Audio and image cross-modal intelligence via a 10tops/w 22nm soc with back-propagation and dynamic power gating
2022 IEEE Symposium on VLSI Technology and Circuits (VLSI …, 2022•ieeexplore.ieee.org
We present an ultra-low-power multimedia signal processor (MMSP) SoC that integrates a
versatile deep neural network (DNN) engine with audio and image signal processing
accelerators for cross-modal IoT intelligence. The proposed MMSP features 2MB MRAM to
store all DNN weights on-chip with an energy-efficient dataflow using an MRAM-cache and
dynamic power gating. The SoC achieves up to 3-10 TOPS/W peak energy efficiency and
consumes only 0.25-3.84 mW. Being the first to demonstrate CNN, GAN, and back …
versatile deep neural network (DNN) engine with audio and image signal processing
accelerators for cross-modal IoT intelligence. The proposed MMSP features 2MB MRAM to
store all DNN weights on-chip with an energy-efficient dataflow using an MRAM-cache and
dynamic power gating. The SoC achieves up to 3-10 TOPS/W peak energy efficiency and
consumes only 0.25-3.84 mW. Being the first to demonstrate CNN, GAN, and back …
We present an ultra-low-power multimedia signal processor (MMSP) SoC that integrates a versatile deep neural network (DNN) engine with audio and image signal processing accelerators for cross-modal IoT intelligence. The proposed MMSP features 2MB MRAM to store all DNN weights on-chip with an energy-efficient dataflow using an MRAM-cache and dynamic power gating. The SoC achieves up to 3-10 TOPS/W peak energy efficiency and consumes only 0.25-3.84 mW. Being the first to demonstrate CNN, GAN, and back-propagation (BP) on a single accelerator SoC for cross-modal fusion, it outperforms state-of-the-art DNN processors by 1.4 - 4.5× in energy efficiency.
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