Integrated Computational Electronics Laboratory (ICE)

Is that layout on those tiles?

Welcome to the ICE Laboratory Site @ GT

The lab has two current focus directions:

  • Programmable and configurable, analog and digital, circuits, signal processing, algorithms, and systems
  • Neuromorphic Engineering
From these two areas of focus, we research signal processing, analog and digital integrated circuits and systems design, computational neuroscience, nonlinear dynamics, and CMOS device physics.

Lead Professor: Dr. Jennifer Hasler

Topically Organized Publications

Overview writings

Recent Courses Taught

Potential Senior Design / Graduate Special Problems directions

Recent article on the importance of the Faculty--Ph.D. Student Mentoring Relationship (GT press: April 11, 2016)

"if you build it, you understand it. And if you understand it, you can build it" -- Carver Mead

Programmability and Configurability

Physical and Neuromorphic Computation

Neuromorphic Systems: have systems based on neuroscience, to perform biological like tasks, including robotics, and thereby contribute to neuroscience understanding.

References :
[1] S. George, S. Kim, S. Shah, et. al, "A Programmable and Configurable Mixed-Mode FPAA SOC,” IEEE Transactions on VLSI, 2016.
[2] M. Collins, J. Hasler, and S. George, "An Open-Source Toolset Enabling Analog–Digital–Software Codesign," Journal of Low Power Electronics Applications, January 2016.
[3] Electronic Product Magazine, March 21, 2016. "New analog chip uses 1,000 times less electrical power (and can be built a hundred times smaller) than comparable digital devices"
[4] http://www.rh.gatech.edu/news/508791/configurable-analog-chip-computes-1000-times-less-power-digital
References :
[1] J. Hasler, "We could build an artificial brain right now," IEEE Spectrum , June 2017. [2] J. Hasler, H. B. Marr, "Finding a Roadmap to achieve Large Neuromorphic Hardware Systems," Frontiers in Neuroscience, vol. 7, no. 118, September 2013. pp. 1-29. DOI=10.3389/fnins.2013.00118 [3] J. Hasler, "Starting Framework for Analog Numerical Analysis for Energy Efficient Computing", Journal of Low Power Electronics Applications, vol. 7, no. 17, June 2017. pp. 1-22. [4] J. Hasler, “Opportunities in Physical Computing driven by Analog Realization,” IEEE IC Rebooting Computing , San Deigo, October 2016.
[5] H. B. Marr and J. Hasler, "Compiling probabilistic, bio-inspired circuits on a field programmable analog array," Frontiers in Neuroscience, 2015. pp. 1-9.
[6] http://www.eetimes.com/document.asp?doc_id=1322022
[7] http://www.kurzweilai.net/neuromorphic-computing-roadmap-envisions-analog-path-to-simulating-human-brain
[8] http://www.extremetech.com/extreme/181096-researchers-create-a-roadmap-for-neuromorphic-brain-like-cpus
[9] http://phys.org/news/2014-04-neuromorphic-roadmap-envisions-analog-path.html