In DFT calculations, the computational complexity mainly arises from the need to evaluate electron repulsion integrals (ERIs) and exchange-correlation (XC) contributions. The past decades have witnessed the development of hardware and algorithms that enabled routine DFT studies of molecular systems consisting of up to several hundreds of atoms; however, regular DFT and linear response time-dependent DFT calculations of larger systems with some few thousands of atoms remain challenging, especially for multi-chromophoric systems as due to the need to solve for many closely lying excited states. In recent years, along with the rapid development of heterogeneous computing and hardware accelerators such as GPUs, significant progress has been made in enabling DFT calculations on GPUs. These efforts focus on redesigning the algorithms for integral evaluation, XC integration and Fock matrix formation, such that the highly parallel architecture of GPUs can be efficiently utilized. Moreover, use of dynamic precision, automated code generation, evaluation of ERIs with higher angular momenta and time-dependent DFT implementations (within the Tamm-Dancoff approximation) on GPUs have also been reported. The use of GPUs in DFT calculations has therefore been greatly promoted. However, to the best of our knowledge, a GPU implementation of the CPP formulation of linear response theory has not been reported before, yet being particularly well suited for studying spectra of large and complex multi-chromophoric systems.