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Prediction algorithms for the PCG pseudo-random generator
This project forked from cbouilla/pcg
Prediction algorithms for the PCG pseudo-random generator
Code for the algorithms that recover seeds for the PCG pseudo-random number generator. Written by Julia Sauvage ([email protected]) and Charles Bouillaguet ([email protected]). This code is in the public domain. challenges/ folder: tools to generate challenge inputs and expected output. Cknown/ folder: case where the default increment is used. main.c: Multi-thread program that recovers the seed from 3 consecutive outputs. Takes about 25 CPU-minutes. A simple procedure is repeated 2**37 times. Cunknown/ folder: case where an unknown increment is used (default in numpy). main.c: MPI program that recovers a partial difference between two states from 10 consecutive outputs. Takes about 12500 CPU-hours. Uses MPI, so is parallelizable on a cluster. A simple procedure is repeated 2**51 times. step2.py: given 64 consecutive outputs and the result from the previous program, finds the full difference between any two consecutive states. Very fast. step3.py: given 64 consecutive outputs and the result from the two previous programs, prints the seeds. Very fast. Other folders: journal article, slides, random junk.
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