  The present work describes the development of heterogeneous GPGPU implicit
CFD coupled solvers, encompassing both density- and pressure- based approaches.
In this setup, the assembled linear matrix is offloaded onto multiple GPUs
using specialized external libraries to solve the linear problem efficiently.
These coupled solvers are applied to two industrial test cases representing
common scenarios: the NASA CRM in a transonic regime and the external
aerodynamics study of the DriveAER car. Significant performance enhancements
are evident when compared to their CPU counterparts. Specifically, the NASA CRM
case achieves an overall speedup of more than 4x, while the DriveAER test case
demonstrates improved stability and reduced computational time compared to
segregated solvers. All calculations were carried out utilizing the GPU-based
partition of the davinci-1 supercomputer at the Leonardo Labs, featuring 82
GPU-accelerated nodes.
