No abstract

No abstract

The highly nonuniform transient power densities in modern semiconductor devices present difficult performance and reliability challenges for circuit components, multiple levels of interconnections and packaging, and adversely impact overall power efficiencies. Runtime temperature calculations would be beneficial to architectures with dynamic thermal management, which control hotspots by effectively optimizing regional power densities. Unfortunately, existing algorithms remain computationally prohibitive for integration within such systems. This work addresses these shortcomings by formulating an efficient method for fast calculations of temperature response in semiconductor devices under a time-dependent dissipation power. A device temperature is represented as output of an infinite-impulse response (IIR) multistage digital filter, processing a stream of sampled power data; this method effectively calculates temperatures by a fast numerical convolution of the sampled power with the modeled system's impulse response. Parameters such as a steady-state thermal resistance or its extension to a transient regime, a thermal transfer function, are typically used with the assumption of a linearity and time-invariance (LTI) to form a basis for device thermal characterization. These modeling tools and the time-discretized estimates of dissipated power make digital filtering a well-suited technique for a run-time temperature calculation. A recursive property of the proposed algorithm allows a highly efficient use of an available computational resource; also, the impact of all of the input power trace is retained when calculating a temperature trace. A network identification by deconvolution (NID) method is used to extract a time-constant spectrum of the device temperature response. We verify this network extraction procedure for a simple geometry with a closed-form solution. In the proposed technique, the amount of microprocessor clock cycles needed for each temperature evaluation remains fixed, which results in a linear relationship between the overall computation time and the number of temperature evaluations. This is in contrast to time-domain convolution, where the number of clock cycles needed for each evaluation increases as the time window expands. The linear dependence is similar to techniques based on FFT algorithms; in this work, however, use of z-transforms significantly decreases the amount of computations needed per temperature evaluation, in addition to much reduced memory requirements. Together, these two features result in vast improvements in computational throughput and allow implementations of sophisticated runtime dynamic thermal management algorithms for all high-power architectures and expand the application range to embedded platforms for use in a pervasive computing environment.

Two-phase microfluidic heat sinks promise high heat flux cooling at reduced pumping power compared to pumped liquid microchannel heat sinks. However, flow instabilities caused by bubble nucleation and expansion severely reduce heat transfer performance of two-phase microfluidic heat sinks. This study probes the governing physics of bubble nucleation and expansion by comparing the effects of pulsed heating to steady-state heating in a single microchannel. Pulsed heating at 8 Hz causes an increase in the average hotspot temperature of as much as 8°C compared to steady-state heating. Upstream and downstream temperature response does not vary significantly between heating conditions. The results correspond well with thin-film evaporation models for bubble growth. This study provides insight for designing two-phase microfluidic cooling system subjected to transient hotspots.

Two-phase microfluidic cooling solutions have the potential to meet the thermal and geometric requirements of high performance microprocessors. However, rapid nucleation and growth of the vapor phase in the micro-scale flow structures produce detrimental rise in the system pressure and create flow instabilities. In our previous work we developed a novel solution to these problems: to locally vent the vapor formed in the microstructures by capping the flow structures with porous, hydrophobic membranes that allow only the trapped vapor phase to escape the system. In this paper we present the results from a visualization study of this venting process in a copper microchannel with a porous hydrophobic Teflon membrane wall and determine the impact of varying flow conditions on the venting process. We tested liquid flow rates of 0.1, 0.25 and 0.5 ml/min with air injection rates varying from 0.2 to 6 ml/min, corresponding to mass qualities of 0.1% to 7%. Bubbly/slug and wavy flows are dominant at the lower liquid and air flow rates, with wavy-stratified and stratified flows becoming dominant at higher air injection rates. At the highest liquid flow rate, plug and annular flows were common. Analysis finds that venting effectiveness is insensitive to Reliq until the point where non-contact flow structures such as annular become dominant and result in a loss of effective venting area. We also find that venting area changes linearly with mass quality and that the maximum venting effectiveness can be improved by increasing the venting area or raising the total static system pressure. However, venting effectiveness is fundamentally limited by the membrane conductance.