### Abstract

The Single Instruction, Multiple Data (SIMD) architecture enables computation in parallel on a single processor. The SIMD operations are implemented on some processors such as Pentium 3/4, Athlon, SPARC, or even on smart cards. This paper proposes efficient algorithms for assembling an elliptic curve addition (ECADD), doubling (ECDBL), and k-iterated ECDBL (k-ECDBL) with SIMD operations. We optimize the number of auxiliary variables and the order of basic field operations used for these addition formulas. If an addition chain has k-bit zero run, we can replace k-time ECDBLs to the proposed faster k-ECDBL and the total efficiency of the scalar multiplication can be improved. Using the singed binary chain, we can compute a scalar multiplication about 10% faster than the previously fastest algorithm proposed by Aoki et al. Combined with the sliding window method or the width-w NAF window method, we also achieve about 10% faster parallelized scalar multiplication algorithms with SIMD operations. For the implementation on smart cards, we establish two fast parallelized scalar multiplication algorithms with SIMD resistant against side channel attacks.

Original language | English |
---|---|

Pages (from-to) | 85-93 |

Number of pages | 9 |

Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |

Volume | E87-A |

Issue number | 1 |

Publication status | Published - Jan 1 2004 |

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### All Science Journal Classification (ASJC) codes

- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics

### Cite this

*IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences*,

*E87-A*(1), 85-93.

**Fast Elliptic Curve Multiplications with SIMD Operations.** / Izu, Tetsuya; Takagi, Tsuyoshi.

Research output: Contribution to journal › Article

*IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences*, vol. E87-A, no. 1, pp. 85-93.

}

TY - JOUR

T1 - Fast Elliptic Curve Multiplications with SIMD Operations

AU - Izu, Tetsuya

AU - Takagi, Tsuyoshi

PY - 2004/1/1

Y1 - 2004/1/1

N2 - The Single Instruction, Multiple Data (SIMD) architecture enables computation in parallel on a single processor. The SIMD operations are implemented on some processors such as Pentium 3/4, Athlon, SPARC, or even on smart cards. This paper proposes efficient algorithms for assembling an elliptic curve addition (ECADD), doubling (ECDBL), and k-iterated ECDBL (k-ECDBL) with SIMD operations. We optimize the number of auxiliary variables and the order of basic field operations used for these addition formulas. If an addition chain has k-bit zero run, we can replace k-time ECDBLs to the proposed faster k-ECDBL and the total efficiency of the scalar multiplication can be improved. Using the singed binary chain, we can compute a scalar multiplication about 10% faster than the previously fastest algorithm proposed by Aoki et al. Combined with the sliding window method or the width-w NAF window method, we also achieve about 10% faster parallelized scalar multiplication algorithms with SIMD operations. For the implementation on smart cards, we establish two fast parallelized scalar multiplication algorithms with SIMD resistant against side channel attacks.

AB - The Single Instruction, Multiple Data (SIMD) architecture enables computation in parallel on a single processor. The SIMD operations are implemented on some processors such as Pentium 3/4, Athlon, SPARC, or even on smart cards. This paper proposes efficient algorithms for assembling an elliptic curve addition (ECADD), doubling (ECDBL), and k-iterated ECDBL (k-ECDBL) with SIMD operations. We optimize the number of auxiliary variables and the order of basic field operations used for these addition formulas. If an addition chain has k-bit zero run, we can replace k-time ECDBLs to the proposed faster k-ECDBL and the total efficiency of the scalar multiplication can be improved. Using the singed binary chain, we can compute a scalar multiplication about 10% faster than the previously fastest algorithm proposed by Aoki et al. Combined with the sliding window method or the width-w NAF window method, we also achieve about 10% faster parallelized scalar multiplication algorithms with SIMD operations. For the implementation on smart cards, we establish two fast parallelized scalar multiplication algorithms with SIMD resistant against side channel attacks.

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M3 - Article

AN - SCOPUS:0842310312

VL - E87-A

SP - 85

EP - 93

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 1

ER -