A Reconfigurable Computing Architecture for Semantic Information Filtering Conference Paper uri icon


  • The increasing amount of information accessible to a user digitally makes information retrieval & filtering difficult, time consuming and ineffective. New meaning representation techniques proposed in literature help to improve accuracy but increase problem size exponentially. In this paper, we present a novel reconfigurable computing architecture that addresses this issue, outperforms contemporary many-core processors such as Intel's Single Chip Cloud computer and Nvidia's GPU's by 20x for semantic information filtering. We validate our design using industry standard System-on-chip virtual prototyping and synthesis tools. Such a high performance reconfigurable architecture can form a template for a wide range of content-based and collaborative filtering engines used for big-data analytics. 2013 IEEE.

name of conference

  • 2013 IEEE International Conference on Big Data

published proceedings


author list (cited authors)

  • Tripathy, A., Ieong, K. C., Patra, A., & Mahapatra, R.

citation count

  • 1

complete list of authors

  • Tripathy, Aalap||Ieong, Ka Chon||Patra, Atish||Mahapatra, Rabi

publication date

  • October 2013