OPTIMIZATION APPROACHES TO MPI AND AREA MERGING-BASED PARALLEL BUFFER ALGORITHM

Abstract

On buffer zone construction, the rasterization-based dilation method inevitably
introduces errors, and the double-sided parallel line method involves a series of
complex operations. In this paper, we proposed a parallel buffer algorithm based on
area merging and MPI (Message Passing Interface) to improve the performances of
buffer analyses on processing large datasets. Experimental results reveal that there
are three major performance bottlenecks which significantly impact the serial and
parallel buffer construction efficiencies, including the area merging strategy, the
task load balance method and the MPI inter-process results merging strategy.
Corresponding optimization approaches involving tree-like area merging strategy, the vertex number oriented parallel task partition method and the inter-process
results merging strategy were suggested to overcome these bottlenecks. Experiments
were carried out to examine the performance efficiency of the optimized parallel
algorithm. The estimation results suggested that the optimization approaches could
provide high performance and processing ability for buffer construction in a cluster
parallel environment. Our method could provide insights into the parallelization of
spatial analysis algorithm.