On the Efficiency of Executing Diverse Game Tree Search Applications in a Volunteer Computing Federation

Abstract

A game tree search application can be implemented as the malleable parallel jobs that are adapted to various processor allocations. We establish an efficient desktop grid federation to enable the small to mid-sized organizations to perform large-scale game tree search tasks via resource sharing. Due to the uneven task scales of the organizations as well as the dynamic generation/pruning of game tree search tasks, the user credits of the desktop grids may fluctuate dramatically, leading an unstable resource allocation to the hosted applications. This paper shows that stable processor allocation leads to higher efficiency for the parallel tasks. A new brokering algorithm is developed that ensures both fairness and stable resource allocation.