Titlebook: High Performance Computing; 32nd International C Julian M. Kunkel,Rio Yokota,David Keyes Conference proceedings 2017 Springer International

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EvoGraph: On-the-Fly Efficient Mining of Evolving Graphs on GPUhs. Modern GPUs provide massive amount of parallelism for efficient graph processing, but the challenges remain due to their lack of support for the near real-time streaming nature of dynamic graphs. Specifically, due to the current high volume and velocity of graph data combined with the complexity

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High-Performance Incremental SVM Learning on Intel, Xeon Phi™ Processorsing real-time guarantees, as the inclusion of each new data point requires retraining of the model from scratch. This paper focuses on the high-performance implementation of an accurate incremental SVM algorithm on Intel. Xeon Phi. processors that efficiently updates the trained SVM model with strea

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Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processormmunity software package simulating seismic wave propagation using a staggered finite difference scheme which is fourth order accurate in space and second order in time. Recent production simulations, e.g. using the software for the computation of seismic hazard maps, largely relied on GPU accelerat

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gearshifft – The FFT Benchmark Suite for Heterogeneous Platformsising data production bandwidths of modern FFT applications, judging best which algorithmic tool to apply, can be vital to any scientific endeavor. As tailored FFT implementations exist for an ever increasing variety of high performance computer hardware, choosing the best performing FFT implementat

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Extreme Event Analysis in Next Generation Simulation Architecturestrate a seamless integration of feature extraction for a simulation of turbulent fluid dynamics. The simulation produces on the order of 6 TB per timestep. In order to analyze and store this data, we extract velocity data from a dilated volume of the strong vortical regions and also store a lossy co