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Titlebook: High Performance Computing; 7th Latin American C Sergio Nesmachnow,Harold Castro,Andrei Tchernykh Conference proceedings 2021 The Editor(s)

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樓主: relapse
31#
發(fā)表于 2025-3-26 23:23:48 | 只看該作者
Félix Armando Mejía Cajicá,John A. García Henao,Carlos Jaime Barrios Hernández,Michel Riveillirradiation, chemical carcinogenic agents, are involved in the development of thyroid cancer. These factors can cause molecular abnormalities of signaling pathways involved in proliferation, differentiation, and apoptosis, which eventually lead to the development and progression of various thyroid n
32#
發(fā)表于 2025-3-27 04:05:38 | 只看該作者
33#
發(fā)表于 2025-3-27 07:08:02 | 只看該作者
34#
發(fā)表于 2025-3-27 11:23:03 | 只看該作者
e. In patients with heart failure the activationof apoptosis may result in the loss of irreplaceable cardiac myocytespromoting the clinical course of the syndrome. Moreover, in thecoronary arteries inflammation and apoptosis may weaken criticalstructures of the vessel wall leading to plaque rupture
35#
發(fā)表于 2025-3-27 17:31:33 | 只看該作者
High Performance Computing Simulations of Granular Media in Silosrder to model realistic situations in reasonable computing times. This article describes the application of a parallel/distributed high performance computing approach for studying the mechanisms that control the charging and discharging process of silos, in which grains pass through a bottleneck. Si
36#
發(fā)表于 2025-3-27 20:37:03 | 只看該作者
Methodology for Design and Implementation an Efficient HPC Clustervides all of those standardized tools in order to spread best practices in building and managing HPC data centers, but unlike Rocks, OpenHPC requires pre-design of the platform, including network infrastructure, storage services, and the different tools to implement, requiring prior knowledge by the
37#
發(fā)表于 2025-3-28 01:39:01 | 只看該作者
38#
發(fā)表于 2025-3-28 02:25:28 | 只看該作者
39#
發(fā)表于 2025-3-28 09:50:23 | 只看該作者
Electricity Demand Forecasting Using Computational Intelligence and High Performance Computinghniques consists in train and evaluate models in parallel with different architectures and sets of parameters using grid search techniques. Furthermore each model is trained using Tensorflow with finite-grained GPU parallelism. Considering the high computing demands of the applied techniques, they a
40#
發(fā)表于 2025-3-28 10:35:27 | 只看該作者
Parallel/Distributed Generative Adversarial Neural Networks for Data Augmentation of COVID-19 Trainioposed model is able to generate accurate images and the . version of the distributed GAN has better robustness properties of its training process, allowing to generate better and more diverse images.
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