Research On Parallel Efficiency Of PC Cluster For Seismic Data Processing

Petroleum seismic data processing needs mass storage and computing, which has been an important application field of high performance computing. Linux-based cluster system has obvious advantages at the cost performance, reliability and scalability and has become the mainstream platform for seismic data processing. It can make full use of existing hardware and software resources to research the parallel efficiency of PC cluster for seismic data processing. It can not only improve the overall efficiency of seismic data processing cluster, but also improve the geological effects and economic benefits. Therefore, the issue has important practical significance.This paper analyzes the characteristics of seismic data processing system to identify the key factors that affect the parallel efficiency of PC cluster for seismic data processing,which are I/O bottleneck and serial programs'low operating efficiency in parallel environment. In order to solve the above problems, this paper conducts research in two areas: parallel file system and parallel programming.Firstly, a PC cluster is built using ordinary PC and MPI. We analyze the key factors that affect cluster performance through LINPACK benchmark and provide relevant suggestions.In order to solve the increasingly serious I/O bottleneck problem of seismic data processing cluster, we install Lustre parallel file system into the test cluster and make a comparison test between NFS and Lustre using iozone. The results show that Lustre can better meet the concurrent I/O requirements and effectively alleviate the I/O bottleneck. In order to improve the security of Lustre, this paper designs a Lustre security model based on PKI.The core algorithms of seismic data processing are FFT and matrix multiplication. We parallelize them using MPI, OpenMP and CUDA, and make a comparison in execute time between the parallel programs and related serial programs. Test results show that it can significantly reduce the run cycle by parallelizing the computing-intensive algorithms.We apply Lustre parallel file system and parallel programming techniques to real seismic data processing system. The real seismic data processing tests show that Lustre and parallel programming techniques can significantly reduce the seismic data processing cycle and improve the efficiency of procedures. In addition, this paper also investigates the effects of the compilers, runtime environment, math libraries and other factors on program efficiency and obtains some meaningful conclusions. Finally, several suggestions are given on further improve the parallel efficiency.