Skip to content

kn-cs/mont256-vec

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Efficient vectorized computations of Montgomery ladder over Montgomery curves at 256-bit security level.

The source codes of this repository correspond to the vectorized computations of scalar multiplications over Montgomery curves at 256-bit security level from the work Kummer versus Montgomery Face-off over Prime Order Fields, authored by Kaushik Nath & Palash Sarkar of Indian Statistical Institute, Kolkata, India.

The Montgomery curves are considered from the work Efficient elliptic curve Diffie-Hellman computation at the 256-bit security level and the implementations have been done using the 4-way vectorized algorithms of the work Efficient 4-way Vectorizations of the Montgomery Ladder. All the implementations are 4-way vectorized and have been developed using assembly language targeting the modern Intel architectures like Skylake and Haswell which are enabled with the AVX2 instruction set.

To report a bug or make a comment regarding the implementations please drop a mail to: Kaushik Nath.


Compilation and execution of programs

  • Please compile the makefile in the test directory and execute the generated executable file.
  • One can change the architecture accordingly in the makefile before compilation. Default provided is Skylake.

Overview of the implementations in the repository

  • M996558: 18-limb implementations of the scalar multiplication over the Montgomery curve M[p506-45,996558].

  • M952902: 18-limb implementations of the scalar multiplication over the Montgomery curve M[p510-75,952902].

  • M1504058: 18-limb implementations of the scalar multiplication over the Montgomery curve M[p521-1,1504058].


About

Efficient vectorized computations of Montgomery ladder over Montgomery curves at 256-bit security level.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published