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基于多集群架構的并行規(guī)劃平臺研究

發(fā)布時間:2018-03-28 03:26

  本文選題:任務規(guī)劃 切入點:集群 出處:《天津大學》2013年碩士論文


【摘要】:任務規(guī)劃技術是隨著無人飛行平臺實際使用需求而迅速發(fā)展起來的一個新興技術,它是以先進、高效的計算機平臺為基礎,通過對各種海量基礎規(guī)劃數據的計算、處理和分析,輔助制定無人飛行平臺任務規(guī)劃和最終飛行航跡。任務規(guī)劃信息處理具有數據量大、計算復雜、處理時間長等特點,,基于多集群開發(fā)一個并行數據預處理系統(tǒng)對縮短任務規(guī)劃時間具有重要意義。 針對任務規(guī)劃中地圖預處理的計算密集和高度并行的特點,本文設計并實現了一個專用于調度地圖預處理作業(yè)的作業(yè)調度系統(tǒng)。為驗證作業(yè)調度系統(tǒng)的調度效率、容錯性和規(guī)劃平臺的可擴展性,本文從任務規(guī)劃中最耗時的基礎地圖數據的預處理入手,實現了地形適配區(qū)選擇的串行計算,并運用OpenMP和MPI兩種并行標準,實現了地形適配區(qū)選擇的多線程并行計算和多節(jié)點并行計算。在集群平臺上用作業(yè)調度系統(tǒng)對地形適配區(qū)選擇作業(yè)進行調度,通過對比實驗,表明了該作業(yè)調度系統(tǒng)具有良好的調度效率、容錯性和規(guī)劃平臺良好的可擴展性,能充分利用集群的計算能力,從而縮短任務規(guī)劃時間。
[Abstract]:Mission planning technology is a new technology developed rapidly with the actual demand of unmanned flight platform. It is based on advanced and efficient computer platform, through the calculation, processing and analysis of various mass basic planning data. To assist in developing mission planning and final flight path of unmanned flight platform. Mission planning information processing has the characteristics of large amount of data, complex calculation, long processing time, etc. It is important to develop a parallel data preprocessing system based on multiple clusters to shorten task planning time. According to the characteristics of intensive and highly parallel map preprocessing in task planning, this paper designs and implements a job scheduling system dedicated to scheduling map preprocessing, in order to verify the scheduling efficiency of the job scheduling system. Fault tolerance and extensibility of the planning platform. This paper starts with the preprocessing of the most time-consuming basic map data in task planning, realizes the serial calculation of terrain adaptation area selection, and uses two parallel standards, OpenMP and MPI. The multi-thread parallel computing and multi-node parallel computing for terrain adaptation area selection are realized. The job scheduling system is used to schedule the terrain adaptation area selection job on the cluster platform. It is shown that the job scheduling system has good scheduling efficiency, fault tolerance and good scalability of the planning platform, and can make full use of the computing power of the cluster, thus shortening the task planning time.
【學位授予單位】:天津大學
【學位級別】:碩士
【學位授予年份】:2013
【分類號】:TP338.6

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