Pointerchain: Tracing pointers to their roots – A case study in molecular dynamics simulations

Abstract

As scientific frameworks become sophisticated, so do their data structures. A data structure typically includes pointers and arrays to other structures in order to preserve application’s state. In order to ensure data consistency from a scientific application on a modern high performance computing (HPC) architecture, the management of such pointers on the host and the device, has become complicated in terms of memory allocations because they occupy separate memory spaces. It becomes so severe that one must go through a chain of pointers to extract the effective address. In this paper, we propose to reduce the need of excessive data transfer by introducing the idea of pointerchain, a directive that replaces the pointer chains with their corresponding effective address inside the parallel region of a code. Based on our analysis, pointerchain leads to a 39% and 38% reduction in the amount of generated codes and the total executed instructions, respectively.With pointerchain, we have parallelized CoMD, a Molecular Dynamics (MD) proxy application on heterogeneous HPC architectures while maintaining a single portable codebase. This portable codebase utilizes OpenACC, an emerging directive-based programming model, to address the need of memory allocations from three computational kernels in CoMD. Two of the three embarrassingly parallel kernels highly benefit from OpenACC and perform better than the hand-written CUDA counterparts. The third kernel performed 61% of peak performance of its CUDA counterpart. The three kernels are common modules in any MD simulations. Our findings provides useful insights into parallelizing legacy MD software across heterogeneous platforms.