Abstract
This paper overviews the main computational issues in personalized and precision medicine (PPM), and present a cogent case for network-on-chip (NoC)-based multicore platforms as enablers in the process. We identify a series of challenges for the design and optimization of NoC-based solutions for PPM. To capture the characteristics of the cyber-physical sensing and processing, we propose a new computational model built on a dynamical heterogeneous hyper-graph description of application-to-architecture interactions. Starting from these premises, we summarize a few implications on NoC design methodologies, present some NoC-based solutions that deal with some of the challenges, and outline a few open problems.
Published Version
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