Several emerging applications need a high performance, main-memory database for which typical memory systems may be inadequate. In particular, the processor-memory bandwidth proves to be a major performance limiting f...
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Several emerging applications need a high performance, main-memory database for which typical memory systems may be inadequate. In particular, the processor-memory bandwidth proves to be a major performance limiting factor. We present the design of a back-end object-oriented database board and argue for its use in implementing high performance, real-time applications. Our board uses programmable logic-enhanced memory (i.e., data memory with select computing abilities) which is a novel way to obviate the low bandwidth problem for data-intensive processing. Our efforts differ significantly from database machines by being more general-purpose and targeting the bandwidth issue at a different level of the memory hierarchy. We describe the utility of logic-enhanced memory in meeting the needs of high performance databases.
Declustering problems are well-known in the databases for parallel computing environments. In this paper, we propose a new similarity-based technique for declustering data. The proposed method can adapt to the availab...
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Declustering problems are well-known in the databases for parallel computing environments. In this paper, we propose a new similarity-based technique for declustering data. The proposed method can adapt to the available information about query distribution (e.g. size,shape and frequency) and can work with alternative atomic data-types. Furthermore, the proposed method is flexible and can work with alternative data distributions, data sizes and partition-size constraints. The method is based on max-cut partitioning of a similarity graph defined over the given set of data, under constraints on the partition sizes. It maximizes the chances that a pair of atomic data-items that are frequently accessed together by queries are allocated to distinct disks. We describe the application of the proposed method to parallelizing Grid Files at the data page level. Detailed experiments in this context show that the proposed method adapts to query distribution and data distribution, and that it outperforms traditional mapping-function-based methods for many interesting query distributions as well for several non-uniform data distributions. Copyright (C) 1996 Elsevier Science Ltd
We have produced a suite of software tools which has proved to be highly valuable in the porting of large, complex relational database applications from conventional to parallel systems. These tools are being continua...
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We have produced a suite of software tools which has proved to be highly valuable in the porting of large, complex relational database applications from conventional to parallel systems. These tools are being continually developed to extend their functionality and genericity over a range of platforms, and provide a basis for the design, implementation, optimisation and management of any parallel database system. A considerable amount of the development has been performed using a Meiko Relational DataCache - a multi-spare, multi-transputer ORACLE system. In this paper we present a summary of our activities, beginning with a brief description of the Meiko system (as currently configured), followed by a more detailed account of some of the tools, and finishing with some general comments on future work.
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