Program Control Language: a programming language for adaptive distributed applications
Many distributed applications must meet stringent performance requirements even when the performance characteristics of the underlying systems and networks vary significantly at runtime. Runtime adaptation can be used to tolerate such changes, but sophisticated adaptive distributed programs can be e...
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| Veröffentlicht in: | Journal of parallel and distributed computing Jg. 63; H. 11; S. 1082 - 1104 |
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| Sprache: | Englisch |
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| Abstract | Many distributed applications must meet stringent performance requirements even when the performance characteristics of the underlying systems and networks vary significantly at runtime. Runtime adaptation can be used to tolerate such changes, but sophisticated adaptive distributed programs can be extremely challenging to design, implement and debug. This paper proposes a language called Program Control Language (PCL) that provides a novel means of specifying adaptations in distributed applications. PCL is based on an abstract, global representation of a distributed program (a static task graph), which enables a programmer to
reason about and to
describe a wide range of application-specific adaptation strategies at a high level, using a few key mechanisms. PCL provides simple high-level syntax for local and remote adaptation operations, local and remote performance monitoring (and aggregation), and for performing adaptations synchronously or asynchronously with respect to the execution of the application process initiating the adaptation. The global task graph representation enables remote performance metrics and adaptation operations to be specified in simple global terms by any process, and the compiler and runtime system automatically perform the communication and synchronization required for the remote operations. The paper describes the conceptual adaptation framework, the PCL language, and our implementation of the PCL compiler and runtime system. The paper uses three adaptative applications examples to illustrate the capabilities and benefits of PCL, and to show experimentally that the performance overheads of using PCL for implementing an adaptive application are negligible. |
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| AbstractList | Many distributed applications must meet stringent performance requirements even when the performance characteristics of the underlying systems and networks vary significantly at runtime. Runtime adaptation can be used to tolerate such changes, but sophisticated adaptive distributed programs can be extremely challenging to design, implement and debug. This paper proposes a language called Program Control Language (PCL) that provides a novel means of specifying adaptations in distributed applications. PCL is based on an abstract, global representation of a distributed program (a static task graph), which enables a programmer to
reason about and to
describe a wide range of application-specific adaptation strategies at a high level, using a few key mechanisms. PCL provides simple high-level syntax for local and remote adaptation operations, local and remote performance monitoring (and aggregation), and for performing adaptations synchronously or asynchronously with respect to the execution of the application process initiating the adaptation. The global task graph representation enables remote performance metrics and adaptation operations to be specified in simple global terms by any process, and the compiler and runtime system automatically perform the communication and synchronization required for the remote operations. The paper describes the conceptual adaptation framework, the PCL language, and our implementation of the PCL compiler and runtime system. The paper uses three adaptative applications examples to illustrate the capabilities and benefits of PCL, and to show experimentally that the performance overheads of using PCL for implementing an adaptive application are negligible. |
| Author | Adve, Vikram Stanley, Joel Ensink, Brian |
| Author_xml | – sequence: 1 givenname: Brian surname: Ensink fullname: Ensink, Brian – sequence: 2 givenname: Joel surname: Stanley fullname: Stanley, Joel email: jstanley@cs.uiuc.edu – sequence: 3 givenname: Vikram surname: Adve fullname: Adve, Vikram email: ensink@cs.uiuc.edu, vadve@cs.uiuc.edu |
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| Cites_doi | 10.1109/4434.749137 10.1145/301618.301683 10.1145/641128.641131 10.1145/301618.301681 10.1007/BFb0053381 10.1109/32.825767 10.1145/268998.266708 10.1177/109434200101500401 10.1145/582034.582086 10.1109/98.709366 10.1109/HCW.2000.843728 10.1007/3-540-45644-9_15 10.1007/BFb0053581 10.1145/231379.231428 10.1145/243327.243340 10.1145/237721.237767 10.1145/239098.239104 10.1145/143369.143446 10.1145/331532.331538 10.1155/2000/481921 10.1109/SC.1998.10051 10.1109/88.384586 10.1145/165854.165874 10.1016/S0167-739X(99)00025-4 10.1007/3-540-44892-6_19 10.1109/SC.2000.10061 10.1109/RELDIS.1998.740506 10.1177/109434200001400403 10.1109/49.790486 10.1145/319151.319155 10.1177/109434200101500403 10.1109/CCGRID.2001.923223 10.1109/TPDS.2003.1195409 10.1006/jvlc.2001.0227 10.1145/331532.331533 |
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| Keywords | Computational grid Parallel computing Adaptive Performance metric Distributed Task graph Runtime system Program control language |
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