Euro-Par 2020: Parallel Processing

Support Tools and Environments.- Skipping Non-essential Instructions Makes Data-dependence Profiling Faster.- A Toolchain to Verify the Parallelization of OmpSs-2 Applications.- Performance and Power Modeling, Prediction and Evaluation.- Towards a Model to Estimate the Reliability of Large-scale Hybrid Supercomputers.- A Learning-Based Approach for Evaluating the Capacity of Data Processing Pipelines.- Operation-Aware Power Capping.- A Comparison of the Scalability of OpenMP Implementations.- Evaluating the Effectiveness of a Vector-Length-Agnostic Instruction Set.- Scheduling and Load Balancing.- Parallel Scheduling of Data-Intensive Tasks.- A Makespan Lower Bound for the Scheduling of the Tiled Cholesky Factorization Based on ALAP Scheduling.- Optimal GPU-CPU Offloading Strategies for Deep Neural Network Training.- Improving mapping for sparse direct solvers: A trade-off between data locality and load balancing.- High Performance Architectures and Compilers.- Modelling Standard and Randomized Slimmed Folded Clos Networks.- OmpMemOpti: Optimized Memory Movement for Heterogeneous Computing.- Data Management, Analytics and Machine Learning.- Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs.- Distributed Fine-Grained Traffic Speed Prediction for Large-Scale Transportation Networks based on Automatic LSTM Customization and Sharing.- Optimizing FFT-based convolution on ARMv8 multi-core CPUs.- Maximizing I/O Bandwidth for Reverse Time Migration on Heterogeneous Large-Scale Systems.- Cluster, Cloud and Edge Computing.- TorqueDB: Distributed Querying of Time-series Data from Edge-local Storage.- Data-Centric Distributed Computing on Networks Mobile Devices.- WPSP: a multi-correlated weighted policy for VM selection and migration for Cloud computing.- Theory and Algorithms for Parallel and Distributed Processing.- LCP-Aware Parallel String Sorting.- Mobile RAM and Shape Formation by Programmable