Samsung uses MRAM for AI in-memory computing
三星的研究人员已经开发了一个64 x 64个横杆阵列，以使用电阻内存，相变内存和闪存存储器执行模拟多重蓄能（MAC）操作。
MRAM被用作耐耐力的前沿制造过程中的嵌入式非易失性记忆，但其低电阻将导致传统的横杆阵列中的大量功耗，该横梁阵列将当前的求和用于模拟MAC操作。
内存计算已成为实现下一代AI半导体芯片的有前途的技术之一，因为它允许局部处理存储在记忆中的数据，并可以最大程度地减少数据的移动，从而节省功耗。研究人员建议，不仅可以将此MRAM芯片用于内存计算，而且还可以用作下载生物神经元网络的平台。
The array is integrated with readout electronics in 28nm CMOS. Using this array, a two-layer perceptron is implemented to classify 10,000 Modified National Institute of Standards and Technology (MNIST) digits with an accuracy of 93.23 per cent (software baseline: 95.24 per cent). In an emulation of a deeper, eight-layer visual geometry group-8 neural network with measured errors, the classification accuracy improves to 98.86 per cent (software baseline: 99.28 per cent). The array also implements a single layer in a ten-layer neural network to realize face detection with an accuracy of 93.4 per cent.
下一步：合并研究
The research was led by Samsung Advanced Institute of Technology (SAIT) in close collaboration with Samsung Electronics Foundry Business and Semiconductor R&D Center.
“内存计算在大脑中，计算也出现在生物记忆或突触的网络中，而神经元之间的点也相似，”纸。“In fact, while the computing performed by our MRAM network for now has a different purpose from the computing performed by the brain, such solid-state memory network may in the future be used as a platform to mimic the brain by modelling the brain’s synapse connectivity.”
相关链接和文章：
www.samsung.com;www.nature.com/articles/S41586-021-04196-6
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