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Titlebook: Algorithms and Architectures for Parallel Processing; 18th International C Jaideep Vaidya,Jin Li Conference proceedings 2018 Springer Natur

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發(fā)表于 2025-3-30 10:17:55 | 只看該作者
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發(fā)表于 2025-3-30 15:33:30 | 只看該作者
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發(fā)表于 2025-3-30 19:22:02 | 只看該作者
Document Nearest Neighbors Query Based on Pairwise Similarity with MapReduceive to the number of the intermediate results. For the purpose of intermediate results reduction, . is proposed for nearest neighbor query based on pairwise similarity. Since only first top-. neighbors are output for each document, the size of records shuffled is kept in the same magnitude as input
54#
發(fā)表于 2025-3-30 23:26:16 | 只看該作者
Accurate Identification of Internet Video Traffic Using Byte Code Distribution Featuresately. To test the performance of our proposal, we collect a set of video traffic traces containing two typical video types, romance and action. We conduct a set of comparing experiments on the collected data. The results show that the BCD method can hit extremely high identification accuracies (hig
55#
發(fā)表于 2025-3-31 01:21:54 | 只看該作者
RISC: Risk Assessment of Instance Selection in Cloud Marketsch to fine-tuning the instance recommendation. We have evaluated our approach using simulations on real-world workloads and cloud market statistics. The results show that, compared to traditional approaches, our approach provides the best tradeoff between SLOs and costs, as it can maximize the overa
56#
發(fā)表于 2025-3-31 07:05:02 | 只看該作者
Real-Time Data Stream Partitioning over a Sliding Window in Real-Time Spatial Big Dataformance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach over a sliding window in real-time spatial Big Data name
57#
發(fā)表于 2025-3-31 09:55:48 | 只看該作者
58#
發(fā)表于 2025-3-31 16:34:59 | 只看該作者
59#
發(fā)表于 2025-3-31 18:03:38 | 只看該作者
Most Memory Efficient Distributed Super Points Detection on Core Networkson a common GPU to accelerate processing speed. Experiments on several real-world core network traffics show that our algorithm acquires the highest accuracy with only consuming littler than one-fifth memory of other algorithms.
60#
發(fā)表于 2025-4-1 01:26:47 | 只看該作者
Parallel Implementation and Optimizations of Visibility Computing of 3D Scene on Tianhe-2 Supercomputechnique called hemispheric visibility computing is designed, which can overcome the visibility missing of traditional perspective algorithm. Secondly, a distributed parallel algorithm for visibility computing is implemented, which is based on the master-worker architecture. Finally, we discuss the
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