Abstract
This article presents the “Delta Driven Computer” (DDC) project and describes the design decisions made for its first implementation. DDC is composed of a set interconnected PCM (Processor, Communication Device, Memory) nodes. DDC is a parallel inference computer. For the first implementation we have studied how to efficiently process a deductive data base. In this article, special consideration is given to:
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the Virtual Inference Machine (VIM) which is based on a production rule language. The unique operation achieved at this abstract level is “saturation”. It is executed with a forward chaining strategy. A special effort has been made to study methods to optimize the execution of VIM programs (Alexander Method);
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the specific execution model DDEM and the data partitioning method which allow us to achieve full parallelism independently in each node of the machine;
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DDCL, the language of the machine, which is a small but powerful language and is oriented toward the execution of operations on relations;
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the internal representation of the data structures and the optimized algorithms which enable us to accelerate the operations on the data base.
This project is under development at the BULL Research Center and is partially supported by ESPRIT-415.
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© 1988 Kluwer Academic Publishers, Boston
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Gonzalez-Rubio, R., Rohmer, J., Bradier, A., Bergsten, B. (1988). DDC: A Deductive Database Machine. In: Kitsuregawa, M., Tanaka, H. (eds) Database Machines and Knowledge Base Machines. The Kluwer International Series in Engineering and Computer Science, vol 43. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1679-4_35
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