A Technology to Evaluate the Performance of Parallel Geo-Computing Algorithms
Chen Cuitin · Geo-information Science · 2015
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.