Titlebook: Supercomputing; 6th Russian Supercom Vladimir Voevodin,Sergey Sobolev Conference proceedings 2020 Springer Nature Switzerland AG 2020 cloud

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書目名稱Supercomputing影響因子(影響力)




書目名稱Supercomputing影響因子(影響力)學(xué)科排名




書目名稱Supercomputing網(wǎng)絡(luò)公開度




書目名稱Supercomputing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Supercomputing被引頻次




書目名稱Supercomputing被引頻次學(xué)科排名




書目名稱Supercomputing年度引用




書目名稱Supercomputing年度引用學(xué)科排名




書目名稱Supercomputing讀者反饋




書目名稱Supercomputing讀者反饋學(xué)科排名

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Parallel Box-Counting Method for Evaluating the Fractal Dimension of Analytically Defined Curvesgments with a billion boxes (box size is .). The graphs depicting an increase in acceleration of parallel code performance with decreasing the box size and increasing the number of curve segments are shown. It is concluded that the efficiency of using the GPU begins with three million boxes and grow

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alyze the evaluation performance using various metrics such as accuracy, loss, and f1 score. The proposed work recorded 100, 90, and 88.23% accuracy for training, validation, and test sets, respectively. The f1 score for the test set is estimated at 87.78% with a 0.50 logloss score.

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