Globally Scheduled Real-Time Multiprocessor Systems with GPUs

Glenn A. Elliott (1) , James H. Anderson (1)

1 Department of Computer Science [Chapel Hill]

Graphics processing units, GPUs, are powerful processors that can offer significant performance advantages over traditional CPUs. The last decade has seen rapid advancement in GPU computational power and generality. Recent technologies make it possible to use GPUs as co-processors to the CPU. The performance advantages of GPUs can be great, often outperforming traditional CPUs by orders of magnitude. While the motivations for developing systems with GPUs are clear, little research in the real-time systems field has been done to integrate GPUs into real-time multiprocessor systems. We present two real-time analysis methods, addressing real-world platform constraints, for such an integration into a soft real-time multiprocessor system and show that a GPU can be exploited to achieve greater levels of total system performance.

Domaines: Systèmes embarqués

Glenn A. Elliott, James H. Anderson. Globally Scheduled Real-Time Multiprocessor Systems with GPUs. 18th International Conference on Real-Time and Network Systems, Nov 2010, Toulouse, France. pp.197-206. ⟨hal-00546957⟩