  High-fidelity simulations of unsteady fluid flow are now possible with
advancements in high-performance computing hardware and software frameworks.
Since computational fluid dynamics (CFD) computations are dominated by linear
algebraic routines, they can be significantly accelerated through massive
parallelization on graphics processing units (GPUs). Thus, GPU implementation
of high-fidelity CFD solvers is essential in reducing the turnaround time for
quicker design space exploration. In the present work, an immersed boundary
method (IBM) based in-house flow solver has been ported to the GPU using
OpenACC, a compiler directive-based heterogeneous parallel programming
framework. Out of various GPU porting pathways available, OpenACC was chosen
because of its minimum code intrusion, low development time, and striking
similarity with OpenMP, a similar directive-based shared memory programming
framework. A detailed validation study and performance analysis of the parallel
solver implementations on the CPU and GPU are presented. The GPU implementation
shows a speedup up to the order $O(10)$ over the CPU parallel version and up to
the order $O(10^2)$ over the serial code. The GPU implementation also scales
well with increasing mesh size owing to the efficient utilization of the GPU
processor cores.
