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实体 Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication

Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication

PulseAugur coverage of Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication — every cluster mentioning Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_70326 ·

    新框架将神经网络处理器设计与认知不确定性相结合

    研究人员开发了一个统一的框架,用于神经网络处理器的端到端协同设计,集成了网络训练、芯片映射、制造和资源分配。该方法将不确定性视为一种可优化的资源,在成本、时间和功耗之外引入了“置信度”。该框架的模块化设计允许在不进行结构性更改的情况下独立优化每个组件,三个案例研究验证了其恢复帕累托最优实现和适应设计改进的能力。