TY - GEN
T1 - Acceleration of Homomorphic Unrolled Trace-Type Function using AVX512 instructions
AU - Inoue, Kotaro
AU - Suzuki, Takuya
AU - Yamana, Hayato
N1 - Funding Information:
This work was supported by JST CREST (JPMJCR1503).
Publisher Copyright:
© 2022 ACM.
PY - 2022/11/7
Y1 - 2022/11/7
N2 - More and more data analysis is being outsourced due to the spread of cloud computing. Therefore, protection of the data from privacy violations and information leaks is required. In particular, homomorphic encryption, which allows computation to be performed with encrypted data, is being actively studied as one of the protection method. Ring learning with errors based homomorphic encryption schemes support packing which allows to pack several elements into slots of a plaintext and ciphertext. A trace-type function, which combines shifting slots (rotation) and homomorphic addition to obtain summation of slots, is often used in homomorphic encryption applications and acceleration of the trace-type function is important. In this paper, we further accelerate the trace-type function using Intel AVX512 compared to existing optimized trace-type function with loop unrolling. The results show that our AVX512 version was 1.05-2.30 times speedup compared to the non-AVX512 version.
AB - More and more data analysis is being outsourced due to the spread of cloud computing. Therefore, protection of the data from privacy violations and information leaks is required. In particular, homomorphic encryption, which allows computation to be performed with encrypted data, is being actively studied as one of the protection method. Ring learning with errors based homomorphic encryption schemes support packing which allows to pack several elements into slots of a plaintext and ciphertext. A trace-type function, which combines shifting slots (rotation) and homomorphic addition to obtain summation of slots, is often used in homomorphic encryption applications and acceleration of the trace-type function is important. In this paper, we further accelerate the trace-type function using Intel AVX512 compared to existing optimized trace-type function with loop unrolling. The results show that our AVX512 version was 1.05-2.30 times speedup compared to the non-AVX512 version.
KW - homomorphic encryption
KW - secure computation
KW - simd
UR - http://www.scopus.com/inward/record.url?scp=85142628739&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85142628739&partnerID=8YFLogxK
U2 - 10.1145/3560827.3563374
DO - 10.1145/3560827.3563374
M3 - Conference contribution
AN - SCOPUS:85142628739
T3 - WAHC 2022 - Proceedings of the 10th Workshop on Encrypted Computing and Applied Homomorphic Cryptography, co-located with CCS 2022
SP - 47
EP - 52
BT - WAHC 2022 - Proceedings of the 10th Workshop on Encrypted Computing and Applied Homomorphic Cryptography, co-located with CCS 2022
PB - Association for Computing Machinery, Inc
T2 - 10th Workshop on Encrypted Computing and Applied Homomorphic Cryptography, WAHC 2022 - Co-located with CCS 2022
Y2 - 7 November 2022
ER -