Abstract
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-oriented approach 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 object is driven by the constraints on the resource on which the object will live. A new parallel programming paradigm is presented in the context of ParoC++ — a new parallel object-oriented programming environment for high performance distributed 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 real-time image processing is used as a test case to the system. The experimental results show that the ParoC++ model is efficient and scalable and that it makes easier to adapt parallel applications to dynamic environments.
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© 2003 Springer-Verlag Berlin Heidelberg
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Nguyen, TA., Kuonen, P. (2003). ParoC++: A Requirement-driven Parallel Object-oriented Programming Language. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Dongarra, J.J., Zomaya, A.Y., Gorbachev, Y.E. (eds) Computational Science — ICCS 2003. ICCS 2003. Lecture Notes in Computer Science, vol 2657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44860-8_17
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DOI: https://doi.org/10.1007/3-540-44860-8_17
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