*Several applications are considered in EPEEC: AVBP (Cerfacs, a numerical simulation framework for the study of fluid dynamics and combustion problems), DIOGENeS (Inria, a numerical simulation framework for the study of nanoscale light-matter interaction problems), OSIRIS (INESC-ID, a numerical simulation framework for the study of plasma physics problems), Quantum ESPRESSO (Cineca, a set of numerical tools for the study of electronic properties of materials) and SMURFF (IMEC, a Bayesian matrix factorization framework for building recommender systems with applications to life sciences). The present news focuses on the DIOGENeS application.*

The field of nanophotonics aims at studying and exploiting the way light interacts with matter structured at the nanoscale. As light is squeezed down into nanometer-scale volumes, field enhancement effects occur resulting in new optical phenomena which can be exploited to challenge existing technological limits and deliver superior photonic devices. Nanophotonics encompasses a wide variety of topics, including metamaterials, plasmonics, high resolution imaging, quantum nanophotonics, and functional photonic materials. Previously viewed as a largely academic field, nanophotonics is now entering the mainstream, and will play an increasing role in the development of exciting new products, ranging from high efficiency solar cells to personalised health monitoring devices able to detect the chemical composition of molecules at ultralow concentrations.

DIOGENeS (DIscOntinuous GalErkin Nanoscale Solvers) is a software suite dedicated to computational nanophotonics, which is developed by Inria. This software suite integrates several variants of the Discontinuous Galerkin (DG) method, which is a blend of finite element and finite volume methods. A DG method relies on an arbitrary high order polynomial interpolation of the field unknowns within the cells of an unstructured mesh. Such a mesh can be locally adapted to the peculiarities of irregularly shaped structures, material interfaces with complex topography, geometrical singularities, etc. As a consequence, a DG method is particularly well adapted to accurately and efficiently deal with the multiscale characteristics of nanoscale light-matter interaction problems. Numerical kernels of the DIOGENeS core library have been initially adapted to high performance computing thanks to a classical SPMD strategy implemented with the MPI message-passing programming standard. The DGTD (Discontinuous Galerkin-Time Domain) solver considered in EPEEC is one simulator, which is built on top of the DIOGENeS core library. It is used for different studies such as the design of nanostructured solar cell devices in connection with photovoltaic energy production (see Figure 1 left), or the design of meta-reflectarrays for light front control in connection with all-optical data communication (see Figure 1 right).

*Figure 1. Examples of simulations with the DGTD solver of DIOGENeS. Left plot: light trapping in a solar cell design with nanocone-based texturing of the active layer. Right plot: control of light front with a of meta-reflectarray. *

This DGTD solver is a perfect candidate for massively parallel heterogeneous computing systems and in particular on systems leveraging accelerators. The motivation for moving to exascale in the context of nanophotonics is twofold. One the one hand, the underlying computational mesh may involve a large number of cells because of the multiscale nature of the considered problem. In addition, high order polynomial expansion of the electromagnetic field components within each cell of the mesh translates into a total number of degrees of freedom that may be very large (from several tens of millions to a few billions). This is typically the case for the class of problems illustrated in Figure 1 right. Even if a relatively coarse mesh is sufficient to attain the required accuracy, which is the case for the problem illustrated in Figure 1 left, the physical simulation time may be very large because the goal is to model the resonant properties of particular structures. In any case, reducing time-to-solution is always a major concern, especially in view of addressing realistic problems modelled by the system of Maxwell equations coupled to advanced physical models of material response (e.g. non-linear media). On the other hand, the solver may be called several times within a goal-oriented outer iteration, further motivating the quest for the highest overall performance. Design optimisation and uncertainty quantification are two topics of high relevance for nanophotonics/nanoplasmonics that correspond to this latter setting.