Session: Porting Applications to Specific Hardware

Massive Parallelization for Finding Shortest Lattice Vectors Based on Ubiquity Generator Framework

Wednesday, November 18, 2020

2:00 PM – 2:30 PM ET

Channel: Track 4

Author(s)

NT

Nariaki Tateiwa

Kyushu University, Japan
Yuji Shinano

Zuse Institute Berlin, Germany
SN

Satoshi Nakamura

Nippon Telegraph and Telephone Corporation, Japan
AY

Akihiro Yoshida

Kyushu University, Japan
SK

Shizuo Kaji

Kyushu University, Japan
MY

Masaya Yasuda

Kyushu University, Japan
Katsuki Fujisawa

Kyushu University, Japan

Lattice-based cryptography has received attention as a next-generation encryption technique, because it is believed to be secure against attacks by classical and quantum computers. Its essential security depends on the hardness of solving the shortest vector problem (SVP). In cryptography, to determine security levels, it is becoming significantly more important to estimate the hardness of the SVP by high-performance computing. In this study, we develop the world's first distributed and asynchronous parallel SVP solver, the MAssively Parallel solver for SVP (MAP-SVP). It can parallelize algorithms for solving the SVP by applying the Ubiquity Generator framework, which is a generic framework for branch-and-bound algorithms. The MAP-SVP is suitable for massive-scale parallelization, owing to its small memory footprint, low communication overhead, and rapid checkpoint and restart mechanisms. We demonstrate the performance and scalability of the MAP-SVP by using up to 100,032 cores to solve instances of the Darmstadt SVP Challenge.