Adaptive parallel computing for large-scale distributed and parallel applications

Proceedings of the First International Workshop on Data Dissemination for Large Scale Complex Critical Infrastructures(2010)

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摘要
This paper presents the structure and functionality of zFunction, which is an adaptive distributed computing platform that supports a user-friendly programming model for developing parallel processing applications. It allows developers to design software as if they are programming for a single computer and then it automatically takes care of data distribution and task parallelization activities on different cluster nodes or multiple CPU cores. zFunction thus substantially improves the performance of complex distributed applications that process a large amount of data in real time, mission critical systems. This paper uses a representative case study from the financial services domain to show how these types of applications can benefit from zFunction.
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关键词
user-friendly programming model,parallel application,adaptive parallel computing,representative case study,mission critical system,parallel processing application,large amount,financial services domain,multiple cpu core,different cluster node,data distribution,real time,software engineering,programming model,parallel processing,financial services,publish subscribe,event,distributed computing,communications,parallel computer,distributed application,ubiquitous computing
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