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(R)ect and distinguish the thermal contributions from appli- cations with di(R)erent workload behaviors at run time in the CMP systems. The pro- posed PDTM and TCDTM enable the exploration of the tradeo(R) between throughput and fairness in temperature-constrained multicore systems.
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(R)ect and distinguish the thermal contributions from appli- cations with di(R)erent workload behaviors at run time in the CMP systems. The pro- posed PDTM and TCDTM enable the exploration of the tradeo(R) between throughput and fairness in temperature-constrained multicore systems.
