Abstract
This paper presents the main directions of the AEGLE project, that targets to integrate cloud technologies together with heterogeneous reconfigurable computing in large scale healthcare systems for Big Bio-Data analytics. AEGLE’s concept brings together the’hot’ big-data technologies with the health’industry’ eventually leading to integrated care and creating a win-win situation for both. We provide the addressed Big Data health scenarios and we describe the structural elements of the proposed solution, with emphasis given in the exploitation of high-performance reconfigurable engines for Big Data analytics acceleration integrated to the AEGLE ecosystem, enabling personalized and integrated health-care services, while also promoting related research activities.
Cite
CITATION STYLE
Raptopoulos, A., Xydis, S., & Soudris, D. (2015). Reconfigurable computing for analytics acceleration of big bio-data: The AEGLE approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9040, pp. 531–541). Springer Verlag. https://doi.org/10.1007/978-3-319-16214-0_49
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