GPU (Graphics Processing Unit) is emerging as a key 3D/2D graphics and parallel workload accelerator in various SoC applications. As semiconductor fabrication technology continues to scale, chips (especially those with extremely high transistor counts such as processors) are becoming increasingly vulnerable to faults that could produce unwanted errors in computing. The most severe problem is Silent Data Corruption (SDC) because this fault insidiously generates erroneous outputs without being detected. This paper discusses the characterization of SDC vulnerability of GPU on various GPGPU (General Purpose computing on GPU) workloads.