Take the RTX 3070 for example.
Bitcrack gives out 800mk.
Vanitysearch, gives out 1600-1700mk.
So why not use vanitysearch for search, if it is twice as fast?
Therefore, I asked about the possibility of searching in a fixed range, in vanitysearch.
Topic: VanitySearch (Yet another address prefix finder) - page 13. (Read 32966 times)
It is a pity that this is not possible.
A very useful feature.
He walks bitkrek step by step, or in jumps, but not randomly.
-stride ------ this is a jump, but the probability that the private key will be a multiple of a divisor or a jump ---- stride ------ is very small.
Thanks everyone for the answer.
What are you wanting to do?A very useful feature.
He walks bitkrek step by step, or in jumps, but not randomly.
-stride ------ this is a jump, but the probability that the private key will be a multiple of a divisor or a jump ---- stride ------ is very small.
Thanks everyone for the answer.
Create a to:from range and search random points all in between; each new key checked/"jump" is random?
It is a pity that this is not possible.
A very useful feature.
He walks bitkrek step by step, or in jumps, but not randomly.
-stride ------ this is a jump, but the probability that the private key will be a multiple of a divisor or a jump ---- stride ------ is very small.
Thanks everyone for the answer.
A very useful feature.
He walks bitkrek step by step, or in jumps, but not randomly.
-stride ------ this is a jump, but the probability that the private key will be a multiple of a divisor or a jump ---- stride ------ is very small.
Thanks everyone for the answer.
Hello.
Tell me, you can somehow in VanitySearch v1.18
Set a different initial search range for the key.?
For example CCCCCCCCCC: FFFFFFFFFFF.
I have ubuntu.
Grateful.
Tell me, you can somehow in VanitySearch v1.18
Set a different initial search range for the key.?
For example CCCCCCCCCC: FFFFFFFFFFF.
AFAIK, no it can't.Set a different initial search range for the key.?
For example CCCCCCCCCC: FFFFFFFFFFF.
You can try Bitcrack, it has a --keyspace option that may be what you're looking for: BitCrack - A tool for brute-forcing private keys
VanitySearch v1.18
Difficulty: 10054102514374868992
Search: 1TryMe33333 [Compressed]
Start Sat Jul 3 17:15:39 2021
Base Key: 3D4939898FF1A5997FE553408039239EEA795E783B821832C17954683D7D4726
Number of CPU thread: 1
Hello.
Tell me, you can somehow in VanitySearch v1.18
Set a different initial search range for the key.?
For example CCCCCCCCCC: FFFFFFFFFFF.
I have ubuntu.
Grateful.
Difficulty: 10054102514374868992
Search: 1TryMe33333 [Compressed]
Start Sat Jul 3 17:15:39 2021
Base Key: 3D4939898FF1A5997FE553408039239EEA795E783B821832C17954683D7D4726
Number of CPU thread: 1
Hello.
Tell me, you can somehow in VanitySearch v1.18
Set a different initial search range for the key.?
For example CCCCCCCCCC: FFFFFFFFFFF.
I have ubuntu.
Grateful.
How would I calculate how many combinations of 16jY7q would be in 2^64 range?
You can't, because there is no direct relation between an address/pubkeyhash and its private key.
It's the fact that the address is a hashed (and encoded) public key that makes it impossible to probe/guess the range of its private key. This also applies even if you have the end/middle of an address instead of the beginning of it.
How would I calculate how many combinations of 16jY7q would be in 2^64 range?
Im having the same issue though with grid size for the 3090, I just took #cuda cores/2 and used that. Not sure if its even close but otherwise I get the illegal memory access error and error about #'s missing.
GPU: GPU #0 NVIDIA GeForce RTX 3090 (82x0 cores) Grid(5248x128)
[3777.30 Mkey/s][GPU 3777.30 Mkey/s]
Is that running a search for a full address? Or multiple full addresses? Or just a partial address string? GPU: GPU #0 NVIDIA GeForce RTX 3090 (82x0 cores) Grid(5248x128)
[3777.30 Mkey/s][GPU 3777.30 Mkey/s]
Im having the same issue though with grid size for the 3090, I just took #cuda cores/2 and used that. Not sure if its even close but otherwise I get the illegal memory access error and error about #'s missing.
