Abstract：As seismic exploration data amount is greatly increasing and new algorithms with a large amount of calculations are adopted, more and more massively parallel computing and heterogeneous collaborative computing are used for seismic data processing. However computing resources at large data centers are often improperly scheduled and lead a low equipment utilization rate. We discuss in this article the system structure, the data management, the scheduling algorithm, and the pluggable resource monitoring of GeoEast large-scale cluster job scheduling and resource management system. Based on the unified node management and real-time monitoring, not only large-scale operations are concurrently running, but also the massive job scheduling and the workload are balanced under the network environment. So seismic jobs are running in the best resource environment, both the computing-resource utilization efficiency and seismic data processing efficiency are improved.
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Luo Gang, Chen Jihong, Sun Xiaoping, Zhou Kun, Du Jiguo. Heterogeneous cluster scheduling and resource mana-gement system for a large number of seismic data processing jobs. Oil Geophysical Prospecting, 2017, 52(s2): 200-205.
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