Reconfigurable computing for analytics acceleration of big bio-data: The AEGLE approach

1Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

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

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free