Parallel GPU architecture simulation framework exploiting work allocation unit parallelism

Abstract

GPU computing is at the forefront of high-performance computing, and it has greatly affected current studies on parallel software and hardware design because of its massively parallel architecture. Therefore, numerous studies have focused on the utilization of GPUs in various fields. However, studies of GPU architectures are constrained by the lack of a suitable GPU simulator. Previously proposed GPU simulators do not have sufficient simulation speed for advanced software and architecture studies. In this paper, we propose a new parallel simulation framework and a parallel simulation technique called work-group parallel simulation in order to improve the simulation speed for modern many-core GPUs. The proposed framework divides the GPU architecture into parallel and shared components, and it determines which GPU component can be effectively parallelized and can work correctly in multithreaded simulation. In addition, the work-group parallel simulation technique effectively boosts the performance of parallelized GPU simulation by eliminating the synchronization overhead. Experimental results obtained using a simulator with the proposed framework show that the proposed parallel simulation technique has a speed-up of up to 4.15 as compared to an existing sequential GPU simulator on an 8-core machine providing minimized cycle errors.