  The electron-phonon Wannier interpolation (EPWI) method is an efficient way
to compute the properties of electron-phonon interactions (EPIs) accurately.
This study presents a GPU-accelerated implementation of the EPWI method for
computing transport properties, followed by a performance analysis. The
implementation is tested on common systems such as aluminum and silicon. The
results show complete consistency with those obtained through CPU computations.
The proposed algorithm has the capability of computing the conductivity of
aluminum in 20 minutes on a single NVIDIA Tesla V100 GPU, adopting a $200^3$
electron and phonon sampling grid. This speed is 173 times higher than the
CPU-based algorithm, running on two nodes of the Intel Xeon Platinum 8260 CPU.
Such impressive acceleration is achieved by carefully designing the algorithm
to exploit the GPU's specific features. Furthermore, this methodology
establishes a generic foundation for EPWI algorithms, which can be applied to
other EPI-related properties.
