{"title":"模拟争用对异构应用程序性能的影响","authors":"S. Figueira, F. Berman","doi":"10.1109/HPDC.1996.546210","DOIUrl":null,"url":null,"abstract":"Fast networks have made it possible to coordinate distributed heterogeneous CPU, memory and storage resources to provide a powerful platform for executing high-performance applications. However, the performance of these applications on such systems is highly dependent on the allocation and efficient coordination of application tasks. A key component for a performance-efficient allocation strategy is a predictive model which provides a realistic estimate of application performance under varying resource loads. In this paper, we present a model for predicting the effects of contention on application behavior in heterogeneous systems. In particular, our model calculates the slowdown imposed on communication and computation for non-dedicated two-machine heterogeneous platforms. We describe the model for the Sun/CM2 and Sun/Paragon coupled heterogeneous systems. We present experiments on production systems with emulated contention which show the predicted communication and computation costs to be within 15% on average of the actual costs.","PeriodicalId":267002,"journal":{"name":"Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1996-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"Modeling the effects of contention on the performance of heterogeneous applications\",\"authors\":\"S. Figueira, F. Berman\",\"doi\":\"10.1109/HPDC.1996.546210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fast networks have made it possible to coordinate distributed heterogeneous CPU, memory and storage resources to provide a powerful platform for executing high-performance applications. However, the performance of these applications on such systems is highly dependent on the allocation and efficient coordination of application tasks. A key component for a performance-efficient allocation strategy is a predictive model which provides a realistic estimate of application performance under varying resource loads. In this paper, we present a model for predicting the effects of contention on application behavior in heterogeneous systems. In particular, our model calculates the slowdown imposed on communication and computation for non-dedicated two-machine heterogeneous platforms. We describe the model for the Sun/CM2 and Sun/Paragon coupled heterogeneous systems. We present experiments on production systems with emulated contention which show the predicted communication and computation costs to be within 15% on average of the actual costs.\",\"PeriodicalId\":267002,\"journal\":{\"name\":\"Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPDC.1996.546210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPDC.1996.546210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling the effects of contention on the performance of heterogeneous applications
Fast networks have made it possible to coordinate distributed heterogeneous CPU, memory and storage resources to provide a powerful platform for executing high-performance applications. However, the performance of these applications on such systems is highly dependent on the allocation and efficient coordination of application tasks. A key component for a performance-efficient allocation strategy is a predictive model which provides a realistic estimate of application performance under varying resource loads. In this paper, we present a model for predicting the effects of contention on application behavior in heterogeneous systems. In particular, our model calculates the slowdown imposed on communication and computation for non-dedicated two-machine heterogeneous platforms. We describe the model for the Sun/CM2 and Sun/Paragon coupled heterogeneous systems. We present experiments on production systems with emulated contention which show the predicted communication and computation costs to be within 15% on average of the actual costs.