Abstarct: The heat transfer enhancement and type of heat transfer fluid has been the subject of much industrial and engineering research in recent decades. Changing the thermophysical properties of the fluid (such as adding nanoparticles to the baxse fluid) and the flow geometry (such as channels with corrugated walls) are two common ways to improve the heat transfer rate. Therefore, the present study investigates the flow and the subject of nanofluid heat transfer inside the channel with a corrugated wall. The governing equations for solving the nanofluid flow include mass conservation equation, momentum conservation and energy conservation which are discretizated by the Spline Alternating Direction Implicit (SADI) method. The discretization of the governing equations lead to Tri-Diagonal system of equation. The rapid resolution of this equation is a challenging issue in Computational Fluid Dynamics (CFD) that uses the GPU to solve it. The GPU architecture is structured so that it can execute a computational instruction on a large amount of data in a short period of time in parallel. The results demonstrated an increase in heat transfer due to the increase of the amplitude–wavelength, Reynolds number, Prandtl number and nanofluid volume fraction. Also, the maximum speed up of parallel Thomas algorithm against CPU runtime was about 7.69x in a 1600×160 grid size.