Themes

• Theme #1: Architecture and design of reconfigurable computing devices, Novel fabrics beyond traditional FPGAs, eFPGAs, Chiplet-based FPGAs, Improving the programmability of reconfigurable computing devices

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• Theme #2: Hardware acceleration of machine learning (ML), Domain-specific acceleration of emerging workloads, New applications of reconfigurable computing such as digital twins and quantum control and simulation

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• Theme #3: Machine Learning (ML) for Hardware, Deploying ML and LLMs 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