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EDN Article: AI Hardware Acceleration Needs Careful Requirements Planning

By July 11, 2018May 12th, 2021No Comments

The explosion of artificial intelligence (AI) applications, from cloud-based big data crunching to edge-based keyword recognition and image analysis, has experts scrambling to develop the best architecture to accelerate the processing of machine learning (ML) algorithms. The extreme range of emerging options underscores the importance of a designer clearly defining the application and its requirements before selecting a hardware platform.
To help minimize power consumption for this level of edge-based AI image processing, GreenWaves Technologies’ GAP8 processor comprises nine RISC-V cores. One core is assigned to hardware and I/O control functions, the other eight form a cluster around shared data and instruction memory. The structure forms a CNN inference engine accelerator, with additional RISC-V ISA instructions to boost DSP-type operations.
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