Exploration of Algorithms for the Hardware Acceleration of Multi-Scalar Multiplication on FPGA

Stephan Cilliers, Amit Kumar Mishra

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

In this paper, we present the exploration of algorithms for the hardware acceleration of multi-scalar multiplication (MSM) on field programmable gate arrays (FPGAs). We have aggregated Verilog and System Verilog implementations of popular algorithms for each component in the MSM processing stack, including large integer multiplication, modular reduction, and elliptic curve point addition, doubling, and scalar multiplication. Additionally, we have compared these algorithms in the context of MSM and evaluated their performance. Our results highlight the efficiency of application specific hardware over general purpose processors for computationally intensive operations. Our contribution provides a valuable resource for those interested in using hardware acceleration to improve the efficiency of zero knowledge proof systems.

Original languageEnglish
Title of host publication2023 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2023 - Proceedings
EditorsDharm Singh Jat, Fungai Bhunu Shava, Meenakshi Tripathi, Jyoti Gajrani, Ajay Nehra, Arpit Jain
PublisherIEEE Press
Pages264-274
Number of pages11
ISBN (Electronic)9798350314878
DOIs
Publication statusPublished - 24 Oct 2023
Externally publishedYes
Event2023 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2023 - Windhoek, Namibia
Duration: 16 Aug 202318 Aug 2023

Publication series

Name2023 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2023 - Proceedings

Conference

Conference2023 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2023
Country/TerritoryNamibia
CityWindhoek
Period16 Aug 202318 Aug 2023

Keywords

  • cryptography
  • elliptic curve point operations
  • FPGA
  • multi-scalar multiplication
  • zk-SNARKs

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