OF THE DISSERTATION Process Variation Aware Interconnect Simulation and Optimization in VLSI Design

This paper describes the ideas and philosophy behind a new compact model (CM) for deep-submicron MOSFETs, called Xsim, which has been developed from scratch over the past few years. Similarities to and differences from existing popular models are pointed out. The opinions on many controversial debates in the CM field are given. The ultimate goal of the CM development in the context of technolog...

An in-depth numerical study has been carried out to investigate a high-pressure commercial scale (2–8 meter diameter) slurry bubble column reactor (SBCR). Typical superficial gas velocities are in the range of 0.5–3 m/s, and overall vapor hold-ups are in the range of 0.45–0.85. The study revealed that steady compartmental reaction models do not match plant data when reaction time constants are ...

There has been an increased interest in optimization for the analysis of large-scale data sets which require gigabytes or terabytes of data to be stored. A variety of applications originate from the fields of signal processing, machine learning and statistics. Seven representative applications are described below. Magnetic Resonance Imaging (MRI): A medical imaging tool used to scan the anatomy...

Abstract. We consider techniques that enable large-scale gradient-based shape optimization of wave-guiding devices in the context of 3D time-domain simulations. The approach relies on a memory efficient boundary representation of the shape gradient together with primal and adjoint solvers semi-automatically generated by the FEniCS framework. The hyperbolic character of the governing linear wave...

Thevenin’s theorem, one of the most celebrated results of electric circuit theory, provides a two-parameter characterization of the behavior of an arbitrarily large circuit, as seen from two of its terminals. We interpret the theorem as a sensitivity result in an associated minimum energy/network flow problem, and we abstract its main idea to develop a decomposition method for convex quadratic ...

In this article, the author describes the results of a collaborative European project work with Abstract. The industrial and commercial worlds are increasingly competitive , requiring companiesto be more productiveand more responsiveto market changes (e.g. globalisation and privatisation). As a consequence, there is a strong need for solutions to large scale optimization problems, in domains su...

Traditional locality-sensitive hashing (LSH) techniques aim to tackle the curse of explosive data scale by guaranteeing that similar samples are projected onto proximal hash buckets. Despite the success of LSH on numerous vision tasks like image retrieval and object matching, however, its potential in large-scale optimization is only realized recently. In this paper we further advance this nasc...