Berkeley MAPP is a MATLAB-based framework for quickly prototyping device compact models and simulation algorithms. MAPP’s internal code structuring, which differs markedly from that of Berkeley SPICE and related simulators, allows users to add new devices with only minimal knowledge of simulation algorithms, and vice-versa. We provide an overview of MAPP's modelling format ModSpec, its Verilog-A translator VAPP and its simulation capabilities. We will also briefly mention recent additions to MAPP, including memristor/RRAM models, BJT snapback models, table-based modelling capabilities, etc..

MAPP is available as open source under the GNU Public License.

Jaijeet Roychowdhury is a Professor in the EECS Department at the University of California at Berkeley. Prior to Berkeley, he spent 8 years in Bell Labs and another 8 years at the University of Minnesota. His current research interests encompass novel computational architectures and paradigms, analog and mixed-signal verification, multi-domain device modelling and open-source infrastructures for reproducible research.

Nano-Engineered Electronic Device Simulation Node (NEEDS), Network for Computational Nanotechnology (NCN), Discovery Park

Researchers should cite this work as follows:

• Jaijeet Roychowdhury (2017), "The Berkeley Model and Algorithm Prototyping Platform," https://nanohub.org/resources/26051.

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