds has enabled scientists to experiment with the latest processor architectures and accelerators. However, the lack of standardization in cloud computing, more specifically ...
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Grid technology is the great progress of network after Internet, since grid enables the integrated and collaborative use of distributed computing resources owned and managed by multiple organizations, available over a...
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Grid technology is the great progress of network after Internet, since grid enables the integrated and collaborative use of distributed computing resources owned and managed by multiple organizations, available over a local or wide area network. In this paper, we provided a data grid platform with integrated storage to solve such data grid problems by using PVFS2 to increase the data storage space. The experimental results presented show the effectiveness of such proposed combination of technologies
In this paper, an efficient technique is proposed to optimize the geometie and arrangements of the slots of the CARLSAs. Moment method in carried out to obtain the unknown excitation coefficients after spliting the sl...
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Cluster and grid computing is a relatively new interdisciplinary field, where computerscience, engineering and computational biology as its core supporting disciplines. The rise of cluster and grid computing discipli...
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Electric Vehicles (EVs) are becoming increasingly popular in recent years. Battery Electric Vehicles (BEVs) are a type of EVs use stored energy more efficiently than typical internal combustion engine powered counterp...
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In order to solve real-time control problems, a good software design together with an appropriate control scheme and a system identification method are extremely importance. To facilitate the software design to cope w...
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In order to solve real-time control problems, a good software design together with an appropriate control scheme and a system identification method are extremely importance. To facilitate the software design to cope with such a time critical system, the concept of imprecise and approximate computation has been imposed and applied in real-time scheduling problems for more than a decade. Applying neural network to solve real-time problem is always a problem to neural network practitioners. In this paper, a principle for neural computation and real-time system 一 imprecise neural computation 一 will be presented. This principle extends the idea of imprecise computation in real-time systems by introducing concepts like mandatory neural structure and imprecise pruning. Using such concepts, it is able to design and analyze a real-time neural system for different real-time applications.
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