Kirchhoff prestack time migration on large heterogeneous computing systems
Zhao Changhai1, Luo Guoan2, Zhang Xudong2, Wang Shihu2, Zhang Jianlei2, Wang Chengxiang2
1. Beijing Branch, Research & Development Center, BGP Inc. CNPC, Beijing 100088, China;
2. Research & Development Center, BGP Inc. CNPC, Zhuozhou, Hebei 072751, China
Abstract：The size of seismic data from a single survey for the moment has reach to 100TB, and may exceed 1PB in the near future. To support increasingly huge survey data sizes and processing complexity, we propose a practical approach to large-scale parallel processing of 3D prestack Kirchhoff time migration (PSTM) with multi-dimension imaging space decomposition on heterogeneous computing systems. The parallel algorithm is based on three-level decomposition of the imaging space. Firstly, the imaging space is partitioned by offsets. Each node runs just one process, and all processes are divided into several distinct groups. The imaging work of common-offset space is assigned to a group, and the common-offset input traces are dynamically distributed to the processes of the group. Once all input traces are migrated, the local imaging sections of all the processes in a group are added to form the final common-offset image. In a node, the common-offset imaging section is further partitioned equally by CMP. If the size of a common-offset imaging section exceeds the total physical memory on the compute node, the whole imaging space should be firstly partitioned along in-line direction so that each common-offset imaging space can fit in memory. The algorithm greatly reduces the dependencies among tasks. The task partitions can be easily mapped to multiple heterogeneous processors and execute asynchronously. Compared to the production CPU version of PSTM, its GPU version achieves up to 4.8 speed times and MIC version achieves up to 2 speed times. Comparative analysis of GPU and MIC is also given on power consumption, performance, and programmablity. The PSTM implementation can obtain close to linear speedup when it processes real data on the Tianhe-1 supercomputer.
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