abstract: Heterogeneous multiprocessor systems-on-chip (MPSoCs) powering mobile platforms integrate multiple asymmetric CPU cores, a GPU, and many specialized processors. When the MPSoC operates close to its peak performance, power dissipation easily increases the temperature, hence adversely impacts reliability. Since using a fan is not a viable solution for hand-held devices, there is a strong need for dynamic thermal and power management (DTPM) algorithms that can regulate temperature with minimal performance impact. This abstract presents a DTPM algorithm based on a practical temperature prediction methodology using system identification. The DTPM algorithm dynamically computes a power budget using the predicted temperature, and controls the types and number of active processors as well as their frequencies. Experiments on an octa-core big.LITTLE processor and common Android apps demonstrate that the proposed technique predicts temperature within 3% accuracy, while the DTPM algorithm provides around 6x reduction in temperature variance, and as large as 16% reduction in total platform power compared to using a fan. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015
| Identifer | oai:union.ndltd.org:asu.edu/item:29665 |
| Date | January 2015 |
| Contributors | Singla, Gaurav Rattan (Author), Ogras, Umit Y (Advisor), Bakkaloglu, Bertan (Committee member), Unver, Ali (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 53 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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