AI deep compression toolchain and Hybrid-fixed point CNN accelerator
Summary Assisted by in-house AI deep compression toolchain (ezLabel, ezModel, ezQUANT, ezHybrid-M), the proposed technology supports automatic AI model design and optimization with the integrated performance of 120x model size reduction and 70x power reduction in 2D CNN model, and develops a world-first 1/2/4/8-bit CNN model realized by the developed high efficiency Hybrid fixed point CNN NPU (Hybrid-NPU), which has been verified in Xilinx ZCU102 FPGA and achieves the performance up to 2.5 TOPS(8-b)/ 20TOPS(1-b)@28nm technology running at 550MHz and 4TOPS/W energy efficiency.

The proposed technology attracted Wistron to launch a four-year investment with annual amount of 10M NTD to setup Wistron-NCTU embedded artificial intelligence research center in NCTU. At the same time, the proposed technology developed in our AI project also results in a total amount of 73M NTD investment from local industry. A new start-up is under cultivation to attract the Angel round investment up to 100M-180M NTD and launch by the end of 2021.

The proposed technology attracted Wistron to launch a four-year investment with annual amount of 10M NTD to setup Wistron-NCTU embedded artificial intelligence research center in NCTU. At the same time, the proposed technology developed in our AI project also results in a total amount of 73M NTD investment from local industry. A new start-up is under cultivation to attract the Angel round investment up to 100M-180M NTD and launch by the end of 2021.
Technical Film
Keyword embedded AI ADAS Self-driving system AI chip Interdisciplinary integration
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