A Graphical Processing Unit (GPU) is a computer chip that renders graphics and images by performing rapid mathematical calculations. In recent years, however, GPUs are exploited for reasons beyond graphics processing as General-Purpose GPU (GPGPU); they work as hardware accelerators for high-performance computing in many different fields, including safety-critical applications. In these domains Convolutional Neural Network (CNN) represent a widely used computing approach which is well supported by GPU since they leverage data and thread-level parallelism. Considering this information, the reliability evaluation of GPUs is needed to meet desired requirements. To achieve this objective, it is necessary to study the GPU behavior in presence of hardware faults.