Hybrid dynamic thermal management based on statistical characteristics of multimedia applications

Recently multimedia applications become one of the most popular applications in mobile devices such as wireless phones, PDAs, and laptops. However, typical mobile systems are not equipped with cooling components, which eventually causes critical thermal deficiencies. Although many low-power and low-temperature multimedia playback techniques have been proposed, they failed to provide QoS (Quality of Service) while controlling temperature due to the lack of proper understanding of multimedia applications. We propose Hybrid Dynamic Thermal Management (HDTM) which exploits thermal characteristics of both multimedia applications and systems. Specifically, we model application characteristics as the probability distribution of the number of cycles required to decode a frame. We also improve existing system thermal models by considering the effect of work-load. This scheme finds an optimal clock frequency in order to prevent overheating with minimal performance degradation at runtime. The proposed scheme is implemented on Linux in a Pentium-M processor which provides variable clock frequencies. In order to evaluate the performance of the proposed scheme, we exploit three major codecs, namely MPEG-4, H.264/AVC and H.264/AVC streaming. Our results show that HDTM lowers the overall temperature by 15°C and the peak temperature by 20°C , while maintaining frame drop ratio under 0.2% compared to previous thermal management schemes such as feedback control DTM, Frame-based DTM and GOP-based DTM.