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The ubiquity of various computing platforms ranging from desktop PCs, laptops, palmtops, tablets, etc. means that such analysis is made even easier.
Parallel computing is a process that simultaneously uses various computing resources to solve calculation problem, which has the advantages of speeding up program execution and saving investments.
This layered architecture enables to process and manage big data at multiple levels using various computing systems with different form factors. Therefore, wide ranges of application models are designed and new systems have been developed for big data processing.
In the proposed advanced computing environment, known as the HoneyBee Platform, various computing devices using single or multiple interfaces and technologies/standards need to communicate and cooperate efficiently with a certain level of security and safety measures.
Finally, the critical paths of the various computing units have been carefully analyzed and balanced using a pipeline scheme in order to maximize the operation frequency without introducing an excessive latency.
Our approach provides a flexible framework that allows us to test the performance of various computing modules in a various ways of combinations.
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Nonetheless, our approach can be applied in various cloud computing architectures since the scheduling component can be developed and easily integrated to the cloud system without dependency.
Various cloud computing platforms have emerged for genomic researchers, including Galaxy, Bionimbus and DNAnexus, which allow researchers to perform genomic analyses using only a web browser.
Then audio and video portion is separated out from IVS. Audio portion is divided into various segments to compute various audio features which is explained in Section 3.2.
Cloud computing offers various computational resources via convenient on-demand service provision.
In general, the total water demand of various industries computed using the following empirical relationship as shown in eq. 1 Krinner et al., 1999).
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