Pub Date : 2004-04-26DOI: 10.1109/HIPS.2004.1299187
Eduardo César, J. G. Mesa, Joan Sorribes, E. Luque
Parallel/distributed application development is a very difficult task for non-expert programmers, and therefore support tools are needed for all phases of this kind of application development cycle. This means that developing applications using predefined programming structures (frameworks) should be easier than doing it from scratch. We propose to take advantage of the knowledge about the structure of the application in order to develop a dynamic and automatic tuning tool. In this sense, we have designed POETRIES, which is a dynamic performance tuning tool based on the idea that a performance model could be associated to the high-level structure of the application. This way, the tool could efficiently make better tuning decisions. Specifically, we focus this work on the definition of the performance model associated to applications developed with the master-worker framework.
{"title":"Modeling master-worker applications in POETRIES","authors":"Eduardo César, J. G. Mesa, Joan Sorribes, E. Luque","doi":"10.1109/HIPS.2004.1299187","DOIUrl":"https://doi.org/10.1109/HIPS.2004.1299187","url":null,"abstract":"Parallel/distributed application development is a very difficult task for non-expert programmers, and therefore support tools are needed for all phases of this kind of application development cycle. This means that developing applications using predefined programming structures (frameworks) should be easier than doing it from scratch. We propose to take advantage of the knowledge about the structure of the application in order to develop a dynamic and automatic tuning tool. In this sense, we have designed POETRIES, which is a dynamic performance tuning tool based on the idea that a performance model could be associated to the high-level structure of the application. This way, the tool could efficiently make better tuning decisions. Specifically, we focus this work on the definition of the performance model associated to applications developed with the master-worker framework.","PeriodicalId":448869,"journal":{"name":"Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments, 2004. Proceedings.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133838669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-04-26DOI: 10.1109/HIPS.2004.1299197
Nathan Debardeleben, W. Ligon, R. Sass
In this paper, we describe Arches, an object-oriented framework for building domain-specific PSEs. The framework was designed to support a wide range of problem domains and to be extendable in a way that allows it to target very different high-performance computing models. To demonstrate this flexibility we describe two PSEs that have been developed from the same framework yet solve different problems and target very different computing platforms. The Coven PSE supports parallel applications that need the large-scale parallelism that is found in cost-effective Beowulf clusters. In contrast, the RCADE PSE targets reconfigurable computing (FPGA-based) platforms with fine-grain parallelism. RCADE was designed to aid NASA Earth scientists interested in studying satellite instrument data and who are unlikely to be schooled in low-level hardware design.
{"title":"Arches: an infrastructure for PSE development","authors":"Nathan Debardeleben, W. Ligon, R. Sass","doi":"10.1109/HIPS.2004.1299197","DOIUrl":"https://doi.org/10.1109/HIPS.2004.1299197","url":null,"abstract":"In this paper, we describe Arches, an object-oriented framework for building domain-specific PSEs. The framework was designed to support a wide range of problem domains and to be extendable in a way that allows it to target very different high-performance computing models. To demonstrate this flexibility we describe two PSEs that have been developed from the same framework yet solve different problems and target very different computing platforms. The Coven PSE supports parallel applications that need the large-scale parallelism that is found in cost-effective Beowulf clusters. In contrast, the RCADE PSE targets reconfigurable computing (FPGA-based) platforms with fine-grain parallelism. RCADE was designed to aid NASA Earth scientists interested in studying satellite instrument data and who are unlikely to be schooled in low-level hardware design.","PeriodicalId":448869,"journal":{"name":"Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments, 2004. Proceedings.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133885650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-04-26DOI: 10.1109/HIPS.2004.1299192
Keming Zhang, Kostadin Damevski, Venkatanand Venkatachalapathy, S. Parker
We present an overview of the SCIRun2 parallel component framework. SCIRun2 is based on the common component architecture (CCA) as stated by R. Armstrong et al. (1999) and the SCI Institutes' SCIRun by C. Johnson and S. Parker (1999). SCIRun2 supports distributed computing through distributed objects. Parallel components are managed transparently over an M/spl times/N method invocation and data redistribution subsystem. A meta component model based on CCA is used to accommodate multiple component models such as CCA, CORBA and Dataflow. A group of monitoring components built on top of the TAU toolkit as stated in Advanced Computing Laboratory (1999) evaluate the performance of the other components.
{"title":"SCIRun2: a CCA framework for high performance computing","authors":"Keming Zhang, Kostadin Damevski, Venkatanand Venkatachalapathy, S. Parker","doi":"10.1109/HIPS.2004.1299192","DOIUrl":"https://doi.org/10.1109/HIPS.2004.1299192","url":null,"abstract":"We present an overview of the SCIRun2 parallel component framework. SCIRun2 is based on the common component architecture (CCA) as stated by R. Armstrong et al. (1999) and the SCI Institutes' SCIRun by C. Johnson and S. Parker (1999). SCIRun2 supports distributed computing through distributed objects. Parallel components are managed transparently over an M/spl times/N method invocation and data redistribution subsystem. A meta component model based on CCA is used to accommodate multiple component models such as CCA, CORBA and Dataflow. A group of monitoring components built on top of the TAU toolkit as stated in Advanced Computing Laboratory (1999) evaluate the performance of the other components.","PeriodicalId":448869,"journal":{"name":"Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments, 2004. Proceedings.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115156548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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