The Aurora Financial Management System developed at the University of Vienna is a decision support tool for portfolio and asset liability management. An investor chooses a portfolio of various assets or asset classes, in such a way that some objective, including a risk measure, is maximized, subject to uncertainty of future markets' development and additional constraints (e.g. budget restrictions). The system is based on pricing models for financial instruments, and a multivariate Markovian birth-anddeath model for liabilities. The core of the system is a large scale linear optimization problem whose solution is the main outcome of the tool. In this paper we discuss the parallelization of a major computational kernel from this system utilizing HPF+, an extended version of HPF.

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