Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/107016
Title: Heterogeneous Implementation of a Voronoi Cell-Based SVP Solver
Authors: Falcao, Gabriel 
Cabeleira, Filipe 
Mariano, Artur 
Paulo Santos, Luis
Keywords: Lattices; lattice-based cryptanalysis; Voronoi-cell; algorithms; high performance computing; parallelism; multi-threading; multicores; graphics processing units; multi-GPU; parallel computing; CUDA; OpenMP; StarPU
Issue Date: 2019
Publisher: IEEE
Project: This work was supported in part by the Instituto de Telecomunicações, in part by the Fundação para a Ciência e a Tecnologia (FCT) under Grant UID/EEA/50008/2019 and Grant PTDC/EEI-HAC/30485/2017, and in part by the National Funds through the Portuguese Funding Agency, FCT Fundação para a Ciência e a Tecnologia, under Grant UID/EEA/50014/2019. The work of A. Mariano was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant 382285730. 
Serial title, monograph or event: IEEE Access
Volume: 7
Abstract: This paper presents a new, heterogeneous CPUCGPU attacks against lattice-based (postquantum) cryptosystems based on the Shortest Vector Problem (SVP), a central problem in lattice-based cryptanalysis. To the best of our knowledge, this is the rst SVP-attack against lattice-based cryptosystems using CPUs and GPUs simultaneously.We show that Voronoi-cell based CPUCGPU attacks, algorithmically improved in previous work, are suitable for the proposed massively parallel platforms. Results show that 1) heterogeneous platforms are useful in this scenario, as they increment the overall memory available in the system (as GPU's memory can be used effectively), a typical bottleneck for Voronoi-cell algorithms, and we have also been able to increase the performance of the algorithm on such a platform, by successfully using the GPU as a co-processor, 2) this attack can be successfully accelerated using conventional GPUs and 3) we can take advantage of multiple GPUs to attack lattice-based cryptosystems. Experimental results show a speedup up to 7:6 for 2 GPUs hosted by an Intel Xeon E5-2695 v2 CPU (12 cores 2 sockets) using only 1 core and gains in the order of 20% for 2 GPUs hosted by the same machine using all 22 CPU threads (2 are reserved for orchestrating the GPUs), compared to single-CPU execution using the entire 24 threads available.
URI: https://hdl.handle.net/10316/107016
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2939142
Rights: openAccess
Appears in Collections:FCTUC Eng.Electrotécnica - Artigos em Revistas Internacionais
I&D IT - Artigos em Revistas Internacionais

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