Rapid inversion of large airborne AEM data datasets utilizing massively parallel coprocessors

While full 2D and 3D inversion schemes are emerging for airborne TEM datasets, the workhorse of large scale surveying still remains the well established 1D forward formulation. Modern airborne TEM surveys typically span several thousand line kilometers of data, which can be very time consuming to invert even within the framework of 1D forward modeling. Here, we present how we have modified our existing inversion code to offload its 1D forward computations to massively parallel Intel Xeon Phi co-processors. A prerequisite for good performance on this type of next generation technology is for a code to provide not only good parallel scaling, but also make efficient use of vector instructions. The latter is not possible without modification to the established framework of 1D forward modeling and we demonstrate how this problem can be overcome in a straight forward manner. We show how the modified algorithm provides virtually ideal parallel scaling and almost ideal use of vector instructions on both multi-core processors and massively parallel Intel Xeon Phi co-processors. The use of vector instructions alone provide a speedup of almost 8x on the co-processor, allowing for full inversion of several thousand line kilometers of data per hour.