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Prof. Dr.-Ing. Richard Membarth serves as Research Professor for System on a Chip and AI for Edge Computing at Technische Hochschule Ingolstadt within the Computer Science domain. He obtained his Diploma in Computer Science with a minor in Physics from Friedrich-Alexander-Universität Erlangen-Nürnberg in 2008, followed by a postgraduate diploma in Computer and Information Sciences from Auckland University of Technology. He completed his Dr.-Ing. degree in 2013 at the same university with a dissertation titled "Code Generation for GPU Accelerators from a Domain-Specific Language for Medical Imaging." His professional trajectory encompasses serving as senior researcher and team leader for Compiler Technologies and High-Performance Computing at the German Research Center for Artificial Intelligence (DFKI) in Saarbrücken from 2014 to 2021, postdoctoral researcher at the Intel Visual Computing Institute at Saarland University from 2013 to 2014, and research employee at the Chair for Hardware/Software Co-Design at Friedrich-Alexander-Universität Erlangen-Nürnberg from 2008 to 2013. Additionally, he worked as a software consultant specializing in GPU computing and CUDA from 2009 to 2018.
Membarth's research specializes in parallel computer architectures and programming models, emphasizing automatic code generation for architectures from embedded systems to high-performance computing installations, applied to image processing, computer graphics, scientific computing, and deep learning. Notable publications include "GPUs All Grown-Up: Fully Device-Driven SpMV Using GPU Work Graphs" (2025, with Wildgrube et al.), "Exploiting Data Redundancy in Im2Col Convolutions" (2025, with Pfaller), "Exploration of Efficient Computation for Trajectory Planning via Fixed-Point Arithmetic" (2025, with Xu), "AnyQ: An Evaluation Framework for Massively-Parallel Queue Algorithms" (2023, with KenZel et al.), "XEngine: Optimal Tensor Rematerialization for Neural Networks in Heterogeneous Environments" (2022, with Schuler and Slusallek), and "AnyHLS: High-Level Synthesis with Partial Evaluation" (2020, with Özkan et al.). He is a member of the HiPEAC European Network on High Performance Edge and Cloud Computing and has contributed to conference leadership, including General Chair for High-Performance Graphics in 2019 and Papers Chair in 2020. His projects, such as AnyDSL and Hipacc, advance domain-specific languages and compilers for high-performance applications.
