Entropy-based Thermal Sensor Allocation for Temperature-aware Multi-core Platforms

Because of the high design complexity in multicore systems, contemporary multi-core systems usually suffer from serious thermal issues caused by the large variety of workloads. To monitor the heat phenomenon, the cost-efficient way is to allocate number-limited thermal sensors on the multicore system. Consequently, a lot of methods were proposed to find proper locations for thermal sensors allocation in the recent decade. However, due to the time-varying characteristic of the temperature behavior on the multi-core system, the temperature distribution usually changes along with time. Besides, the temperature distribution also depends on the target application on the multi-core system, which increases the difficulty to find the proper locations for the thermal sensor allocation. The improper locations for the thermal error while using the sensing information from the allocated error while using the sensing information from the allocated art, we propose an entropy-based thermal sensor allocation method, which aims to find locations to cover as many different temperature behaviors on the system as possible. In this way, we can apply the Restricted Isometry Property (RIP) to reconstruct the full-chip temperature distribution efficiently based on the number-limited thermal sensing information. Compared with the previous thermal sensor allocation methods, we can reduce the average full-chip temperature reconstruction error by 3% to 93%. In addition, the maximum error can be reduced by 3% to 96% as well.