A 16-channel noise-shaping machine learning analog-digital interface
A 16-channel noise-shaping machine learning analog-digital interface
复制标题
16 通道噪声整形机器学习模拟数字接口
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
M. Flynn
中科院分区：
文献类型：
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作者：
Fred N. Buhler;Adam E. Mendrela;Yong Lim;Jeffrey Fredenburg;M. Flynn
16通道机器学习数字化接口将内积计算嵌入Delta-Sigma调制器（IPDSM）阵列中，消除量化噪声并对被乘数进行噪声整形。该原型电路在65 nm CMOS芯片上具有16个独立的IPDSM通道，核心面积为0.95 mm 2。每个通道执行高达100 M乘法/s。该系统演示了一个标准的机器学习方案的图像识别。它实现了相同的分类精度的MNIST集的手写数字与相同的算法在浮点DSP。
A 16-channel machine learning digitizing interface embeds Inner-Product calculation within a Delta-Sigma Modulator (IPDSM) array canceling quantization noise and noise shaping the multiplicand. The prototype, with 16 independent IPDSM channels occupies a core area of 0.95mm2 in 65 nm CMOS. Each channel performs up to 100M multiplications/s. The system is demonstrated with a standard machine learning scheme for image recognition. It achieves the same classification accuracy for the MNIST set of hand-written digits as with the same algorithm on floating point DSP.