TCD-NPE: A Re-configurable and Efficient Neural Processing Engine, Powered by Novel Temporal-Carry-deferring MACs
TCD-NPE: A Re-configurable and Efficient Neural Processing Engine, Powered by Novel Temporal-Carry-deferring MACs
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DOI：
10.1109/reconfig48160.2019.8994751
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Ali Mirzaeian;H. Homayoun;Avesta Sasan
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文献类型：
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作者：
Ali Mirzaeian;H. Homayoun;Avesta Sasan
在本文中，我们首先提出了时间携带延迟MAC（TCD-MAC）的设计，并说明我们提出的解决方案可以获得显着的能量和性能优势时，利用处理输入数据流。然后，我们提出使用TCD-MAC构建一个可重构的，高速的，低功耗的神经处理引擎（TCD-NPE）。此外，我们提出了一种新的调度程序，列出了所需的处理事件的序列，以处理MLP模型在我们提出的TCD-NPE的计算轮数最少。我们表明，我们提出的TCD-NPE显着优于类似的神经处理解决方案，使用传统的MAC在能源消耗和执行时间。
In this paper, we first propose the design of Temporal-Carry-deferring MAC (TCD-MAC) and illustrate how our proposed solution can gain significant energy and performance benefit when utilized to process a stream of input data. We then propose using the TCD-MAC to build a reconfigurable, high speed, and low power Neural Processing Engine (TCD-NPE). We, further, propose a novel scheduler that lists the sequence of needed processing events to process an MLP model in the least number of computational rounds in our proposed TCD-NPE. We illustrate that our proposed TCD-NPE significantly outperform similar neural processing solutions that use conventional MACs in terms of both energy consumption and execution time.