• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computers & geosciences >Scalability and composability of flow accumulation algorithms based on asynchronous many-tasks
【24h】

Scalability and composability of flow accumulation algorithms based on asynchronous many-tasks

机译：Scalability and composability of flow accumulation algorithms based on asynchronous many-tasks

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相关主题

摘要

Models simulating the state of the biological and physical environment can be built using frameworks that contain pre-developed data structures and operations. To achieve good model performance it is important that individual modelling operations perform and scale well. Flow accumulation operations that support the use of criteria for selecting how much material flows downstream are an important part in several Earth surface simulation models. For these operations, no algorithms exist that perform, scale, and compose well. The objective of this study is to develop these algorithms, and evaluate their performance, scalability, and composability. We base our algorithms on the asynchronous many-task approach for parallel and concurrent computations, which avoids the use of synchronization points and supports composability of modelling operations. The relative strong and weak scaling efficiencies when scaling a flow accumulation operation over six CPU cores in a NUMA node are 83% and 84% respectively. The relative strong and weak scaling efficiencies when scaling a case-study model over four cluster nodes are 73% and 84%. Our algorithms are composable: the latency of executing two flow accumulation operations combined is lower than the sum of their individual latencies.

著录项

获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号