PIPS: Parallel optimization solver for stochastic programming problems with recourse. Uses an interior-point method and customized parallel linear algebra. Obtains the decomposition at the linear algebra layer by using a Schur-complement technique. MPI+OpenMP programming model. Supports GPUs for the accelaration of dense linear algebra. Ported to a variety of supercomputing platforms: IBM BG/P and BG/Q, Cray XE6, XK7 and XC30.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Breuer, Thomas; Bussieck, Michael; Cao, Karl-Kiên; Cebulla, Felix; Fiand, Frederik; Gils, Hans Christian; Gleixner, Ambros; Khabi, Dmitry; Koch, Thorsten; Rehfeldt, Daniel; Wetzel, Manuel: Optimizing large-scale linear energy system problems with block diagonal structure by using parallel interior-point methods (2018)
- Petra, Cosmin G.; Schenk, Olaf; Lubin, Miles; Gäertner, Klaus: An augmented incomplete factorization approach for computing the Schur complement in stochastic optimization (2014)
- Lubin, Miles; Hall, J. A. Julian; Petra, Cosmin G.; Anitescu, Mihai: Parallel distributed-memory simplex for large-scale stochastic LP problems (2013)