Abstract
Cloud computing is increasingly being regarded as a key enabler of the 'democratization of science', because on-demand, highly scalable cloud computing facilities enable researchers anywhere to carry out data-intensive experiments. In the context of natural language processing (NLP), algorithms tend to be complex, which makes their parallelization and deployment on cloud platforms a non-trivial task. This study presents a new, unique, cloud-based platform for large-scale NLP research-GATECloud. net. It enables researchers to carry out data-intensive NLP experiments by harnessing the vast, on-demand compute power of the Amazon cloud. Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security and fault tolerance. We also include a cost-benefit analysis and usage evaluation. © 2012 The Author(s) Published by the Royal Society. All rights reserved.
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CITATION STYLE
Tablan, V., Roberts, I., Cunningham, H., & Bontcheva, K. (2013). GATECloud.net: A platform for large-scale, open-source text processing on the cloud. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1983). https://doi.org/10.1098/rsta.2012.0071
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