An object-oriented parallel programming language for distributed-memory parallel computing platforms
Science of Computer Programming
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Adaptive utilization of resources in a highly heterogeneous computational environment such as the Grid is a difficult question. In this paper, we address an object-orientedapproach to the solution using requirement-driven parallel objects. Each parallel object is a self-described, shareable and passive object that resides in a separate memory address space. The allocation of the parallel objectis driven by the constraints on the resource on which theobject will live. A new parallel programming paradigm ispresented in the context of ParoC++ - a new parallel object-oriented programming environment for high performancedistributed computing. ParoC++ extends C++ for supporting requirement-driven parallel objects and a runtime system that provides services to run ParoC++ programs in distributed environments. An industrial application on realtime image processing is used as a test case to the system.The experimental results show that the ParoC++ model isefficient and scalable and that it makes easier to adapt parallel applications to dynamic environments.