| Presentation | 2023-03-23 Evaluation of Bit-Reduced Homomorphic Encryption Library on Intel Xeon and Fujitsu A64FX Masaki Nishi, Teppei Shishido, Xinyi Li, Keiji Kimura, Kentaro Sano, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | As deep learning is used in various applications, the protection of training data, input data, inference results, and training models is becoming an issue. Therefore, deep learning with homomorphic encryption, which can perform operations while keeping the data encrypted, has been attracting attention. However, the computational cost of homomorphic encryption is high, and various speed-up methods such as parallelization and use of hardware accelerators have been proposed. On the other hand, the authors have focused on the fact that deep learning inference does not require a large number of bits, and have proposed a deep learning inference method using a bit-reduced version of homomorphic encryption. In this paper, we first implemented the bit-reduced deep learning process on the homomorphic encryption library SEAL and the deep learning framework HE-Transformer, which uses SEAL, and evaluated them on an Intel Xeon processor. In addition, we implemented and evaluated a bit-reduced version of the homomorphic encryption on a Fujitsu A64FX. As a result of the evaluation, we achieved a maximum speedup of 9.37 times on the Intel Xeon processor compared to the original nGraph-HE2 in the classification of MNIST datasets using CryptoNets. The evaluation of matrix products on Fujitsu A64FX showed a speedup of up to 1.08x compared to Intel Xeon W-2145. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Homomorphic Encryption / Deep Learning / SIMD / Parallelization / A64FX |
| Paper # | CPSY2022-38,DC2022-97 |
| Date of Issue | 2023-03-16 (CPSY, DC) |
| Conference Information | |
| Committee | DC / CPSY / IPSJ-SLDM / IPSJ-EMB / IPSJ-ARC |
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| Conference Date | 2023/3/23(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Amagi Town Disaster Prevention Center (Tokunoshima) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Tatsuhiro Tsuchiya(Osaka Univ.) / Michihiro Koibuchi(NII) / Hiroyuki Ochi(Ritsumeikan Univ.) / / Hiroshi Inoue(Nagoya Institute of Technology) |
| Vice Chair | Toshinori Hosokawa(Nihon Univ.) / Kota Nakajima(Fujitsu Lab.) / Tomoaki Tsumura(Nagoya Inst. of Tech.) |
| Secretary | Toshinori Hosokawa(Nihon Univ.) / Kota Nakajima(Chiba Univ.) / Tomoaki Tsumura(JAIST) / (Hitachi) / (Tokyo Inst. of Tech.) / (Meiji Univ.) |
| Assistant | / Ryohei Kobayashi(Tsukuba Univ.) / Takaaki Miyajima(Meiji Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Dependable Computing / Technical Committee on Computer Systems / Special Interest Group on System and LSI Design Methodology / Special Interest Group on Embedded Systems / Special Interest Group on System Architecture |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluation of Bit-Reduced Homomorphic Encryption Library on Intel Xeon and Fujitsu A64FX |
| Sub Title (in English) | |
| Keyword(1) | Homomorphic Encryption |
| Keyword(2) | Deep Learning |
| Keyword(3) | SIMD |
| Keyword(4) | Parallelization |
| Keyword(5) | A64FX |
| 1st Author's Name | Masaki Nishi |
| 1st Author's Affiliation | Waseda University(Waseda Univ.) |
| 2nd Author's Name | Teppei Shishido |
| 2nd Author's Affiliation | Waseda University(Waseda Univ.) |
| 3rd Author's Name | Xinyi Li |
| 3rd Author's Affiliation | Waseda University(Waseda Univ.) |
| 4th Author's Name | Keiji Kimura |
| 4th Author's Affiliation | Waseda University(Waseda Univ.) |
| 5th Author's Name | Kentaro Sano |
| 5th Author's Affiliation | Center for Computational Science(RIKEN) |
| Date | 2023-03-23 |
| Paper # | CPSY2022-38,DC2022-97 |
| Volume (vol) | vol.122 |
| Number (no) | CPSY-451,DC-452 |
| Page | pp.pp.25-30(CPSY), pp.25-30(DC), |
| #Pages | 6 |
| Date of Issue | 2023-03-16 (CPSY, DC) |