Enabling Technologies for 3D ICs: TSV Modeling and Analysis

Abstract

Through silicon via (TSV) based three-dimensional (3D) integrated circuit (IC) aims to stack and interconnect dies or wafers vertically. This emerging technology offers a promising near-term solution for further miniaturization and the performance improvement of electronic systems and follows a more than Moore strategy. Along with the need for low-cost and high-yield process technology, the successful application of TSV technology requires further optimization of the TSV electrical modeling and design. In the millimeter wave (mmW) frequency range, the root mean square (rms) height of the TSV sidewall roughness is comparable to the skin depth and hence becomes a critical factor for TSV modeling and analysis. The impact of TSV sidewall roughness on electrical performance, such as the loss and impedance alteration in the mmW frequency range, is examined and analyzed following the second order small perturbation method. Then, an accurate and efficient electrical model for TSVs has been proposed considering the TSV sidewall roughness effect, the skin effect, and the metal oxide semiconductor (MOS) effect. However, the emerging application of 3D integration involves an advanced bio-inspired computing system which is currently experiencing an explosion of interest. In neuromorphic computing, the high density membrane capacitor plays a key role in the synaptic signaling process, especially in a spike firing analog implementation of neurons. We proposed a novel 3D neuromorphic design architecture in which the redundant and dummy TSVs are reconfigured as membrane capacitors. This modification has been achieved by taking advantage of the metal insulator semiconductor (MIS) structure along the sidewall, strategically engineering the fixed oxide charges in depletion region surrounding the TSVs, and the addition of oxide layer around the bump without changing any process technology. Without increasing the circuit area, these reconfiguration of TSVs can result in substantial power consumption reduction and a significant boost to chip performance and efficiency. Also, depending on the availability of the TSVs, we proposed a novel CAD framework for TSV assignments based on the force-directed optimization and linear perturbation.