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 recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

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.

Recently, a research team from the Technical University of Munich in Germany developed a new algorithm called High Parallel ...

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 ...

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.