Parallel algorithms for singular value decomposition (SVD) have risen to prominence as an indispensable tool in high-performance numerical linear algebra. They offer significant improvements in the ...
In this video, Peter Sanders from Karlsruhe Institute of Technology presents: Parallel Algorithms Reconsidered. Parallel algorithms have been a subject of intensive algorithmic research in the 1980s.
A hands-on introduction to parallel programming and optimizations for 1000+ core GPU processors, their architecture, the CUDA programming model, and performance analysis. Students implement various ...
It is well known that traditional Markov chain Monte Carlo (MCMC) methods can fail to effectively explore the state space for multimodal problems. Parallel tempering is a well-established population ...
Recently, a research team from the Technical University of Munich in Germany developed a new algorithm called High Parallel ...
Parallel tempering is a generic Markov chain Monte Carlo sampling method which allows good mixing with multimodal target distributions, where conventional Metropolis-Hastings algorithms often fail.
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