Device Requirements and Technology-driven Architecture Optimization for Analog Neurocomputing

V. Calayir and L. Pileggi, “Device Requirements and Technology-driven Architecture Optimization for Analog Neurocomputing”, IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), vol. 5, no. 2, pp. 162-173, June 2015.

A Robust and Efficient Power Series Method for Tracing PV Curves

X. Chen, D. Bromberg, G. Hug, X. Li and L. Pileggi, ” A Robust and Efficient Power Series Method for Tracing PV Curves”, The 47th North American Power Symposium, October 2015.

Using TMO-based RRAM Multi-Level Cells and Nano-Oscillators for Efficient ONN Implementation

T. C. Jackson, A. A. Sharma, R. Shi, J. Weldon, and L. Pileggi, “Using TMO-based RRAM Multi-Level Cells and Nano-Oscillators for Efficient ONN Implementation”,TECHCON 2015, Austin, Texas.

High Performance, Integrated 1T1R Oxide-based Oscillator: Stack Engineering for Low-Power Operation in Neural Network Applications

A. Sharma, T. Jackson, J. Bain, L. Pileggi and J. Weldon, “High Performance, Integrated 1T1R Oxide-based Oscillator: Stack Engineering for Low-Power Operation in Neural Network Applications”,in IEEE Symp. VLSI Technology, June 2015.

Application-Specific Synthesis of Embedded Logic-in-Memory Designs

H.E. Sumbul, K. Vaidyanathan, Q. Zhu, F. Franchetti, L. Pileggi, “Application-Specific Synthesis of Embedded Logic-in-Memory Designs”, manuscript accepted for publishing in Design Automation Conference (DAC 2015), June 2015.

3D Integration of AlN MEMS Filters and CMOS for Self-Healing RF Front-Ends

E. Calayir, J. Xu, A. Patterson, G. K. Fedder, G. Piazza, L. Pileggi, “3D Integration of AlN MEMS Filters and CMOS for Self-Healing RF Front-Ends”,Government Microcircuit Applications and Critical Technology Conference, March 2015.

An Equivalent Circuit Formulation of the Power Flow Problem with Current and Voltage State Variables

D. Bromberg, G. Hug, X. Li and L. Pileggi, “An Equivalent Circuit Formulation of the Power Flow Problem with Current and Voltage State Variables”,Powertech Eindhoven, June 2015.

An RRAM-Based Oscillatory Neural Network

T. C. Jackson, A. A. Sharma, J. A. Bain, J. A. Weldon, and L. Pileggi, “An RRAM-Based Oscillatory Neural Network”,in Proc. 2015 Latin American Symposium on Circuits and Systems. Montevideo, Uruguay, 2015.

3D-Stacked Memory-Side Acceleration: Accelerator and System Design

Q. Guo, N. Alachiotis, B. Akin, F. Sadi, G. Xu, T.M. Low, L. Pileggi, J.C. Hoe, and F. Franchetti, “3D-Stacked Memory-Side Acceleration: Accelerator and System Design”, WoNDP: 2nd Int’l Workshop on Near-Data Processing, December 2014.

Analog Neuromorphic Computing Enabled by Multi-Gate Programmable Resistive Devices, Design and Test in Europe

V. Calayir, M.Darwish, J. Weldon and L. Pileggi, “Analog Neuromorphic Computing Enabled by Multi-Gate Programmable Resistive Devices, Design and Test in Europe” (DATE), March 2015.