arXiv subjects

Fritz Göbel

Publications and source records attributed to Fritz Göbel.

3 recordsLinked to original sources

arXiv2025

Software Development Aspects of Integrating Linear Algebra Libraries

Many scientific discoveries are made through, or aided by, the use of simulation software. These sophisticated software applications are not built from the ground up, instead they rely on smaller parts for specific use cases, usually from domains unfamiliar to the application scientists. The software library Ginkgo is one of these building blocks to handle sparse numerical linear algebra on different platforms. By using Ginkgo, applications are able to ease the transition to modern systems, and speed up their simulations through faster numerical linear algebra routines. This paper discusses the challenges and benefits for application software in adopting Ginkgo. It will present examples from different domains, such as CFD, power grid simulation, as well as electro-cardiophysiology. For these cases, the impact of the integrations on the application code is discussed from a software engineering standpoint, and in particular, the approaches taken by Ginkgo and the applications to enable sustainable software development are highlighted.

cs.SE↗

arXiv2023

GPU-Resident Sparse Direct Linear Solvers for Alternating Current Optimal Power Flow Analysis

Integrating renewable resources within the transmission grid at a wide scale poses significant challenges for economic dispatch as it requires analysis with more optimization parameters, constraints, and sources of uncertainty. This motivates the investigation of more efficient computational methods, especially those for solving the underlying linear systems, which typically take more than half of the overall computation time. In this paper, we present our work on sparse linear solvers that take advantage of hardware accelerators, such as graphical processing units (GPUs), and improve the overall performance when used within economic dispatch computations. We treat the problems as sparse, which allows for faster execution but also makes the implementation of numerical methods more challenging. We present the first GPU-native sparse direct solver that can execute on both AMD and NVIDIA GPUs. We demonstrate significant performance improvements when using high-performance linear solvers within alternating current optimal power flow (ACOPF) analysis. Furthermore, we demonstrate the feasibility of getting significant performance improvements by executing the entire computation on GPU-based hardware. Finally, we identify outstanding research issues and opportunities for even better utilization of heterogeneous systems, including those equipped with GPUs.

cs.CE↗

arXiv2020

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

In this paper, we present Ginkgo, a modern C++ math library for scientific high performance computing. While classical linear algebra libraries act on matrix and vector objects, Ginkgo's design principle abstracts all functionality as "linear operators", motivating the notation of a "linear operator algebra library". Ginkgo's current focus is oriented towards providing sparse linear algebra functionality for high performance GPU architectures, but given the library design, this focus can be easily extended to accommodate other algorithms and hardware architectures. We introduce this sophisticated software architecture that separates core algorithms from architecture-specific back ends and provide details on extensibility and sustainability measures. We also demonstrate Ginkgo's usability by providing examples on how to use its functionality inside the MFEM and deal.ii finite element ecosystems. Finally, we offer a practical demonstration of Ginkgo's high performance on state-of-the-art GPU architectures.

cs.MS↗