Recently, processor power density has been increasing at an alarming rate result-
ing in high on-chip temperature. Higher temperature increases current leakage and
causes poor reliability. In our research, we ¯rst propose a Predictive Dynamic Ther-
mal Management (PDTM) based on Application-based Thermal Model (ABTM) and
Core-based Thermal Model (CBTM) in the multicore systems. Based on predicted
temperature from ABTM and CBTM, the proposed PDTM can maintain the system
temperature below a desired level by moving the running application from the possi-
ble overheated core to the future coolest core (migration) and reducing the processor
resources (priority scheduling) within multicore systems. Furthermore, we present the
Thermal Correlative Thermal Management (TCDTM), which incorporates three main
components: Statistical Workload Estimation (SWE), Future Temperature Estima-
tion Model (FTEM) and Temperature-Aware Thread Controller (TATC), to model
the thermal correlation e®ect and distinguish the thermal contributions from appli-
cations with di®erent workload behaviors at run time in the CMP systems. The pro-
posed PDTM and TCDTM enable the exploration of the tradeo® between throughput
and fairness in temperature-constrained multicore systems.
Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2913 |
Date | 15 May 2009 |
Creators | Liu, Chih-Chun |
Contributors | Kim, Eun Jung |
Source Sets | Texas A and M University |
Language | en_US |
Detected Language | English |
Type | Book, Thesis, Electronic Thesis, text |
Format | electronic, application/pdf, born digital |
Page generated in 0.0018 seconds