Titlebook: Algorithms and Architectures for Parallel Processing; 19th International C Sheng Wen,Albert Zomaya,Laurence T. Yang Conference proceedings

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書目名稱Algorithms and Architectures for Parallel Processing影響因子(影響力)




書目名稱Algorithms and Architectures for Parallel Processing影響因子(影響力)學科排名




書目名稱Algorithms and Architectures for Parallel Processing網(wǎng)絡(luò)公開度




書目名稱Algorithms and Architectures for Parallel Processing網(wǎng)絡(luò)公開度學科排名




書目名稱Algorithms and Architectures for Parallel Processing被引頻次




書目名稱Algorithms and Architectures for Parallel Processing被引頻次學科排名




書目名稱Algorithms and Architectures for Parallel Processing年度引用




書目名稱Algorithms and Architectures for Parallel Processing年度引用學科排名




書目名稱Algorithms and Architectures for Parallel Processing讀者反饋




書目名稱Algorithms and Architectures for Parallel Processing讀者反饋學科排名

戲法

Improving the Parallelism of CESM on GPUually lasts for weeks even on high-performance clusters. In this paper, we propose several optimization strategies to improve the parallelism of three hotspots in CESM on GPU. Specifically, we analyze the performance bottleneck of CESM and propose corresponding GPU accelerations. The experiment resu

符合國情

Parallel Approach to Sliding Window Sumsdvanced vector extension (AVX) instructions available on modern processors, or the parallel compute units on GPUs and FPGAs, would provide a significant performance boost..We develop a generic vectorized sliding sum algorithm with speedup for window size . and number of processors . is .(./.) for a

提升

Rise the Momentum: A Method for Reducing the Training Error on Multiple GPUsescent or its variants. Distributed training increases training speed significantly but causes precision loss at the mean time. Increasing batchsize can improve training parallelism in distributed training. However, if the batchsize is too large, it will bring difficulty to training process and intr

盡忠

放縱

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太空

A Comparison Study of VAE and GAN for Software Fault Predictioning. In recent years, deep learning has been widely used in the fields of image, text and voice. However it is seldom applied in the field of software fault prediction. Considering the ability of deep learning, we select the deep learning techniques of VAE and GAN for software fault prediction and c

單挑

A Framework for Designing Autonomous Parallel Data Warehousesa . on such platforms requires efficient data partitioning and allocation techniques. Most of these techniques assume a priori knowledge of workload. To deal with their evolution, . are mainly used. The BI 2.0 requirements have put .. Consequently, reactive-based solutions for deploying a . in paral

abysmal