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 2 articles )
Showing results 1 to 2 of 2.
- 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)