On the Autotuning Potential of Time-stepping methods from Scientific Computing. - Natalia Kalinnik; Robert Kiesel; Thomas Rauber; Marcel Richter; Gudula Rünger (FedCSIS, 2018)

A Hybrid CPU/GPU Implementation of Computationally Intensive Particle Simulations Using OpenCL. - Michael Hofmann 002; Robert Kiesel; Dirk Leichsenring; Gudula Rünger (ISPDC, 2018)

Exploring Self-Adaptivity Towards Performance and Energy for Time-Stepping Methods. - Natalia Kalinnik; Robert Kiesel; Thomas Rauber; Marcel Richter; Gudula Rünger (SBAC-PAD, 2018)

Energy and Performance Analysis of Parallel Particle Solvers from the ScaFaCoS Library. - Michael Hofmann 002; Robert Kiesel; Gudula Rünger (ICPE, 2018)

Performance and Energy Evaluation of Parallel Particle Simulation Algorithms for Different Input Particle Data. - Robert Kiesel; Gudula Rünger (FedCSIS (Position Papers), 2019)

A performance- and energy-oriented extended tuning process for time-step-based scientific applications. - Natalia Kalinnik; Robert Kiesel; Thomas Rauber; Marcel Richter; Gudula Rünger (J. Supercomput., 2021)