Thermal Characterization Methodology and Cooling Performance of Extended Volume Air Cooling (EVAC) Heat Sinks

Abstract

With increased processor cores and performance for CPU/GPU, thermal design power (TDP) of these products are increasing. Traditional air-cooling solutions are sometimes insufficient to cool high density, high powered CPUs. Liquid cooling solutions can support higher power but would drive for significant initial capital investment and may not be the best solution for cooling if total cost of ownership (TCO) is high. Hence advanced air-cooling solutions like Extended Volume Air Cooling (EVAC) heat sinks are more ideal to adopt. These heat sinks use heat pipes or thermosiphon tubes to transfer the heat to regions where more physical volume is available for additional heat exchangers to deliver the best overall performance. With these extra cooling surfaces (outriggers), the thermal performance of the heat sink can be improved.The characterization of EVAC at the component level is much less straightforward than standard heat sinks due to the complexity of air flow distribution among different sections of an EVAC heat sink. This airflow distribution must be understood in order to determine effects by and on the surrounding system. This paper shows two methodologies to characterize EVAC heat sink performance at component level.The first one is to apply a thermal resistance network methodology with wind tunnel testing results of sections of the heat sink so that the cooling contribution of each section can be individually characterized for design optimization on EVAC heat sink as well as for cooling performance estimation for what-if scenario analysis in a system so that system trade-off can be investigated to optimize system trade-off to provide overall better system cooling performance. The thermal resistance network methodology described in this paper can accurately predict the EVAC heat sink thermal performance independent of system boundary conditions at different locations on the heatsink. It can also be used to optimize the overall EVAC performance. The network thermal resistance model predicts the thermal performance within 3-6% of error compared to the test results.The second methodology is to design a wind tunnel test setup with other key components (DIMM in this paper) included from a specific system so that the airflow is somewhat representative as in that system. This methodology is meant to provide a repeatable and easy-to-setup way to benchmark and compare EVAC HS performance across different designs, vendors and/or builds.This paper also shows the test results of an EVAC heat sink prototype in a spread core system to assess the cooling performance gain comparing to a non-EVAC HS. While EVAC improves CPU cooling, it could have negative impact on other system components depending on the placement of the outriggers. This paper showcased the system cooling balancing between CPU and DIMM, with different EVAC design. EVAC heatsink described in this paper can provide 20-30% improvement in thermal performance of CPU and reduces memory cooling capability by 5-15% depending on the EVAC location