Logic Simulation is widely used to verify the logical correctness of hardware designs. In this work, we present the implementation of a generic graphics processor based logic simulator and compare it with the corresponding CPU (desktop) based implementation. The motivation for this study arises from the increasing computational power of graphics processors (GPUs). Graphics hardware performance is approximately doubling every six months, and they are out-pacing CPUs in raw computational power. GPUs are becoming increasingly programmable and their prices are falling steeply. Most desktops now come built-in with programmable graphics processors. The highly parallel nature of graphics computations enables GPUs to use additional transistors for computation, achieving higher arithmetic intensity with the same transistor count. Applications such as Ray Tracing, Fluid Modeling, Radiology imaging etc have shown speed-ups on graphics processors. This led us to investigate the use of GPUs to run concurrent algorithms for logic simulation. We present the implementation and analyze performance bottlenecks and finally draw conclusions as to whether the GPU can be used for speeding up the logic simulation algorithm.