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Titlebook: Parallel and Distributed Computing, Applications and Technologies; 23rd International C Hiroyuki Takizawa,Hong Shen,Ryusuke Egawa Conferenc

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Multi-GPU Scaling of a Conservative Weakly Compressible Solver for Large-Scale Two-Phase Flow Simulationith multi-GPU computation is proposed. Following the principle of consistent transport, the phase-field model and VOF method are coupled with the momentum equation respectively. Combined with the evolving pressure projection method to damp the acoustic wave, this solver aims at a robust and accurate
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Improving the Performance of Lattice Boltzmann Method with Pipelined Algorithm on A Heterogeneous Multi-zone Processorcomputing due to its particulate nature and local dynamics, especially on recent multi-core or many-core platforms. This paper develops a parallel software framework for 3D LBM simulation on a heterogeneous multi-zone processor, MT-3000. An improved pipelined algorithm named . is proposed, which can
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DEEPFAKE CLI: Accelerated Deepfake Detection Using FPGAs day. People consume around one billion hours of video on social media platforms every day, and that’s why it is very important to stop the spread of fake videos as they can be damaging, dangerous, and malicious. There has been a significant improvement in the field of deepfake classification, but d
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An Advantage Actor-Critic Deep Reinforcement Learning Method for Power Management in HPC Systemsthousands of compute nodes that consume huge amount of electrical power even during their idle states. One way to increase the energy efficiency is to apply the backfilling method to the First Come First Serve (FCFS) job scheduler (FCFS+Backfilling). The backfilling method allows jobs that arrive la
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An AutoML Based Algorithm for Performance Prediction in HPC Systemsruct the neural network architecture that provides accurate performance (runtime) predictions by exploring the number of layers and neurons in each layer. Automated machine learning (AutoML) using neural architecture search (NAS) frameworks such as Auto-Keras have been proposed to tune neural networ
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Edge-Gateway Intrusion Detection for Smart Homed to benefit human life. However, due to the increasing number and diversity of smart home devices, they are vulnerable to be attacked that might cause serious security threats and user’s privacy disclosure. In addition, large-scale distributed and heterogeneous sensing devices have different requir
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