Optimizing Efficiency and Performance: PhD Thesis Defense on Energy- and Time-aware Scheduling for High-Performance Embedded Systems

Yesterday, I participated in the PhD defense committee of Julius Röder, a PhD student in the Parallel Computing Systems group at the University of Amsterdam. The thesis “Energy- and Time-aware Scheduling for Heterogeneous High-Performance Embedded Systems” addresses the relevant problem of optimizing non-functional behavior, such as timing and energy consumption, of heterogeneous high-performance embedded systems. The goal of this optimization Is to reduce energy consumption, thereby also reducing carbon footprint and extending battery-life, as well as ensuring that real-time requirements of applications are satisfied, even at high resource utilizations. To this end, the thesis contributes a discussion on setups used for energy measurements, as well as experiments and a statistical analysis that demonstrate the Importance of sampling frequency on the accuracy of such measurements. The bulk of the thesis proposes heuristic algorithms, both conventional and based on reinforcement learning, for mapping and scheduling applications modelled as directed acyclic graphs (DAG) on heterogeneous platforms. The applications are assumed to be available In different versions, with different non-functional behavior, for the different types of processing elements In the heterogeneous architecture, which enables trade-offs between timing and energy. A key strength of the thesis is that theory is combined with a practical component; the scheduling algorithms are implemented and evaluated on a heterogeneous multi-core systems, where timing and energy behavior are carefully measured and analyzed.

In presence of family, friends, and colleagues, Julius confidently defended his PhD thesis and earned the right to call himself a doctor. Congratulations Julius with this great achievement!

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