Automated Redirection of Hardware Accesses for Host-Compiled Software Simulation. - Rafael Stahl; Daniel Mueller-Gritschneder; Ulf Schlichtmann (FDL, 2018)

Instruction Extension of a RISC-V Processor Modeled with IP-XACT. - Saman Payvar; Esko Pekkarinen; Rafael Stahl; Daniel Mueller-Gritschneder; Timo D. Hämäläinen (NORCAS, 2019)

Fully Distributed Deep Learning Inference on Resource-Constrained Edge Devices. - Rafael Stahl; Zhuoran Zhao 001; Daniel Mueller-Gritschneder; Andreas Gerstlauer; Ulf Schlichtmann (SAMOS, 2019)

Neural Network-based Vehicle Image Classification for IoT Devices. - Saman Payvar; Mir Khan; Rafael Stahl; Daniel Mueller-Gritschneder; Jani Boutellier (SiPS, 2019)

Driver Generation for IoT Nodes With Optimization of the Hardware/Software Interface. - Rafael Stahl; Daniel Mueller-Gritschneder; Ulf Schlichtmann (IEEE Embed. Syst. Lett., 2020)

DeeperThings: Fully Distributed CNN Inference on Resource-Constrained Edge Devices. - Rafael Stahl; Alexander Hoffman; Daniel Mueller-Gritschneder; Andreas Gerstlauer; Ulf Schlichtmann (Int. J. Parallel Program., 2021)

The Scale4Edge RISC-V Ecosystem. - Wolfgang Ecker; Peer Adelt; Wolfgang Müller 003; Reinhold Heckmann; Milos Krstic; Vladimir Herdt; Rolf Drechsler; Gerhard Angst; Ralf Wimmer 001; Andreas Mauderer; Rafael Stahl; Karsten Emrich; et al. (DATE, 2022)

Towards Rapid Exploration of Heterogeneous TinyML Systems using Virtual Platforms and TVM's UMA. - Samira Ahmadifarsani; Rafael Stahl; Philipp van Kempen; Daniel Mueller-Gritschneder; Ulf Schlichtmann (CODAI, 2023)

MLonMCU: TinyML Benchmarking with Fast Retargeting. - Philipp van Kempen; Rafael Stahl; Daniel Mueller-Gritschneder; Ulf Schlichtmann (CODAI, 2023)

Efficient Software-Implemented HW Fault Tolerance for TinyML Inference in Safety-critical Applications. - Uzair Sharif; Daniel Mueller-Gritschneder; Rafael Stahl; Ulf Schlichtmann (DATE, 2023)

Fused Depthwise Tiling for Memory Optimization in TinyML Deep Neural Network Inference. - Rafael Stahl; Daniel Mueller-Gritschneder; Ulf Schlichtmann (CoRR, 2023)

Code Optimization and Generation of Machine Learning and Driver Software for Memory-Constrained Edge Devices. - Rafael Stahl (2024)