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Chapter 4 introduces our vision of how to use TCI and TLC to enable More-than-Moore system performance leaps. It first explores how TCI can be employed to stack SRAM to offer better memory access performance than stacked DRAM for deep neural network (DNN) accelerators to enable system-level innovations and possible paradigm shifts. The idea of an electronic right brain is then introduced and its difference from an electronic left brain implemented with the conventional von Neumann computer explained. SRAM stacked on an FPGA using TCI is then proposed as an implementation of a DNN-based electronic right brain. It further describes how, by storing configuration information in the SRAM, the FPGA can be reconfigured in real time to enable virtualization of different DNNs over time and hence temporal scaling of the right-brain hardware. It then explains how this can be combined with an electronic left brain based on a von Neumann computer also enhanced by TCI to construct a complete electronic brain, and how it can be scaled both up and down to address different performance needs. The chapter concludes by exploring how such an electronic brain can support trends in the IC industry and the emerging digital society.
Synthesising fifteen years of research, this authoritative text provides a comprehensive treatment of two major technologies for wireless chip and module interface design, covering technology fundamentals, design considerations and tradeoffs, practical implementation considerations, and discussion of practical applications in neural network, reconfigurable processors, and stacked SRAM. It explains the design principles and applications of two near-field wireless interface technologies for 2.5-3D IC and module integration respectively, and describes system-level performance benefits, making this an essential resource for researchers, professional engineers and graduate students performing research in next-generation wireless chip and module interface design.
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