On-Chip Network-Enabled Many-Core Architectures for Computational Biology Applications
Turbo Majumder1, Partha Pratim Pande2,a and Ananth Kalyanaraman2,b
1Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
2School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, USA.
Computational molecular biology applications are at the heart of the backend processing in cyber-physical systems when applied to domains such as drug discovery, personalized medicine and genetic disease risk assessment. These applications are characterized by the preponderance of data and computational complexity, and yet require reasonably fast processing in order to have any meaningful impact. As such, hardware acceleration for these applications have generated a lot of research interest. In this paper, we discuss the superiority of Network-on-Chip (NoC)-enabled many-core platforms over other conventional platforms in both the quantum of speedup achieved and the amount of energy consumed. We hence posit that research in NoC-enabled platforms for CPS applications will be a major enabler of future scientific and medical breakthroughs.
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