Reconfigurable Computing for Analytics Acceleration of Big Bio-Data: The AEGLE Approach

  • Andreas Raptopoulos
  • Sotirios Xydis
  • Dimitrios Soudris
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9040)

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.

Keywords

Chronic Lymphocytic Leukemia MapReduce Framework Reconfigurable Computing Analytics Acceleration Related Research Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andreas Raptopoulos
    • 1
  • Sotirios Xydis
    • 2
  • Dimitrios Soudris
    • 2
  1. 1.EXUSAthensGreece
  2. 2.School of Electrical and Computer EngineeringNational Technical University of AthensAthensGreece

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