Abstract
Radio signal strength estimation is essential in many applications, including the design of military radio communications and industrial wireless installations. While classical approaches such as finite difference methods are well-known, new event-based models of radio signal propagation have been recently shown to deliver such estimates faster (via serial execution) than other methods. For scenarios with large or richly-featured geographical volumes, however, parallel processing is required to meet the memory
and computation time demands. Here, we present a scalable and efficient parallel execution of a recently-developed event-based radio signal propagation model. We demonstrate its scalability to thousands of processors, with parallel speedups over 1000x. The speed and scale achieved by our parallel execution enable larger scenarios and faster execution than has ever been reported before.
