Accuracy Improvement With Weight Mapping Strategy and Output Transformation for STT-MRAM-Based Computing-in-Memory by Xianggao Wang, Na Wei, Shifan Gao, Wenhao Wu, Yi Zhao

“…Circuit-level simulation verified the functionality and performance improvement of the CiM macro based on the MNIST and CIFAR-10 datasets, realizing a 3% and 5% accuracy loss compared with the benchmark, respectively. The 640-GOPS (8 bit) throughput, 34.6-TOPS/mm2 area compactness, and 83.3-TOPS/W energy efficiency demonstrate the advantages of STT-MRAM CiM in the coming AI era.…”
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