Benjamin Fischer

Niclas Eich, Johannes Erdmann, Martin Erdmann et al.

The VISPA project is a self-managed, mid-scale computing cluster that supports physics data analysis in research and teaching. Because the cluster is housed in a 1970s institute building with limited retrofit options, conventional efficiency upgrades would yield only minor energy savings. We therefore target sustainability primarily through user-centric measures. A monitoring system now records per-job energy consumption, while real-time data on the renewable share of the German power grid enable `green-window' scheduling. Users can query their individual energy consumption and carbon footprints, receive weekly reports, and tag jobs by project for aggregate accounting; memory records from previous runs help avoid oversubscription. All options are voluntary, fostering a cultural shift rather than imposing hard constraints. A simulation framework evaluates the potential impact of these measures. Together, the technological and behavioral interventions aim at medium- to long-term reductions in greenhouse-gas emissions by increasing resource awareness within the scientific community.

Benjamin Fischer, Nico Gorbach, Stefan Bauer et al.

Gaussian processes are powerful, yet analytically tractable models for supervised learning. A Gaussian process is characterized by a mean function and a covariance function (kernel), which are determined by a model selection criterion. The functions to be compared do not just differ in their parametrization but in their fundamental structure. It is often not clear which function structure to choose, for instance to decide between a squared exponential and a rational quadratic kernel. Based on the principle of approximation set coding, we develop a framework for model selection to rank kernels for Gaussian process regression. In our experiments approximation set coding shows promise to become a model selection criterion competitive with maximum evidence (also called marginal likelihood) and leave-one-out cross-validation.