Online Thermal Prediction in Different Thermal Phases for Multicore Systems

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

MOHEBBI NAJM ABAD J.; SOLEIMANI A.; Pouyan A.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: TABRIZ JOURNAL OF ELECTRICAL ENGINEERING Year:2019 | Volume:49 | Issue:4 (90) Page(s): 1813-1825

Download Full-Text

Persian Verion

View:

243

Download:

Cites:

Information Journal Paper

Title

Online Thermal Prediction in Different Thermal Phases for Multicore Systems

Author(s)

MOHEBBI NAJM ABAD J. | SOLEIMANI A. | Pouyan A. | Issue Writer Certificate

Keywords

Dynamic thermal managementQ1

thermal predictionQ1

feature selectionQ1

multilayer perceptronQ1

thermal phaseQ1

adaptive resonance theory networkQ1

Abstract

Increasing the number of cores to enhance computing power of processors leads to an increase in temperature for multicore systems. Thermal management is significant challenge in these processors. A proactive Dynamic thermal management uses a thermal model to predict the temperature before processor temperature reaches the threshold. In this paper, some appropriate features for thermal model are read by using system measurement tools. Other features as historical and control features are created using the proposed processes. An online thermal model based on several thermal phase is proposed. For each phase, a neural network is used to forecast temperature. Different thermal phases are identified according to the parameters affecting the processor temperature using the adaptive resonance theory network. For each of the neural networks, the minimum number of proper features is selected based on the mutual information between the features. The proposed thermal model is able to detect new thermal phase at run time. Then, appropriate neural network is created for new phase. The proposed model has been evaluated to predict temperature for different time distances. The results shows the mean absolute error is less than 1 ° C.

Cites

No record.

References

No record.

Cite

APA: Copy

MOHEBBI NAJM ABAD, J., SOLEIMANI, A., & Pouyan, A.. (2019). Online Thermal Prediction in Different Thermal Phases for Multicore Systems. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 49(4 (90) ), 1813-1825. SID. https://sid.ir/paper/386728/en

Vancouver: Copy

MOHEBBI NAJM ABAD J., SOLEIMANI A., Pouyan A.. Online Thermal Prediction in Different Thermal Phases for Multicore Systems. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2019;49(4 (90) ):1813-1825. Available from: https://sid.ir/paper/386728/en

IEEE: Copy

J. MOHEBBI NAJM ABAD, A. SOLEIMANI, and A. Pouyan, “Online Thermal Prediction in Different Thermal Phases for Multicore Systems,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 49, no. 4 (90) , pp. 1813–1825, 2019, [Online]. Available: https://sid.ir/paper/386728/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops