IM+io Fachmagazin, Ausgabe 1/2022

Computer werden grün. Green Computing: Rechenzentren, Architektur und Algorithmen nachhaltig machen.

Volker Lindenstruth, Frankfurt Institute for Advanced Studies


[1] D.R.H. Borderstep Institute, “Rechenzentren 2020, energiebedarf der rechenzentren steigt trotz corona weiter an.”

[2] Lindenstruth, V., Stöcker, H. “Building for a computer centre with devices for efficient cooling.”

[3] Lindenstruth, V., Stöcker, H. “Methods and apparatus for temperature control of computer racks and computer data centres.”

[4] Rohr, D., Neskovic, G., Lindenstruth, V. The L-CSC cluster: Optimizing power efficiency to become the greenest supercomputer in the world in the green500 list of November 2014, CoRR abs/1811.11475 (2018) [1811.11475].

[5] Rohr, D., Bach, M., G.N., Lindenstruth, V., Pinke, C., Philipsen, O. Lattice-csc: Optimizing and building an efficient supercomputer for lattice-qcd and to achieve first place in green500, in High Performance Computing – 30th International Conference (ISC), Frankfurt, Germany, July 12-16,, pp. 179–196, 2015.

[6] Kretz, M. Extending C++ for explicit data-parallel programming via SIMD vector types, Ph.D. thesis, Goethe University Frankfurt am Main, 2015. 10.13140/RG.2.1.2355.4323.

[7] Bach, M.,  Lindenstruth, V., Philipsen, O., Pinke, C. Lattice QCD based on OpenCL, Comput. Phys. Commun. 184 (2013) 2042.

[8] Gerhard, J.,  Lindenstruth, V., Bleicher, M. Relativistic hydrodynamics on graphic cards, Comput. Phys. Commun. 184 (2013) 311.

[9] Gorbunov, S., Rohr, D., Aamodt, K. et al., Alice hlt high speed tracking on gpu, Nuclear Science, IEEE Transactions on 58 (2011) 1845.

[10] ALICE Collaboration, Real-time data processing in the ALICE high level trigger at the LHC, Computer Physics Communications 242 (2019) 25.

[11] Gorbunov, S., Kebschull, U., Kisel, I., Lindenstruth, V., Müller, W.F. Fast simdized kalman filter based track fit, Comput. Phys. Commun. 178 (2008) 374.

[12] Cossio, P., Rohr, D.,  Baruffa, F., Rampp, M., Lindenstruth, V. and Hummer, G. BioEM: GPU-accelerated computing of bayesian inference of electron microscopy images, Comput. Phys. Commun. 210 (2017) 163.