Shape optimization of hotspot targeted micro pin fins for heterogeneous integration applications

Abstract

In the field of high-performance computing (HPC), growing power demands makes Heterogeneous Integration (HI) the future of next-generation computing systems to sustain Moore's law. HI refers to the assembly of different separately-manufactured components onto a single electronic module to enhance functionality and operating characteristics. As a consequence of HI, the next generation of electronic chips have regions of localized hotspots or cores, translating to a region of extremely high temperature if not adequately cooled. The mitigation of hotspots demands advanced thermal management cooling schemes compared to the conventional ones. This study investigates the combination of impingement jet array of liquid water and non-uniform hotspot targeted micro pin fins, printed on chips, as a potential heat transfer augmentation technique. The configuration comprises four 2cm×2cm chips (Total chip area is 16 cm2) with eight hotspots on each. Liquid water is employed as the coolant in the present study. A detailed numerical parametric study and optimization were carried out using a supervised machine learning algorithm. The multi-objective optimization is performed to optimize both the thermal and flow resistances simultaneously. The results from the detailed optimization reveal that optimal fin parameters for the regions of hotspot and background could be significantly different. The optimal pin fin configuration resulted in a minimum thermal resistance of 0.208 K.cm2/W (0.013K/W) at a constrained pressure drop of about 10 kPa.