By Mahdi Abdelguerfi, Simon Lavington
This booklet illustrates vital ways that new parallel is getting used to enhance the rate and value of quite a few details structures. It comprises 13 unique papers that survey the most recent developments in functionality bettering architectures for clever info systems.The machines featured within the textual content were designed to aid details platforms starting from relational databases to semantic networks and different synthetic intelligence paradigms. furthermore, a few of the tasks illustrated within the ebook include everyday architectural rules that help higher-level requisites by utilizing semantics-free designs.The case reviews describe add-on machines and performance-enhancing devices that hire parallel to hurry up database operations. different case experiences exhibit how high-performance pcs aid database and similar software program, even if a few structures have been initially designed for clinical or numeric purposes. The final 3 chapters provide examples of machines which are intentionally designed to hurry up a specific wisdom illustration formalism or a selected AI challenge fixing paradigm. the knowledge provided all through this e-book may also help all these engaged within the layout or use of high-performance architectures for nonnumeric (i.e., symbolic) purposes.
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Extra resources for Emerging Trends in Database and Knowledge Based Machines: The Application of Parallel Architectures to Smart Information Systems
A bucket of indices corresponding to a key is stored in blocks, each of which is in a separate bank. Thus, the effective access time for a bucketful of indices is typically the time to access a single block, since there are many parallel blanks in SM. These blocked-oriented memory blanks may be realized in the chargecoupled-devices technology. Thus, we have achieved the multiple-data-streams operation for the meta data by accessing multiple blocks of meta data in parallel. On the other hand, MM is still based on moving-head disk technology.
However, they tend to yield highest absolute performance in database management. The purelysoftware innovations tend to produce database computers that are easy and inexpensive to upgrade, that is, to scale up readily and cheaply for performance gains and capacity growths. However, on a machine-vis-a-vis-computer basis, the individual hardware-oriented database machine has a higher absolute performance than does the software-oriented database computer. The use of a software-oriented database computer is therefore not for its absolute performance but for its relative performance, that is, relative to the cost.
The processing of the pre-merge and output merge stages is carried out concurrently while records are being transferred between the host computer and the sorter. Thus, the latency time in the sorter (from the end of record input to the beginning of output) is N*([logk N]-2), where N > k 2. Typically this is equal to the time required for one stage-at worst the two stages-of the intermediate merge processing. Furthermore, since the sort processing is carried out through successive merges, the maximum number of records that can be sorted is disassociated from the hardware configuration.