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English(EN) SAMpLE: A SystemC-AMS Machine LEarning-based Framework for Virtual Prototyping

新的 SAMpLE 框架将机器学习模型集成到 SystemC-AMS 虚拟原型中

研究人员开发了 SAMpLE,一个开源框架,将机器学习模型集成到 SystemC-AMS 虚拟原型中。该框架允许机器学习模型作为一流的时序数据流组件运行,简化了它们在仿真中的集成。SAMpLE 提供两个执行后端:一个用于在 C++ 中对轻量级模型进行在线训练,另一个用于执行外部开发且无需手动集成的模型。它利用 ONNX 进行模型交换,从而在一个统一且可复现的仿真环境中评估各种基于机器学习的解决方案。 AI

影响 该框架可以简化将人工智能模型集成到硬件设计仿真中的过程,从而可能加速开发周期。

排序理由 该集群描述了一篇关于将机器学习集成到虚拟原型中的新研究论文的细节。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新的 SAMpLE 框架将机器学习模型集成到 SystemC-AMS 虚拟原型中

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该集群描述了一篇关于将机器学习集成到虚拟原型中的新研究论文的细节。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Andrei Mihai Albu, Sara Vinco ·

    SAMpLE:一种用于虚拟原型的SystemC-AMS机器学习框架

    arXiv:2608.25910v1 Announce Type: new Abstract: Machine Learning (ML) is increasingly used in virtual prototypes of embedded systems to model behaviors that are difficult to capture analytically. However, integrating ML models into virtual platform simulation is still typically d…