Date: April 6, 2020
Speaker: Sara Achour
Faculty host: Prof. John Kymissis
Abstract: Reconfigurable analog computers are a powerful new computing substrate especially appropriate for executing dynamical systems in an energy efficient manner. These platforms leverage the physical behavior of transistors to directly implement computation. Under this paradigm, voltages and currents within the hardware implement continuously evolving variables in the computation.
In this talk, I discuss compilation techniques for automatically configuring such computers to execute dynamical systems. I present Legno, the first compilation system that automatically targets a real reconfigurable analog hardware platform of this class. Legno synthesizes analog circuits from parametric and specialized analog blocks and accounts for analog noise, quantization error, operating range limitations, and process variations within the hardware. I evaluate Legno on applications from the biology, physics, and controls domains. The results demonstrate that these applications execute with acceptable error while consuming microjoules of energy.
Bio: Sara Achour is a PhD candidate at the Computer Science and Artificial Intelligence Laboratory at Massachusetts Institute of Technology (CSAIL MIT) and a NSF Fellowship recipient. Her research focuses on new techniques and tools, specifically new programming languages, compilers, and runtime systems, that enable end users to easily develop computations that exploit the potential of emerging nontraditional computing platforms.