2 Search Results for "Glaß, Michael"

Document
DOI: 10.4230/DagRep.6.1.224
Dark Silicon: From Embedded to HPC Systems (Dagstuhl Seminar 16052)

Authors: Hans Michael Gerndt, Michael Glaß, Sri Parameswaran, and Barry L. Rountree

Published in: Dagstuhl Reports, Volume 6, Issue 1 (2016)

Abstract
Semiconductor industry is hitting the utilization wall and puts focus on parallel and heterogeneous many-core architectures. While continuous technological scaling enables the high integration of 100s-1000s of cores and, thus, enormous processing capabilities, the resulting power consumption per area (the power density) increases in an unsustainable way. With this density, the problem of Dark Silicon will become prevalent in future technology nodes: It will be infeasible to operate all on-chip components at full performance at the same time due to the thermal constraints (peak temperature, spatial and temporal thermal gradients etc.). However, this is not only an emerging threat for SoC and MPSoC designers, HPC faces a similar problem as well: The power supplied by the energy companies as well as the cooling capacity does not allow to run the entire machine at highest performance anymore. The goal of Dagstuhl Seminar 16052 "Dark Silicon: From Embedded to HPC Systems" was to increase the awareness of the research communities of those similarities and to work and explore common solutions based on more flexible thermal/power/resource management techniques both for runtime, design time as well as hybrid solutions.
Cite as

Hans Michael Gerndt, Michael Glaß, Sri Parameswaran, and Barry L. Rountree. Dark Silicon: From Embedded to HPC Systems (Dagstuhl Seminar 16052). In Dagstuhl Reports, Volume 6, Issue 1, pp. 224-244, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{gerndt_et_al:DagRep.6.1.224,
  author =	{Gerndt, Hans Michael and Gla{\ss}, Michael and Parameswaran, Sri and Rountree, Barry L.},
  title =	{{Dark Silicon: From Embedded to HPC Systems (Dagstuhl Seminar 16052)}},
  pages =	{224--244},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{1},
  editor =	{Gerndt, Hans Michael and Gla{\ss}, Michael and Parameswaran, Sri and Rountree, Barry L.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.1.224},
  URN =		{urn:nbn:de:0030-drops-58198},
  doi =		{10.4230/DagRep.6.1.224},
  annote =	{Keywords: dark silicon, embedded, hpc, parallel computing, performance analysis and tuning, power density, power modelling, programming tools, resource manageme}
}
Document
DOI: 10.4230/DagSemProc.06061.9
The Factorized Distribution Algorithm and the Minimum Relative Entropy Principle

Authors: Heinz Mühlenbein and Robin Höns

Published in: Dagstuhl Seminar Proceedings, Volume 6061, Theory of Evolutionary Algorithms (2006)

Abstract
We assume that the function to be optimized is additively decomposed (ADF). Then the interaction graph $G_{ADF}$ can be used to compute exact or approximate factorizations. For many practical problems only approximate factorizations lead to efficient optimization algorithms. The relation between the approximation used by the FDA algorithm and the minimum relative entropy principle is discussed. A new algorithm is presented, derived from the Bethe-Kikuchi approach in statistical physics. It minimizes the relative entropy to a Boltzmann distribution with fixed $eta$. We shortly compare different factorizations and algorithms within the FDA software. We use 2-d Ising spin glass problems and Kaufman's n-k function as examples.
Cite as

Heinz Mühlenbein and Robin Höns. The Factorized Distribution Algorithm and the Minimum Relative Entropy Principle. In Theory of Evolutionary Algorithms. Dagstuhl Seminar Proceedings, Volume 6061, pp. 1-27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{muhlenbein_et_al:DagSemProc.06061.9,
  author =	{M\"{u}hlenbein, Heinz and H\"{o}ns, Robin},
  title =	{{The Factorized Distribution Algorithm and the Minimum Relative Entropy Principle}},
  booktitle =	{Theory of Evolutionary Algorithms},
  pages =	{1--27},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6061},
  editor =	{Dirk V. Arnold and Thomas Jansen and Michael D. Vose and Jonathan E. Rowe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.06061.9},
  URN =		{urn:nbn:de:0030-drops-5973},
  doi =		{10.4230/DagSemProc.06061.9},
  annote =	{Keywords: Junction tree, minimum relative entropy, maximum likelihood, Bethe-Kikuchi approximation}
}
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