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intelligence. This PhD project will leverage the power of field-programmable gate arrays (FPGA) to deploy machine learning models on the edge with low latency and high energy efficiency. This added intelligence
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energy-efficient CMOS blocks implementing SSM-based LLMs. Prototype hardware blocks on FPGA and prepare for ASIC tape-out. Benchmark performance and comparison with transformer accelerators. Work with
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