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All CFPs on WikiCFP | |||||||||||
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Present CFP : 2009 | |||||||||||
The CLADE 2009 workshop will be held in conjunction with the 18th International Symposium on High Performance Distributed Computing (HPDC-18), in Munich, Germany.
A new era of large scale, distributed applications are exploiting advances in networking, high-end computers, large data stores and middleware capabilities to address challenging problems. This workshop focuses on the complex issues that arise in large-scale applications of distributed computation, and promotes the development of innovative applications that effectively use distributed resources, e.g., to adapt to heterogeneity and dynamics in space and time. This includes recent results on the development, deployment, management and evaluations of large scale applications in science, engineering, medicine, business, economics, education, and other disciplines, on Grids and other distributed heterogeneous and dynamic computing environments. Topics of interest to this workshop include (but are not limited to) applications that illustrate advances in the following areas: * Large-scale distributed applications, both computational and data-centric * Application-specific portals in distributed environments * Distributed problem-solving environments * Distributed, collaborative science applications * Large, distributed data analysis * Applications with heterogeneous spatial and temporal characteristics * Distributed, multidimensional, dynamically adaptive applications * Applications of new theories and tools for constructing adaptive software systems * Enterprise/data-center applications * Applications on Emerging Distributed Environments such as Clouds * Examples of distributed applications benefiting from advances in o Worlflow tools in distributed environments o Application hosting frameworks for distributed environments o Runtime support for intelligent, adaptive systems o Programming models for heterogeneous and dynamic computation o Portability, quality of service, or fault-tolerance in cluster and Grid computation o Resource management, dynamic scheduling or load balancing in heterogeneous environments | |||||||||||
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