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[null,null,"Titolo",null,"High performance computing : 8th Latin American conference, CARLA 2021, Guadalajara, Mexico, October 6-8, 2021, revised selected papers / / edited by Isidoro Gitler, Carlos Jaime Barrios Hernández and Esteban Meneses"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-04209-3"]
[null,null,"Descrizione fisica",null,"1 online resource (273 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science ; ; v.1540"]
[null,null,"Disciplina",null,"004.11"]
[null,null,"Soggetti",null,"High performance computing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- High Performance Computing -- TEPUI: High-Performance Computing Infrastructure for Beamlines at LNLS/Sirius -- 1 Introduction -- 2 Cluster Subsystems -- 2.1 High-Performance Computing -- 2.2 Storage -- 3 System Access -- 3.1 Scheduling System -- 4 Monitoring System -- 4.1 Infrastructure -- 5 Conclusion -- References -- Energy Consumption Studies of WRF Executions with the LIMITLESS Monitor -- 1 Introduction -- 2 WRF: The Standard for Weather Simulations -- 3 The LIMITLESS Monitor -- 4 Methodology -- 5 Results -- 6 Conclusions and Future Work -- References -- Improving Performance of Long Short-Term Memory Networks for Sentiment Analysis Using Multicore and GPU Architectures -- 1 Introduction -- 2 Related Work -- 3 Implementation -- 3.1 Technical Specifications -- 3.2 Training Data Pre-processing -- 3.3 Model and Training -- 4 Results -- 4.1 Accuracy of the Sentiment Analysis Model -- 4.2 Performance Improvements -- 4.3 Proposal Validation -- 5 Conclusion and Future Works -- References -- A Methodology for Evaluating the Energy Efficiency of Post-Moore Architectures -- 1 Introduction -- 2 State of the Art -- 3 ACDC Methodology Outline -- 3.1 Description of the ACDC Methodology -- 3.2 Case Study: Implementation of the ACDC Methodology -- 4 Conclusions -- References -- Understanding COVID-19 Epidemic in Costa Rica Through Network-Based Modeling -- 1 Introduction -- 2 Background -- 2.1 Epidemic Model Simulation -- 2.2 Corona++ Simulation Framework -- 2.3 Related Work -- 3 Modeling -- 3.1 "]
[{"$nulls":4},"Characterization -- 3.2 Calibration and Scenario Setup -- 4 Results -- 4.1 Experimental Setup -- 4.2 Validation -- 4.3 Evaluation of Scenarios -- 5 Conclusions and Further Work -- References -- An Efficient Vectorized Auction Algorithm for Many-Core and Multicore Architectures -- 1 Introduction -- 2 Related Work."]
[{"$nulls":4},"3 Auction Algorithm -- 4 Vectorization of the Auction Algorithm for Multicore and Many-Core Architecture -- 4.1 Vectorization of the bid Phase -- 4.2 Vectorization of the assign Phase -- 5 Parallelization of the Auction Algorithm -- 6 Experimental Analysis -- 6.1 Experimental Analysis of the Vectorization -- 6.2 Experimental Analysis of the Parallel Vectorization -- 7 Conclusions -- References -- Green Energy HPC Data Centers to Improve Processing Cost Efficiency -- 1 Introduction -- 2 Development -- 3 Results -- 4 Conclusions -- References -- DICE: Generic Data Abstraction for Enhancing the Convergence of HPC and Big Data -- 1 Introduction -- 2 Data Containers -- 2.1 Input Containers -- 2.2 Output Containers -- 2.3 Storage Support for Containers -- 2.4 Interface -- 3 Reduction of I/O Interference -- 4 Evaluation -- 5 Related Work -- 6 Conclusions -- References -- A Comparative Study of Consensus Algorithms for Distributed Systems -- 1 Introduction -- 2 Implementation -- 2.1 Paxos -- 2.2 Raft -- 2.3 Practical Byzantine Fault Tolerance (pBFT) -- 3 Results -- 4 Conclusion -- References -- OCFTL: An MPI Implementation-Independent Fault Tolerance Library for Task-Based Applications -- 1 Introduction -- 2 Background and Motivation -- 2.1 Failure Detection and Propagation -- 2.2 Failure Mitigation -- 3 Related Work -- 4 An Implementation-Independent Fault Tolerance Library - OCFTL -- 4.1 Failure Detection -- 4.2 Handling Failures -- 4.3 Repairing Communicators -- 4.4 Gathering States -- 4.5 MPI Wrappers -- 4.6 Notification Callbacks -- 5 Experimental Results and Discussion -- 5.1 MPI Behavior -- 5.2 Empirical OCFTL Performance Evaluation -- 5.3 Internal Broadcast -- 5.4 Locality Problem -- 5.5 Checkpointing -- 5.6 Limitations -- 5.7 Stand-Alone Use -- 6 Conclusions and Future Work -- References -- Accelerating Smart City Simulations -- 1 Introduction."]
