Euro-Par 2015: Parallel Processing de Jesper Larsson Träff

Euro-Par 2015: Parallel Processing

Jesper Larsson Träff

Sascha Hunold

Francesco Versaci

This book constitutes the refereed proceedings of the 21st International Conference on Parallel and Distributed Computing, Euro-Par 2015, held in Vienna, Austria, in August 2015. The 51 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 190 submissions. The papers are organized in the following topical sections: support tools and environments; performance modeling, prediction and evaluation; scheduling and load balancing; architecture and compilers; parallel and distributed data management; grid, cluster and cloud computing; distributed systems and algorithms; parallel and distributed programming, interfaces and languages; multi- and many-core programming; theory and algorithms for parallel computation; numerical methods and applications; and accelerator computing.

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Cuprins

Concurrent Systems: Hybrid Object Implementations and Abortable Objects.- Runtime-Aware Architectures.- MPI Thread-Level Checking for MPI+OpenMP Applications.- Event-Action Mappings for Parallel Tools Infrastructures.- Low-Overhead Detection of Memory Access Patterns and Their Time Evolution.- Automatic On-line Detection of MPI Application Structure with Event Flow Graphs.- Online Automated Reliability Classification of Queueing Models for Streaming Processing Using Support Vector Machines.- A Duplicate-Free State-Space Model for Optimal Task Scheduling.- On the Heterogeneity Bias of Cost Matrices when Assessing Scheduling Algorithms.- Hardware Round-Robin Scheduler for Single-ISA Asymmetric Multi-Core.- Moody Scheduling for Speculative Parallelization.- Allocating Jobs with Periodic Demands.- A Multi–Level Hypergraph Partitioning Algorithm Using Rough Set Clustering.- Non-preemptive Throughput Maximization for Speed-Scaling with Power-Down.- Scheduling Tasks from Selfish Multi-tasks Agents.- Locality and Balance for Communication-Aware Thread Mapping in Multicore Systems.- Concurrent Priority Queues Are not Good Priority Schedulers.- Load Balancing Prioritized Tasks via Work-Stealing.- Optimizing Task Parallelism with Library-Semantics-Aware Compilation.- Data Layout Optimization for Portable Performance.- Automatic Data Layout Optimizations for GPUs.- Performance Impacts with Reliable Parallel File Systems at Exascale Level.- Rapid Tomographic Image Reconstruction via Large-Scale Parallelization.- Software consolidation as an efficient energy and cost Saving Solution for a SaaS/PaaS Cloud Model.- VMPlaceS A Generic Tool to Investigate and Compare VM Placement Algorithms.- A Connectivity Model for Agreement in Dynamic Systems.- DFEP: Distributed Funding-based Edge Partitioning.- PR-STM: Priority Rule Based Software Transactions on the GPU.- Leveraging MPI-3 Shared-Memory Extensions for Efficient PGAS Runtime Systems.- A Practical Transactional Memory Interface.- AMulticore Parallelization of Continuous Skyline Queries on Data Streams.- A Fast and Scalable Graph Coloring Algorithm for Multi-core and Many-core Architectures.- A Composable Deadlock-Free Approach to Object-Based Isolation.- Scalable Data-Driven PageRank: Algorithms, System Issues & Lessons Learned.- How Many Threads Will Be Too Many? On the Scalability of OpenMP Implementations.- Efficient Nested Dissection for Multicore Architectures.- Scheduling Trees of Malleable Tasks for Sparse Linear Algebra.- Elastic Tasks: Unifying Task Parallelism and SPMD Parallelism with an Adaptive Runtime.- Semi-discrete Matrix-Free Formulation of 3D Elastic Full Waveform Inversion Modeling.- 10,000 Performance Models per Minute - Scalability of the UG4 Simulation Framework.- Exploiting Task-Based Parallelism in Bayesian Uncertainty Quantification.- Parallelization of an Advection-Diffusion Problem Arising in Edge Plasma Physics Using Hybrid MPI/OpenMP Programming.- Behavioral Non-Portability in Scientific Numeric Computing.- Fast Parallel Suffix Array on the GPU.- Effective Barrier Synchronization on Intel Xeon Phi Coprocessor.- High Performance Multi-GPU SpMV for Multi-component PDE-based Applications.- Accelerating Lattice Boltzmann Applications with OpenACC.- High-Performance and Scalable Design of MPI-3 RMA on Xeon Phi Clusters.- Improving Performance of Convolutional Neural Networks by Separable Filters on GPU.- Iterative Sparse Triangular Solves for Preconditioning.- Targeting the Parallella.- Systematic Fusion of CUDA Kernels for Iterative Sparse Linear System Solvers.- Efficient Execution of Multiple CUDA Applications using Transparent Suspend, Resume and Migration.