Abstract
This chapter introduces a programming environment for SCI clusters that takes advantage of both parallel and distributed programming paradigms. It aims at helping programmers to design high performance applications based on the assembling of generic software components. This environment is based on CORBA (Common Object Request Broker Architecture), with our own extensions to support parallelism across several cluster nodes within a distributed system. Our contribution concerns extensions to support a new kind of object, which we call a parallel CORBA object (or parallel object), as well as the integration of message-passing paradigms, mainly MPI, within a parallel object. These extensions exploit as much as possible the functionality offered by CORBA and require few modifications to an available CORBA implementation. This paper reports on these extensions and the description of a runtime system, called Cobra, which provides resource allocation services for the execution of parallel objects.
The chapter is organized as follows. Section 19.2 discusses some issues related to parallel and distributed programming. Section 19.3 gives a short introduction to CORBA. Section 19.4 describes the concept of parallel CORBA objects. Section 19.5 introduces the Cobra runtime system for the execution of parallel objects. Section 19.6 presents a case study based on a signal processing application from Aerospatiale. Section 19.7 describes some related work which has some similarities with our work. Finally, Section 19.8 draws some conclusions and outlines perspectives of this work.
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Priol, T., René, C., Alléon, G. (1999). Programming SCI Clusters Using Parallel CORBA Objects. In: Hellwagner, H., Reinefeld, A. (eds) SCI: Scalable Coherent Interface. Lecture Notes in Computer Science, vol 1734. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10704208_25
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DOI: https://doi.org/10.1007/10704208_25
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