Shallow water waves on a deep technology stack: Accelerating a finite volume tsunami model using reconfigurable hardware in invasive computing

Abstract

Reconfigurable architectures are commonly used in the embedded systems domain to speed up compute-intensive tasks. They combine a reconfigurable fabric with a general-purpose microprocessor to accelerate compute-intensive tasks on the fabric while the general-purpose CPU is used for the rest of the workload. Through the use of invasive computing, we aim to show the feasibility of this technology for HPC scenarios. We demonstrate this by accelerating a proxy application for the simulation of shallow water waves using the i-Core, a reconfigurable processor that is part of the invasive computing multiprocessor system-on-chip. Using a floating-point custom instruction, the entire computation of numerical fluxes occurring in the application’s finite volume scheme is performed by hardware accelerators.