Face recognition is important in many applications including surveillance, biometrics, and other domains and fast face recognition is required if she wants to train and test more images or to increase the resolution of an input image for better accuracy in recognition. Meanwhile, Graphics Processing Units (GPUs) have become widely available, offering the opportunity for real-time face recognition even for larger set of images with high resolution. In this paper, we explore the design space of parallelizing a PCA (Principal Components Analysis) based face recognition algorithm and propose a fast face recognizer on GPUs by exploiting the fine-grained data-parallelism found in the face recognition algorithm. Our best results with the CUDA face recognizer show over 40-fold speedups compared to a sequential C implementation.