Pollard Rho Algorithm Speedy Implementation

Hey everyone! Just finished my version of the Pollard-rho algorithm. It takes about 38 minutes for an 80-bit challenge and 14 minutes for a 70-bit one, thanks to half a billion data points. Used some AVX2 stuff, a bloom filter, and new optimizations. Check it out if you're interested!

Sounds awesome! Always hoping for faster methods.

Cool but where's the part for loading DP.bin with load-dp coming from? I added a new command-line option to specify a DP.bin file. If you use load-dp, it'll load from there instead of generating. Plus, everything else still works like saving DP, etc.

Wow, loading it from file is quick! I solved a 70-bit puzzle in 10 seconds on my ancient setup.

Hey NoMachine, bring your GitHub back please! Your coding skills are impressive and this Mark1 is a solid upgrade from your previous work.

Is it a dumb question, but... can we have both odd and even DPs in the same kangaroo, like @AlexanderCurl? Would that help with reaching 90-bit f?

That won't really help. For DLP problems, brute-forcing isn't needed anyways.

But I tried your method and it didn't work. You could've explained it better though. Using the X coord like that is pointless.

Thanks for the template but I’ve already got something for my PointsBuilder demo. Your batch addition method for P + Q and P Q isn't useful outside specific cases.

Lol can't wait for someone to try it and see how it fails. You should be the one to give it a shot since you think it speeds things up.

Just returned all the merit points I had. Now I owe you 11 points, I’ll get back to you when I can. But seriously, your idea is clever! A cool concept for Kangaroo Hopping!

Batch addition isn't effective for Kangaroo or rho, which is what we’re discussing here. Many have tried similar methods already.

This is a waste, honestly.

Next step for the Kangaroo is to avoid using RAM for DPs. Storing them in RAM really limits performance, especially in high ranges.

Where'd you get that idea? Storing DPs in RAM works fine with databases, you can handle terabytes of data.

Talking about the dp.bin we’re discussing here.

You could set up a Memory-Mapped DP System with a Bloom filter in RAM and a memory-mapped DP table on disk. Just be ready for the massive size of those tables.

I thought about adding a database to Kangaroo too. I had a plan to store DPs sorted like a database. Would make searches way more efficient.

I’ve done that already! Switched the DP_table from RAM to SSD. Next step, adding GPU support for secp256.

Is there a fork available for Visual Studio on Windows?