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¥ 2.0
Solution: End-to-End TinyML Deployment and Benchmarking Flow • [MLIF] (Machine Learning Interface) • Framework/target-independent abstraction layers for Target SW • [MLonMCU] • Provides support for • 15+ targets (mainly RISC-V simulators) • 6 backends ([TVM] and TFLM) • Handling of Dependencies • Analysis and Exploration methods • Designed with并行性/可重复性
在自定义RISC-V ASIPS上嵌入机器学习的挑战
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