A full spectrum of computing-in-memory technologies. Sun, Z., Kvatinsky, S., Si, X., Mehonic, A., Cai, Y., & Huang, R. Nature Electronics, November, 2023. Publisher: Nature Publishing Group![A full spectrum of computing-in-memory technologies [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Computing in memory (CIM) could be used to overcome the von Neumann bottleneck and to provide sustainable improvements in computing throughput and energy efficiency. Underlying the different CIM schemes is the implementation of two kinds of computing primitive: logic gates and multiply–accumulate operations. Considering the input and output in either operation, CIM technologies differ in regard to how memory cells participate in the computation process. This complexity makes it difficult to build a comprehensive understanding of CIM technologies. Here, we provide a full-spectrum classification of all CIM technologies by identifying the degree of memory cells participating in the computation as inputs and/or output. We elucidate detailed principles for standard CIM technologies across this spectrum, and provide a platform for comparing the advantages and disadvantages of each of the different technologies. Our taxonomy could also potentially be used to develop other CIM schemes by applying the spectrum to different memory devices and computing primitives.
@article{sun_full_2023,
title = {A full spectrum of computing-in-memory technologies},
copyright = {2023 Springer Nature Limited},
issn = {2520-1131},
url = {https://www.nature.com/articles/s41928-023-01053-4},
doi = {10.1038/s41928-023-01053-4},
abstract = {Computing in memory (CIM) could be used to overcome the von Neumann bottleneck and to provide sustainable improvements in computing throughput and energy efficiency. Underlying the different CIM schemes is the implementation of two kinds of computing primitive: logic gates and multiply–accumulate operations. Considering the input and output in either operation, CIM technologies differ in regard to how memory cells participate in the computation process. This complexity makes it difficult to build a comprehensive understanding of CIM technologies. Here, we provide a full-spectrum classification of all CIM technologies by identifying the degree of memory cells participating in the computation as inputs and/or output. We elucidate detailed principles for standard CIM technologies across this spectrum, and provide a platform for comparing the advantages and disadvantages of each of the different technologies. Our taxonomy could also potentially be used to develop other CIM schemes by applying the spectrum to different memory devices and computing primitives.},
language = {en},
urldate = {2023-11-14},
journal = {Nature Electronics},
author = {Sun, Zhong and Kvatinsky, Shahar and Si, Xin and Mehonic, Adnan and Cai, Yimao and Huang, Ru},
month = nov,
year = {2023},
note = {Publisher: Nature Publishing Group},
keywords = {Computer science, Electrical and electronic engineering},
pages = {1--13},
}
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