Key points are not available for this paper at this time.
In this paper, we address the problem of efficiently managing the relative power demands of a high-performance GPU and its memory subsystem. We develop a management approach that dynamically tunes the hardware operating configurations to maintain balance between the power dissipated in compute versus memory access across GPGPU application phases. Our goal is to reduce power with minimal performance degradation.
Paul et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: