Over the last couple of years, it has become more difficult to assess which hardware can deliver the most cost-optimal solution for demanding imaging tasks. The days of faster and faster CPUs are over. A clear choice of hardware has been replaced with many core technologies, and a proliferation of alternatives. In particular, accelerators like GPGPU and field programmable gate arrays (FPGAs) have emerged as strong contenders for the title of hardware platform of choice. With the radical differences in hardware architectures, it has also become more and more difficult to evaluate which platform is optimal for the application in question. An apples-to-apples comparison is no longer possible. Through the example of reverse time migration (RTM), we demonstrate that only through a careful optimization for each platform, with the involvement of hardware, computer-science and algorithmic scientists, can we come up with a reasonable assessment of the alternatives available today.