Corpus ID: 235446930

Exploring the Feasibility of Using 3D XPoint as an In-Memory Computing Accelerator

@article{Zabihi2021ExploringTF,
  title={Exploring the Feasibility of Using 3D XPoint as an In-Memory Computing Accelerator},
  author={Masoud Zabihi and Salonik Resch and M. H. Cilasun and Z. Chowdhury and Zhengyang Zhao and Ulya R. Karpuzcu and Jianping Wang and S. Sapatnekar},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.08402}
}
This paper describes how 3D XPoint memory arrays can be used as in-memory computing accelerators. We first show that thresholded matrix-vector multiplication (TMVM), the fundamental computational kernel in many applications including machine learning, can be implemented within a 3D XPoint array without requiring data to leave the array for processing. Using the implementation of TMVM, we then discuss the implementation of a binary neural inference engine. We discuss the application of the core… Expand

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