[AI/ML] Large-Scale Field-Programmable Analog Arrays for on-chip machine learning in extreme environments
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Speaker: Jennifer Hesler, Georgia Tech
Abstract: Large-scale field-programmable analog array (FPAA) devices could enable ubiquitous analog or mixed-signal low-power sensor to processing devices similar to the ubiquitous implementation of the existing field-programmable gate array (FPGA) devices. Design tools enable high-level synthesis to gate/transistor design targeting today’s FPGA devices and the opportunity for analog or mixed-signal applications with FPAA devices. This discussion will illustrate the FPAA concepts and FPAA history. The development of FPAAs enables the development of multiple potential metrics, and these metrics illustrate future FPAA device directions. The system-on-chip (SoC) FPAA devices illustrate the IC capabilities, computation, tools, and resulting hardware infrastructure. SoC FPAA device generation has enabled analog computing with levels of abstraction for application design.