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MACHINE LEARNING INFERENCE ENGINE SCALABILITY

机译:机器学习推理引擎的可扩展性

摘要

Systems, apparatuses, and methods for adaptively mapping a machine learning model to a multi-core inference accelerator engine are disclosed. A computing system includes a multi-core inference accelerator engine with multiple inference cores coupled to a memory subsystem. The system also includes a control unit which determines how to adaptively map a machine learning model to the multi-core inference accelerator engine. In one implementation, the control unit selects a mapping scheme which minimizes the memory bandwidth utilization of the multi-core inference accelerator engine. In one implementation, this mapping scheme involves having one inference core of the multi-core inference accelerator engine fetch given data and broadcast the given data to other inference cores of the inference accelerator engine. Each inference core fetches second data unique to the respective inference core. The inference cores then perform computations on the first and second data in order to implement the machine learning model.
机译:公开了用于将机器学习模型自适应地映射到多核推理加速器引擎的系统,装置和方法。一种计算系统,包括具有耦合到存储器子系统的多个推理核的多核推理加速器引擎。该系统还包括控制单元,该控制单元确定如何将机器学习模型自适应地映射到多核推理加速器引擎。在一种实施方式中,控制单元选择使多核推理加速器引擎的存储器带宽利用率最小的映射方案。在一个实现中,该映射方案涉及使多核推理加速器引擎的一个推理核心获取给定数据并将该给定数据广播到推理加速器引擎的其他推理核心。每个推理核心获取对于各自的推理核心唯一的第二数据。然后,推理核心对第一和第二数据执行计算,以实现机器学习模型。

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