Solving Dynamic Programming Problems on a Computational Grid
We implement a dynamic programming algorithm on a computational grid consisting of loosely coupled processors, possibly including clusters and individual workstations. The grid changes dynamically during the computation, as processors enter and leave the pool of workstations. The algorithm is implemented using the MasterWorker library running on the HTCondor grid computing platform, which can be deployed on many networks. We implement value function iteration for large dynamic programming problems of two kinds: optimal growth problems and dynamic portfolio problems. We present examples that solve in hours on HTCondor but would take weeks if executed on a single workstation. The cost of using HTCondor is small because it uses CPU resources that otherwise would be idle. The use of HTCondor can increase a researchers computational productivity by at least two orders of magnitude.
grid computing value function iteration numerical dynamic programming parallel computing dynamic portfolio optimization multi-country optimal growth c61 c63 g11