This paper proposes a shape optimization algorithm based on the principles of Isogeometric Analysis (IGA) in which the parameterization of the geometry enters the problem formulation as an additional PDE-constraint. Inspired by the isoparametric principle of IGA, the parameterization and the governing state equation are treated using the same numerical technique. This leads to a scheme that is comparatively easy to differentiate, allowing for a fully symbolic derivation of the gradient and subsequent gradient-based optimization. To improve the efficiency and robustness of the scheme, the basis is re-selected during each optimization iteration and adjusted to the current needs. The scheme is validated in two test cases.

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High-performance computing platforms are becoming more and more heterogeneous, which makes it very difficult for researchers and scientific software developers to keep up with the rapid changes on the hardware market. In this paper, the open-source project FDBB (Fluid Dynamics Building Blocks) is presented, which eases the development of fluid dynamics applications for heterogeneous systems. It consists of a low-level API that provides a unified interface to many different linear algebra back-ends and a lightweight and extendible high-level expression template library, which provides largely customizable fluid dynamics building blocks, like transformations between primary and secondary variables as well as expressions for Riemann invariants, equations of state, inviscid fluxes and their flux-Jacobians. The performance of the developed approach is assessed both for synthetic micro-benchmarks and within mini-applications.@en