What if next-generation computing systems were able to adopt the human brain's information processing capacity and energy efficiency?
"We are designing a new generation of computing systems, inspired by the operating principles of the human brain," said Dhireesha Kudithipudi, associate professor of computer engineering in
Kudithipudi and members of the
The different projects focus on developing and using novel memristive devices (computer memory technology), as an essential step toward improved information processing in computer hardware. Kudithipudi's research team is embedding these devices in abstracted models of cortical and subcortical brain functions. With the advent of big data and the need for increasing computing power to manage this information, computing systems need to be more powerful. New computing systems solutions are being addressed using information from neuroscience, nanotechnology and computer architecture.
"If you think of the current computing systems, they are structured in a very specific paradigm which is called compute-and-storage. You separate what you are computing with where you are storing, known as VonNeumann computing," she explained. "There is a memory bandwidth bottleneck with these designs. We are moving away from that paradigm, where fundamental elements compute and store information in the same medium similar to biological synapses."
This past year, Kudithipudi and engineering doctoral student
Neuromorphic computing could improve multi-modal signal processing defined as the ability to acquire, manage and assess data efficiently from multiple input streams, which is not feasible with a traditional computing systems, she explained. This summer, Kudithipudi and Merkel were awarded the Air Force Summer Faculty Fellowship to study this problem in detail. This has important applications in
Kudithipudi and her research team received a grant from
"The brain's noise tolerance, power efficiency and resiliency of the mammalian brain are remarkable characteristics of evolutionary design. We should be studying the brain as an ideal model for information processing," she said. "Neuroscientists are attempting to understand the full-scale functional models of the brain, yet nobody has a complete picture of how [the brain] works. This is what makes this research area challenging and exciting. New discoveries are made every day that are shaping a new paradigm of intelligent computer architectures."
Note: This past summer, Kudithipudi presented research findings about Intelligent Computing with Memristive Circuits and Systems at the
TNS 30TagarumaMar-140830-4843730 30TagarumaMar
Most Popular Stories
- Government: 500 Million Records Stolen in 12 Months
- More Hispanic Voters May Not Mean More Clout
- Pistorius Gets 5-year Sentence in Shooting Death
- Mom Makes Toys R Us Pull 'Breaking Bad' Dolls
- Apple Pay Debuts With Few Issues
- Cuba Deploys More Medicos in Ebola Fight
- Volatility No Reason to Bail on Stock Market
- Samsung Phones Cleared For U.S. Government Use
- 2016 Camaro Shrinks, Moves to Caddy Platform
- Disney's Animated Feature 'Moana' Slated for 2016 Release