Costas Sarris

The design of advanced integrated circuits and microsystems from zero to terahertz frequencies calls for fast and accurate electromagnetics-based modeling and simulation. The sheer complexity and high design cost associated with the integrated circuits and microsystems prevent one from designing them based on hand calculation, approximation, intuition, or trial and error. The move towards higher frequencies and heterogeneous technologies stresses the need even more. However, the analysis and design of integrated circuits (ICs) and microsystems impose many unique challenges on electromagnetic analysis such as exponentially increased problem size and extremely multiscaled system spanning from nano- to centi-meter scales. These challenges become new driving forces of the advancement of Computational Electromagnetics (CEM) in recent years, since past techniques do not address them well. In this talk, recent advances in fast direct solvers of O(N) (optimal) complexity will be presented, including both direct PDE and IE solvers, for addressing the ultra large problem size encountered in the IC design problems. In these solvers, the underlying dense or sparse system matrix is directly inverted or factorized in O(N) complexity. To show how these solvers work, a series of new accuracy controlled fast matrix arithmetic will be elaborated including the representation of a dense matrix of O(N2) elements using O(N) parameters with controlled accuracy, subsequent matrix-matrix multiplication, matrix factorization, and inversion performed in O(N) complexity with directly controlled accuracy. The application of these fast algorithms to the design and analysis of industry product-level integrated circuits and systems will be presented. Comparisons with direct and iterative solvers in the past will be made, which demonstrate the clear advantages of the new O(N) direct solvers. Co-sponsored by: Center for Computational Science and Engineering (CCSE), Faculty of Applied Science and Engineering, University of Toronto Speaker(s): Dan Jiao Biography: Dan Jiao received the Ph.D. degree in electrical engineering from the University of Illinois at Urbana-Champaign, Urbana, IL, USA, in 2001. She then joined the Technology Computer-Aided Design (CAD) Division, Intel Corporation, until September 2005, where she was a Senior CAD Engineer, Staff Engineer, and Senior Staff Engineer. In September 2005, she joined Purdue University, West Lafayette, IN, USA, as an Assistant Professor with the School of Electrical and Computer Engineering. She is currently a Professor with Purdue University. She has authored 3 book chapters and over 300 papers in refereed journals and international conferences. Her current research interests include computational electromagnetics; high-frequency digital, analog, mixed-signal, and RF integrated circuit (IC) design and analysis; high-performance very large scale integration (VLSI) CAD; modeling of microscale and nanoscale circuits; applied electromagnetics; fast and high-capacity numerical methods; fast time-domain analysis, scattering and antenna analysis; RF, microwave, and millimeter-wave circuits; wireless communication; and bioelectromagnetics. Dr. Jiao has served as a reviewer for many IEEE publications and conferences. She is an associate editor for the IEEE Transactions on Components, Packaging, and Manufacturing Technology. She was the recipient of the 2013 S. A. Schelkunoff Prize Paper Award of the IEEE Antennas and Propagation Society, which recognizes the Best Paper published in the IEEE Transactions on Antennas and Propagation during the previous year. She has been named a University Faculty Scholar by Purdue University since 2013. She was among the 85 engineers selected throughout the nation for the National Academy of Engineerings 2011 U.S. Frontiers of Engineering Symposium. She was the recipient of the 2010 Ruth and Joel Spira Outstanding Teaching Award, the 2008 National Science Foundation (NSF) CAREER Award, the 2006 Jack and Cathie Kozik Faculty Start Up Award (which recognizes an outstanding new faculty member of the School of Electrical and Computer Engineering, Purdue University), a 2006 Office of Naval Research (ONR) Award under the Young Investigator Program, the 2004 Best Paper Award presented at the Intel Corporation’s annual corporate-wide technology conference (Design and Test Technology Conference) for her work on generic broadband model of high-speed circuits, the 2003 Intel Corporation Logic Technology Development (LTD) Divisional Achievement Award, the Intel Corporation Technology CAD Divisional Achievement Award, the 2002 Intel Corporation Components Research Award, the Intel Hero Award (Intel-wide she was the tenth recipient), the Intel Corporation LTD Team Quality Award, and the 2000 Raj Mittra Outstanding Research Award presented by the University of Illinois at Urbana–Champaign. Register: https://events.vtools.ieee.org/m/303190

Join the IEEE Toronto Electromagnetics & Radiation Society Chapter for a talk on High Order Adaptive Mesh Refinement, presented by Professor Dinshaw S. Balsara. Abstract: Adaptive mesh refinement (AMR) is the art of solving PDEs on a mesh hierarchy with increasing mesh refinement at each level of the hierarchy. Accurate treatment on AMR hierarchies requires accurate prolongation of the solution from a coarse mesh to a newly-defined finer mesh. For scalar variables, suitably high order finite volume WENO methods can carry out such a prolongation. However, classes of PDEs, like computational electrodynamics (CED) and magnetohydrodynamics (MHD), require that vector fields preserve a divergence constraint. The primal variables in such schemes consist of normal components of the vector field that are collocated at the faces of the mesh. As a result, the reconstruction and prolongation strategies for divergence constraint-preserving vector fields are necessarily more intricate. In this talk, we present a fourth order divergence constraint-preserving prolongation strategy that is analytically exact. Extension to higher orders using analytically exact methods is very challenging. To overcome that challenge, a novel WENO-like reconstruction strategy is invented that matches the moments of the vector field in the faces where the vector field components are collocated. This approach is almost divergence constraint-preserving; so we call it WENO-ADP. To make it exactly divergence constraint-preserving, a touch-up procedure is developed that is based on a constrained least squares (CLSQ) based method for restoring the divergence constraint up to machine accuracy. With the touch-up, it is called WENO-ADPT. It is shown that refinement ratios of two and higher can be accommodated. An item of broader interest in this work is that we have also been able to invent very efficient finite volume WENO methods where the coefficients are very easily obtained and the multidimensional smoothness indicators can be expressed as perfect squares. We demonstrate that the divergence constraint-preserving strategy works at several high orders for divergence-free vector fields as well as vector fields where the divergence of the vector field has to match a charge density and its higher moments. We also show that our methods overcome the late time instability that has been known to plague adaptive computations in Computational Electrodynamics. Co-sponsored by: Center for Computational Science and Engineering, University of Toronto Speaker(s): Prof. D. S. Balsara, Register: https://events.vtools.ieee.org/m/312557 Biography: Dinshaw S. Balsara received the Ph.D. degree in computational physics and astrophysics from the University of Illinois at Urbana-Champaign, Champaign, IL, USA, in 1990. He is currently a Professor with the Department of Physics and the Department of Applied and Computational Mathematics and Statistics. He has developed computational algorithms and applications in the areas of interstellar medium, turbulence, star formation, planet formation, the physics of accretion disks, compact objects, and relativistic astrophysics. Many of the algorithms developed by him for higher order methods have seen extensive use and have been copiously cited. Dr. Balsara was the recipient of the 2014 Department of Energy Award of Excellence for significant contributions to the Stockpile Stewardship Program and the 2017 Global Initiative on Academic Networks Award from the Government of India. He serves the community as an Associate Editor of Journal of Computational Physics and Computational Astrophysics and Cosmology.