| Popis: |
Electromagnetic imaging has been perfected to investigate the subsurface over the past three decades. Developing numerical schemes, algorithms, and easy access to supercomputers have supported innovation throughout the geo-electromagnetic community. Now, with the Exascale computing era dawning upon us, even more accurate, clearer, and faster data will be within our reach. However, numerical methods, computational strategies, and codes must be reshaped and honed to prepare for the upcoming challenges. Europe is making a huge effort in the strategic global race to Exascale, with large investments in the infrastructure. From the point of view of science and services, this unprecedented infrastructure opens a myriad of possibilities but, at the same time, the transition is challenging and requires a joint effort from (geo)scientists, mathematics, software engineers, and data analysts. Herein, we discuss the symbiotic relationship between numerical methods and computational strategies for EM imaging in the Exascale era. We focus on the need to explore all the alternatives of technologies, applications, and expertise transfer to propel the high-performance electromagnetic mapping landscape forward. |
