Directive-Based Auto-Tuning for the Finite Difference Method on the Xeon Phi

Abstract

In this paper, we present a directive-based auto-tuning (AT) framework, called ppOpen-AT, and demonstrate its effect using simulation code based on the Finite Difference Method (FDM). The framework utilizes well-known loop transformation techniques. However, the codes used are carefully designed to minimize the software stack in order to meet the requirements of a many-core architecture currently in operation. The results of evaluations conducted using ppOpen-AT indicate that maximum speedup factors greater than 550% are obtained when it is applied in eight nodes of the Intel Xeon Phi. Further, in the AT for data packing and unpacking, a 49% speedup factor for the whole application is achieved. By using it with strong scaling on 32 nodes in a cluster of the Xeon Phi, we also obtain 24% speedups for the overall execution.