Implementation of Parallel Game Tree Search on a SIMD System

Abstract

The α-β algorithm is an efficient technique for searching game trees. In this paper, we present the detailed implementation of parallel α-β algorithm on our Engineering and Scientific Computation Accelerator (ESCA) system, which is a heterogeneous multi-core SIMD (Single Instruction stream Multiple Data stream) architecture to accelerate the compute-intensive parallel computing in high performance applications and has enhanced for control organization. The conditional execution provided by ESCA has significant benefit to implement the α-β pruning, and the communication mechanism between the control unit and PEs (processing elements) can accumulate information for load balancing to gain better processor utilization. We choose synthetic game tree for the evaluation and the experimental results with the metric of speedup are presented with varied number of processing elements under various size of trees.