Hardware-in-the-loop simulation of Android GPGPU applications

Emerging mobile devices are likely to adopt CPU-GPU heterogeneous architecture where an embedded GPU executes offloaded computations from the CPU as well as rendering tasks. For design space exploration of such a CPU-GPU heterogeneous architecture at the early design stage or for monitoring the dynamic system behavior of a system, it is very desirable to run the same application software on a full system simulation platform without modification. Since simulations will be performed repetitively, compromise should be made between simulation speed and timing accuracy. Since all known GPU simulators are very slow, in this paper, we propose a hardware-in-the-loop (HIL) simulation framework that integrates the CPU simulator with an existent GPU hardware. A novel interfacing mechanism between the CPU simulator and the GPU hardware is devised to guarantee functional correctness. The proposed technique maintains the timing accuracy of computation workload as much as possible with unavoidable penalty on the timing accuracy of CPU-GPU communication overhead. The proposed simulation framework is implemented with a gem5 full-system simulator and various kinds of GPGPU hardware. For a real-life scenario, we ported the Android platform to the proposed simulation framework and ran a face detection application that calls a native function via JNI. The native function can be written in CUDA or OpenCL if it will be offloaded to the GPU, or in Pthreads if it will be run on the CPU. Preliminary experiments show some use cases of the proposed simulation framework for design space exploration and dynamic behavior monitoring.