But how do devs calculate their speed when using BSGS?
I see a lot of peta, exa keys per second, I’m trying to figure out how they calculate the speed…and then apply it to my script.
Well, if you were the person you claim to be (WanderingPhilos
opher
Keyhunt), you probably wouldn't had put this question.
The source code of Keyhunt is open and you can see how the speed is determined. It is in the nature of the BSGS algorithm that you cannot compare these values with the classic searches. The same applies to Kangaroo, which is a completely different approach. A comparison would be like comparing apples and oranges. These are completely different algorithms, for example: if you run Kangaroo well-tuned and you would rely on the speed rate the tool shows you and then compare it to the speed of let's say BSGS you would be disappointed. Because BSGS will report a much higher rate. But in fact, the Kangaroo will always run faster than BSGS. Again, you cannot compare them.
In BSGS mode of keyhunt for example the speed shown also depends on the pubkeys used. More keys will result in less speed.
Honestly, it’s a simple question, maybe you shouldn’t try to answer.
I’m not trying to compare potatoes and cabbage.
If I am using BSGS and can find a 52 bit key in 30 seconds, what’s the speed? 😂
It really wasn't meant to spurn any controversy. I know others have disagreed in the past, so I was curious to what people had to say.
If I use albertobsd method, I can say that the speed of my single core python script gets roughly, 140,549,854,653,356 Keys/s.
I wasn't trying to say it was fast or anything, just curious as to the actual speed and how different people view it.
I've been working on a low memory BSGS script; this one only uses about 500MB of RAM. Low memory, for various reasons but my reason is because I wrote a server/client script (python) and some of my machines have 8-16 GB max on them so I needed a way to employ them via low memory.
my search rate per hour for 30 bit above is approximately 800,324 keys per hours (like what i said before about leaking the cpu speed and more usage ram when 30 bit above)
Time to find 66-bit key≈1.75×108years
Your code does seem on the slower side of speed, but I was just going to show you some ways/see if we could speed it up (using python only). Not saying it will ever solve a puzzle, but more speed never hurts.
hi sir, i'm very motivated with your opinion about search speed.
i do some Experiment, trial and error for 66 bit
Let's say i take one 66 bit address for practice
00000000000000000000000000000000000000000000000
2be7989dd1a1a63ad | Hash 160 20cb77af1a425c5e74483d9b30cf950911a090de | 13zQNJwpREZogcPSkNJmYQzZ9HZQZS48Hx [TARGET]
result scan :
000000000000000000000000000000000000000000000002b809677889fb1078 | Hash 160 20cb78b594b77cf97259be5cc414f0a49f1bde81 |
13zQNb5x4P7vCjag18rZKCVHkBcqtddaLS | 102.92 sec | 136.0 keys/sec |
00000000000000000000000000000000000000000000000285a7e79fd01fc2a4 | Hash 160 20cbc445f68147eb89314c6710de2a7c5fc2e0fb |
13zQj6btR6awFjac835xsvDqeCtVyioiiW | 112.67 sec | 124.9 keys/sec |
000000000000000000000000000000000000000000000002757de2916bb72c92 | Hash 160 20cbc889d5186984e2189dd818e67d990f992459 |
13zQkFk3v2WXrhLVVhP2NKM1JT4Gbd6VoY | 153.39 sec | 110.4 keys/sec |
000000000000000000000000000000000000000000000002a6bdd8aaca2a5a56 | Hash 160 20cbb6398c3a2a9ad13eec60d2ffd84ed113d96d |
13zQfHTEd9EZncjXmiKMoZV7SqSZP39myL | 159.93 sec | 100.8 keys/sec |
I'm very grateful the result seem make some chance to hit the targeted and correct key
00000000000000000000000000000000000000000000000
2b809677889fb1078 | Hash 160 20cb78b594b77cf97259be5cc414f0a49f1bde81 |
13zQNb5x4P7vCjag18rZKCVHkBcqtddaLS | 102.92 sec | 136.0 keys/sec |
i make some checkpoint rules and check if at least 10 addresses have similarity in hash160 derived from private key.