[{"$nulls":4},"2 Related Works -- 3 SimEDaPE: Simulation Estimation by Data Patterns Exploration -- 3.1 Time Series Extraction -- 3.2 Clustering -- 3.3 Estimation -- 4 Low-Level Performance Optimizations -- 4.1 Optimizations -- 5 Experimental Results -- 5.1 SimEDaPE -- 5.2 Low-Level Optimizations -- 6 Conclusions -- References -- High Performance Computing and Artificial Intelligence -- Distributed Artificial Intelligent Model Training and Evaluation -- 1 Introduction -- 2 Implementation Auto Tuning for ML Training -- 2.1 Front End -- 2.2 Back End -- 3 Accelerated Prediction/Inference Implementation -- 4 Results -- 4.1 Manual Adjustment Testing -- 4.2 Hyper-parameter Scopes -- 4.3 Model Variations -- 4.4 Inference Results -- 5 Conclusions -- References -- Large-Scale Distributed Deep Learning: A Study of Mechanisms and Trade-Offs with PyTorch -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Deep Learning Neural Network Models -- 3.2 Deep Learning Frameworks -- 3.3 Distributed Deep Learning Training -- 4 Methodology -- 5 Experimental Results -- 5.1 Scalability Study -- 5.2 Accuracy and Scaling Trade-Off -- 5.3 Mixed-Precision Distributed Training -- 5.4 Adaptive Summation in Distributed Training -- 6 Discussion -- 7 Concluding Remarks -- References -- Wind Prediction Using Deep Learning and High Performance Computing -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 3.1 Time Series Wind Prediction -- 3.2 Convolutional Networks -- 4 Experiment Setup -- 4.1 Data -- 4.2 Experimental Framework -- 4.3 Technical Assessment and HPC "]
[{"$nulls":4},"Requirements -- 4.4 Hyper-parameter Tuning and Optimization -- 5 Experimentation -- 5.1 Multiple Input Multiple Output (MIMO) Approach -- 5.2 Common Parameters in all Architectures -- 5.3 Classic Convolutional Architecture -- 5.4 Separable Convolutional Architecture."]
[{"$nulls":4},"5.5 Adding Skip and Residual Connections to the Models -- 5.6 Multi-head Architectures -- 6 Discussion and Conclusions -- 6.1 MIMO is a Reliable Approach for Deep Networks -- 6.2 Convolutional Networks are Superior to Baselines -- 7 Future Work -- References -- An Analysis of Neural Architecture Search and Hyper Parameter Optimization Methods -- 1 Introduction -- 2 Architecture and Hyper-parameters Optimization Overview -- 3 Optimization Methods -- 3.1 Bayesian Optimization -- 3.2 Population-Based Algorithms -- 3.3 Reinforcement Learning -- 3.4 Multi-objective Optimization -- 4 Occurrence Analysis -- 4.1 Cluster 1: Applications -- 4.2 Cluster 2: Learning -- 4.3 Cluster 3: Multi-objective -- 4.4 Cluster 4 and 5: Optimization Strategies -- 5 Conclusion -- References -- High Performance Computing Applications -- Solving the Heat Transfer Equation by a Finite Difference Method Using Multi-dimensional Arrays in CUDA as in Standard C -- 1 Introduction -- 2 Bidimensional Arrays -- 3 Tridimensional Arrays -- 4 Application to the Non-steady Heat Transport Equation -- 4.1 2D Case -- 4.2 3D Case -- 5 Performance Test -- 6 Conclusions -- References -- High-Throughput of Measure-Preserving Integrators Derived from the Liouville Operator for Molecular Dynamics Simulations on GPUs -- 1 Introduction -- 2 Methodology -- 3 Results -- 3.1 Code Validation -- 3.2 Code Performance -- 4 Discussion -- 5 Conclusions -- References -- An Efficient Parallel Model for Coupled Open-Porous Medium Problem Applied to Grain Drying Processing -- 1 Introduction -- 2 Numerical Simulation of Coupled Open-Porous Medium Problem -- 3 Methodology -- 3.1 The Algorithm -- 3.2 OpenMP Implementation -- 3.3 Experimental Setup -- 4 Experimental Results -- 4.1 Numerical Results -- 4.2 Preliminary Performance Analysis -- 4.3 Performance Evaluation -- 5 Conclusion and Future Works -- References."]
[{"$nulls":4},"Author Index."]