Advanced Computational Electromagnetics

Dear Colleagues,

Scientific and technological developments in applied electromagnetics set even more challenging goals either in traditional areas such as high-performance antenna design, radar cross section analysis of electrically large targets, target recognition, and electromagnetic compatibility, to mention just a few, or in the design of innovative circuits or of novel materials and structures.

The availability of even better-performing, massively parallel, and low-cost platforms for computational acceleration, such as graphics processing units (GPUs), which can be installed in embedded systems or inside traditional desktop PCs or even in small clusters, has enabled the democratization of high-performance computing (HPC), opening the door to real-time applications or to applications previously feasible only on large mainframes of a few computing centers. Today, HPC by such accelerators has turned to be of common use and so widespread that it is offered as a free-of-charge service of cloud computing. On a larger scale, TOP500 reports even more supercomputers based on hardware accelerators which, from year to year, make impossible applications now feasible.

By a virtuous circle, hardware innovations also influence the choice and the development of the most appropriate numerical techniques for solving challenging problems. New methods can be set up by properly exploiting new computational resources, or already available approaches can be readjusted or reinterpreted to this end, also exploiting specifically introduced programming languages.

The purpose of this Special Issue is to provide a forum for researchers and engineers on hot issues related to advanced numerical techniques and HPC for electromagnetics applications.

Prof. Dr. Angelo Liseno
Prof. Dr. Claudio Curcio
Guest Editors

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• Parallel computing for CPU clusters, GPUs, multi-GPUs, GPU clusters, and TPUs
• Fast and accurate numerical modeling
• Real-time processing
• Fast solution of inverse problems
• Fast or real-time ray tracing
• Machine learning and deep learning
• Trends, perspectives, and future visions on numerical computation on HPC
• Numerical techniques as FDTD, MoM, FEM, FMM, MLFMM
• Synthesis of large electromagnetic structures
• Multiscale problems
• Multiphysics.