并行地理计算算法性能评测技术研究

从并行地理算法的正确性评测、性能评测、评测流程和评测工具实现等角度,研究了高性能集群环境下的评测技术。在正确性评测假设基础上,将评测用例在不同进程数环境下的计算结果与该算法在单进程环境下的运算结果逻辑求差得出相对误差,提出了问题规模计算方法。根据评测用例的问题规模确定评测用例的权重,提出了性能指标和评测流程,并通过评测工具自动获得同一个并行地理计算算法。在多个不同评测用例下的评测指标来衡量算法的计算误差与性能,形成评测报告。经实验验证,本文方法能较好地满足并行地理计算算法评测的需求,为并行空间分析算法性能优化提供技术保障。

A Technology to Evaluate the Performance of Parallel Geo-Computing Algorithms

We study and propose the evaluation approach for parallel geo-computation algorithms from the following aspects: correctness evaluation, performance evaluation, evaluation routines and evaluation tools. This approach proposes the hypotheses for correctness evaluation which are viewed as the foundation of measuring the correctness of geo-computation algorithms. To measure the correctness, we compute the relative errors by comparing the results using a certain algorithm under the single-process with the corresponding results evaluated under the multi-process environment. In this paper, we present a method in which the weights of the evaluation cases are determined by the computation scale. We also discuss a method which computes the computation scale of evaluation cases. The method involves the data scale, data distribution coefficient and time consumption per unit computation. Meanwhile, the geo-computation algorithms are evaluated by cases with weights. Under some circumstances, we can obtain the various evaluation indicators of a certain algorithm, such as the execution time, the speedups, and the parallel efficiency. In addition, this paper designs an evaluation routine based on the correctness evaluation and performance evaluation. It obtains the correctness evaluation and performance indicators of our target algorithms and generates the final reports. After experiments, we may confirm that our techniques can meet the requirements for evaluating parallel geo-computation algorithms. It could provide an effective support to algorithm optimization.