MN-Core - A Highly Efficient and Scalable Approach to Deep Learning

K. Namura, Johannes Maximilian Kühn, Tohru Adachi, H. Imachi, H. Kaneko, T. Kato, Go Watanabe, Naoto Tanaka, S. Kashihara, Hiroshi Miyashita, Y. Tomonaga, Ryosuke Okuta, Takuya Akiba, Brian Vogel, S. Kitajo, F. Osawa, K. Takahashi, Y. Takatsukasa, K. Mizumaru, T. Yamauchi, J. Ono, A. Takahashi, Tanvir Ahmed, Y. Doi, K. Hiraki, J. Makino. MN-Core - A Highly Efficient and Scalable Approach to Deep Learning. In 2021 Symposium on VLSI Circuits, Kyoto, Japan, June 13-19, 2021. pages 1-2, IEEE, 2021. [doi]

Authors

K. Namura

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Johannes Maximilian Kühn

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Tohru Adachi

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H. Imachi

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H. Kaneko

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T. Kato

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Go Watanabe

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Naoto Tanaka

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S. Kashihara

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Hiroshi Miyashita

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Y. Tomonaga

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Ryosuke Okuta

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Takuya Akiba

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Brian Vogel

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S. Kitajo

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F. Osawa

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K. Takahashi

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Y. Takatsukasa

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K. Mizumaru

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T. Yamauchi

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J. Ono

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A. Takahashi

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Tanvir Ahmed

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Y. Doi

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K. Hiraki

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J. Makino

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