Seismic Noise Correlation on Heterogeneous Supercomputers

We present a high-performance tool for the computation of ambient seismic noise correlations on central processing unit (CPU) and graphic processing unit (GPU) clusters. This is intended to address emerging challenges in noise correlation studies with increasingly large data volumes. We propose a parallelization scheme and strategies to efficiently harness modern supercomputing resources, and we demonstrate that the use of GPUs can accelerate the computation of noise correlations by one order of magnitude or more compared with a homogeneous implementation on CPUs. In addition to reducing wall-clock time, our tool enables on-the-fly computations of large noise correlation datasets, thereby eliminating the need for mass storage to archive results.