Themes

• Theme #1: FPGA architecture, Novel fabrics beyond traditional FPGAs, eFPGAs, Chiplet-based FPGAs, Improving the programmability of reconfigurable substrates

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• Theme #2: Hardware acceleration of machine learning (ML), Domain-specific acceleration of emerging workloads, Architecture and programming of heterogenous systems for ML

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• Theme #3: Machine Learning (ML) for Hardware, Deploying ML to improve architecture, design and verification of ASICs or FPGAs, developing datasets and frameworks for using ML easily in chip design

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• Theme #4: Sustainable Computing, Energy efficient computing, Processing in/near/using memory, Combining non-Von Neumann computing with existing paradigms