MapReduce Implementation of Prestack Kirchhoff Time Migration (PKTM) on Seismic Data

The oil and gas industries have been great consumers of parallel and distributed computing systems, by frequently running technical applications with intensive processing of terabytes of data. By the emergence of cloud computing which gives the opportunity to hire high-throughput computing resources with lower operational costs, such industries have started to adopt their technical applications to be executed on such high-performance commodity systems. In this paper, we first give an overview of forward/inverse Prestack Kirchhoff Time Migration (PKTM) algorithm, as one of the well-known seismic imaging algorithms. Then we will explain our proposed approach to fit this algorithm for running on Google's MapReduce framework. Toward the end, we will analyse the relation between MapReduce-based PKTM completion time and the number of mappers/reducers on pseudo-distributed MapReduce mode

SHYAM: A system for autonomic management of virtual clusters in hybrid clouds

none2noWhile the public cloud model has been vastly explored over the last few years to face the demand for large-scale distributed computing capabilities, many organizations are now focusing on the hybrid cloud model, where the classic scenario is enriched with a private (company owned) cloud – e.g., for the management of sensible data. In this work, we propose SHYAM, a software layer for the autonomic deployment and configuration of virtual clusters on a hybrid cloud. This system can be used to face the temporary (or permanent) lack of computational resources on the private cloud, allowing cloud bursting in the context of big data applications. We firstly provide an empirical evaluation of the overhead introduced by SHYAM provisioning mechanism. Then we show that, although the execution time is significantly influenced by the intercloud bandwidth, an autonomic off-premise provisioning mechanism can significantly improve the application performance.openLoreti, Daniela; Ciampolini, AnnaLoreti, Daniela; Ciampolini, Ann