{"title":"GPU-enabled efficient executions of radiation calculations in climate modeling","authors":"S. Korwar, Sathish S. Vadhiyar, R. Nanjundiah","doi":"10.1109/HiPC.2013.6799141","DOIUrl":null,"url":null,"abstract":"In this paper, we discuss the acceleration of a climate model known as the Community Earth System Model (CESM). The use of Graphics Processor Units (GPUs) to accelerate scientific applications that are computationally intensive is well known. This work attempts to extract the performance of GPUs to enable faster execution of CESM and obtain better model throughput. We focus on two major routines that consume the largest amount of time namely, radabs and radcswmx, which compute parameters related to the long wave (infra-red) and short wave (visible and ultra-violet) radiations respectively. We propose a novel asynchronous execution strategy in which the results computed by the GPU for the current time step are used by the CPU in the subsequent time step. Such a technique effectively hides computational effort on the GPU. By exploiting the parallelism offered by the GPU and using asynchronous executions on the CPU and GPU, we obtain a speed-up of about 26× for the routine radabs and about 5.6× for routine radcswmx.","PeriodicalId":206307,"journal":{"name":"20th Annual International Conference on High Performance Computing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"20th Annual International Conference on High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HiPC.2013.6799141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, we discuss the acceleration of a climate model known as the Community Earth System Model (CESM). The use of Graphics Processor Units (GPUs) to accelerate scientific applications that are computationally intensive is well known. This work attempts to extract the performance of GPUs to enable faster execution of CESM and obtain better model throughput. We focus on two major routines that consume the largest amount of time namely, radabs and radcswmx, which compute parameters related to the long wave (infra-red) and short wave (visible and ultra-violet) radiations respectively. We propose a novel asynchronous execution strategy in which the results computed by the GPU for the current time step are used by the CPU in the subsequent time step. Such a technique effectively hides computational effort on the GPU. By exploiting the parallelism offered by the GPU and using asynchronous executions on the CPU and GPU, we obtain a speed-up of about 26× for the routine radabs and about 5.6× for routine radcswmx.