Cloud computing is enabling users to instantiate and access high-performance computing clusters quickly. However, without proper knowledge of the type of application and the nature of the instances, it can become quite expensive. Our objective is to indicate that adequately choosing the instances provides a fast execution, which, in turn, leads to a low execution price, using the pay-as-you-go model on cloud computing. We have used graphics processing unit instances on the spot market to execute a seismic-data set interpolation job and compared their performance with regular on-demand central processing unit (CPU) instances. Furthermore, we explored how scaling could also improve the execution times at small price differences. The experiments have shown that, by using an instance with eight accelerators on the spot market, we obtain up to a 300 times speed-up compared with the on-demand CPU options, while being 100 times cheaper. Finally, our results have shown that seismic-imaging processing can be sped up by an order of magnitude with a low budget, resulting in faster and cheaper processing turnaround time and enabling new possible imaging techniques.