{"title":"确定地图分区,加速风场计算","authors":"Gemma Sanjuan, C. Brun, T. Margalef, A. Cortés","doi":"10.1109/HPCSim.2014.6903674","DOIUrl":null,"url":null,"abstract":"Wind speed and direction are parameters that affect forest fire propagation dramatically. So, an accurate estimation of such parameters is crucial to predict the fire propagation precisely. WindNInja is a wind field simulator that can easily be coupled to a forest fire propagation simulator such as FARSITE. However, wind field simulators present to main drawbacks: They take too much time to compute the wind field and they require a lot of memory. So, a map partitioning strategy has been developed to compute partial wind field maps that can be aggregated afterwards. Each map part can be computed in parallel and the amount of memory required is available in a single node. In this work a methodology to determine the most adequate map partitioning is presented. The map part shape, map part size, amount of overlapping and number of parts have been studied considering execution time and effects on wind field estimation. The results are based on a wide experimentation and are validated with real case scenarios.","PeriodicalId":6469,"journal":{"name":"2014 International Conference on High Performance Computing & Simulation (HPCS)","volume":"15 1","pages":"96-103"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Determining map partitioning to accelerate wind field calculation\",\"authors\":\"Gemma Sanjuan, C. Brun, T. Margalef, A. Cortés\",\"doi\":\"10.1109/HPCSim.2014.6903674\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wind speed and direction are parameters that affect forest fire propagation dramatically. So, an accurate estimation of such parameters is crucial to predict the fire propagation precisely. WindNInja is a wind field simulator that can easily be coupled to a forest fire propagation simulator such as FARSITE. However, wind field simulators present to main drawbacks: They take too much time to compute the wind field and they require a lot of memory. So, a map partitioning strategy has been developed to compute partial wind field maps that can be aggregated afterwards. Each map part can be computed in parallel and the amount of memory required is available in a single node. In this work a methodology to determine the most adequate map partitioning is presented. The map part shape, map part size, amount of overlapping and number of parts have been studied considering execution time and effects on wind field estimation. The results are based on a wide experimentation and are validated with real case scenarios.\",\"PeriodicalId\":6469,\"journal\":{\"name\":\"2014 International Conference on High Performance Computing & Simulation (HPCS)\",\"volume\":\"15 1\",\"pages\":\"96-103\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on High Performance Computing & Simulation (HPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCSim.2014.6903674\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSim.2014.6903674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determining map partitioning to accelerate wind field calculation
Wind speed and direction are parameters that affect forest fire propagation dramatically. So, an accurate estimation of such parameters is crucial to predict the fire propagation precisely. WindNInja is a wind field simulator that can easily be coupled to a forest fire propagation simulator such as FARSITE. However, wind field simulators present to main drawbacks: They take too much time to compute the wind field and they require a lot of memory. So, a map partitioning strategy has been developed to compute partial wind field maps that can be aggregated afterwards. Each map part can be computed in parallel and the amount of memory required is available in a single node. In this work a methodology to determine the most adequate map partitioning is presented. The map part shape, map part size, amount of overlapping and number of parts have been studied considering execution time and effects on wind field estimation. The results are based on a wide experimentation and are validated with real case scenarios.