A Simplicial Piecewise Linear Approach for Efficient Hardware Realization of Neural Networks : (Invited Presentation)

N. Rodríguez, P. Julián, E. Paolini
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Abstract

Neural Networks (NN) have been a matter of research because of their capability to solve complex problems where other topologies fail. However, current implementations of practical NNs require powerful computers for their deployment, like the ones used in data centers which typically require a high energy budget. This work proposes a simplicial piecewise linear algorithm as an alternative to implement NNs, which in addition can be implemented in low-power microelectronics. We illustrate the feasibility of the approach giving some examples where the simplicial algorithms replace conventional NNs with similar results.
神经网络硬件实现的简单分段线性方法(特邀报告)
神经网络(NN)由于能够解决其他拓扑结构无法解决的复杂问题而成为研究热点。然而,目前实际的神经网络的实现需要强大的计算机来部署,就像数据中心使用的那些通常需要高能量预算的计算机一样。这项工作提出了一种简单的分段线性算法作为实现神经网络的替代方案,该算法还可以在低功耗微电子中实现。我们给出了一些简单算法用类似的结果取代传统神经网络的例子来说明这种方法的可行性。
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