The HotGauge framework is publicly available on GitHub and archived on Zenodo.


On-chip thermal hotspots are becoming one of the primary design concerns for next generation processors. Industry chip design trends coupled with post-Dennard power density has led to a stark increase in localized and application-dependent hotspots. These “advanced” hotspots cause a variety of adverse effects if untreated, ranging from dramatic performance loss, incorrect circuit operation, and reduced device lifespan. In the past, hotspots could be addressed with physical cooling systems and EDA tools; however, the severity of advanced hotspots is prohibitively high for conventional thermal regulation techniques alone. Fine-grained, architecture-level techniques are needed. To develop these new techniques, the architecture community needs the modern methods and metrics for simulating and characterizing advanced hotspots.

This work presents a novel hotspot characterization methodology for modern and next generation processors which we have coined, HotGauge. HotGauge includes new methods and metrics to enable architects to build hotspot mitigation techniques of the future. To demonstrate the utility ofHotGauge, we present a case study in which we characterize the hotspot behavior in a modern 7nm high-performance client CPU. We observe an average Time-until-hotspot (TUH) that is 2×shorter in its 14nm cousin for a variety of SPEC2006 benchmarks, and we observe TUH varies by up to 2 orders of magnitude between different benchmarks.The first hotspot arises after only 0.2 ms. We then use HotGauge to compare hotspot severity across different floorplans, and we observe that floorplanning-based hotspot mitigation techniques like area scaling are inadequate. Upon publication of this work, we will release HotGauge along with all models used in the case study in this work to be used by the broader community.


Alexander Hankin (Tufts University), David Werner (Tufts University), Julien Sebot (Intel), Kaushik Vaidyanathan (Google), Maziar Amiraski (Tufts University), Mark Hempstead (Tufts University). HotGauge: A Methodology for Characterizing Advanced Hotspots in Modern and Next Generation Processors. The 2021 IEEE International Symposium on Workload Characterization (IISWC), November 2021.