Quick_Hotspot: A Software Supported Methodology for Supporting Run-Time Thermal Analysis at MPSoC Designs

Detailed thermal analysis and exploration has recently received significant attention since it is straightforwardrelated to numerous reliability issues. Furthermore, thermal profiling is a critical challenge for supporting efficient power management, especially to multi-processor system-on-chips (MPSoCs). This problem becomes even more important if we take into account the computational complexity of existing thermal profiling and analysis approaches. Among others this limitation imposes that thermal analysis is performed solely at design time. However, such a static exploration does not take into account constraints posed during application execution that lead to temperature variations. Hence, new algorithms and software tools able to provide accurate yet fast thermal analysis are upmost required. In this paper, we introduce a new software supported methodology for performing thermal analysis at run-time with different levels of granularity. Additional performance improvement is feasible by applying thermal analysis only to device regions with blocks that operate under high power densities. For demonstration purposes we show how this methodology is applied to an Altera Stratix-based FPGA device. Experimental results prove the efficiency of the proposed methodology, since the average execution time ranges between 41% and 78%, as compared to state of the art relevant solution, without any accuracy degradation at the derived thermal profile.