A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

Technical Report · Tue Oct 01 00:00:00 EDT 2013

DOI:https://doi.org/10.2172/1096252· OSTI ID:1096252

James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew

The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); University of New Mexico,, Albuquerque, NM
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1096252
• Report Number(s): SAND2013-7915; 476320
• Country of Publication: United States
• Language: English