GPU: GPU #0 NVIDIA GeForce RTX 3090 (82x0 cores) Grid(5248x128)
[3777.30 Mkey/s][GPU 3777.30 Mkey/s]
GPU: GPU #0 NVIDIA GeForce RTX 3090 (82x0 cores) Grid(5248x128)
[3777.30 Mkey/s][GPU 3777.30 Mkey/s]
Crap, posted on wrong page I guess. Using vanitygen.
Switched over to vanitysearch, much much much faster!
Let me know how your 3090 works.
Crap, posted on wrong page I guess. Using vanitygen.
Switched over to vanitysearch, much much much faster!
[moderator's note: consecutive posts merged]
Crap, posted on wrong page I guess. Using vanitygen.
Switched over to vanitysearch, much much much faster!
[moderator's note: consecutive posts merged]
My gtx 1080 was doing 100mkey/s
The new rtx 3090 is doing 380mkey/s
GPU utilization is only at 33%, am I missing something here or is this expected?
The 2080 TI did. around 1500 mk
So what was the problem why it didn’t work b4?
So I’ve been following you guys for a while and have had excellent results with vanitygen as well as oclvantiygen-plus.
I’ve finally got my hands on a rtx 3090 and after many hours got it running in both programs but it’s only working at a rate 3 times better than my old gtx 1080.
My gtx 1080 was doing 100mkey/s
The new rtx 3090 is doing 380mkey/s
GPU utilization is only at 33%, am I missing something here or is this expected?
Are you using VanitySearch or a variation of VanGen? I’ve finally got my hands on a rtx 3090 and after many hours got it running in both programs but it’s only working at a rate 3 times better than my old gtx 1080.
My gtx 1080 was doing 100mkey/s
The new rtx 3090 is doing 380mkey/s
GPU utilization is only at 33%, am I missing something here or is this expected?
So I’ve been following you guys for a while and have had excellent results with vanitygen as well as oclvantiygen-plus.
I’ve finally got my hands on a rtx 3090 and after many hours got it running in both programs but it’s only working at a rate 3 times better than my old gtx 1080.
My gtx 1080 was doing 100mkey/s
The new rtx 3090 is doing 380mkey/s
GPU utilization is only at 33%, am I missing something here or is this expected?
I’ve finally got my hands on a rtx 3090 and after many hours got it running in both programs but it’s only working at a rate 3 times better than my old gtx 1080.
My gtx 1080 was doing 100mkey/s
The new rtx 3090 is doing 380mkey/s
GPU utilization is only at 33%, am I missing something here or is this expected?
Has anyone put together (or started to put together) a list of CPUs / Video Cards & the speed you can get out of them.
I know it's a newer project and Jean_Luc is working VERY VERY hard on it so getting accurate numbers is going to be a moving target. But for now all we can do is look through the thread and see who is running what to get a general idea.
So far I have pulled from this thread:
GPU: GPU #0 GeForce GTX 1080 Ti (28x128 cores) Grid(224x128)
914.418 MK/s (GPU 896.216 MK/s)
GPU: GPU #0 GeForce GTX 1050 Ti (6x128 cores) Grid(48x128)
220.180 MK/s (GPU 220.180 MK/s)
GPU: GPU #0 GeForce GT 520M (1x48 cores) Grid(8x128)
10.233 MK/s (GPU 7.026 MK/s)
GPU: GPU #0 GeForce RTX 2070 (36x64 cores) Grid(288x128)
1535.880 MK/s (GPU 1470.257 MK/s)
Added 30-April-2019
GPU: GPU #0 GeForce GTX 1060 3GB (9x128 cores) Grid(72x128)
321.929 MK/s (GPU 321.929 MK/s)
GPU: GPU #0 GeForce GTX 1080 (20x128 cores) Grid(160x128)
672.062 MK/s (GPU 672.062 MK/s)
Added 1-May-2019
GPU: GPU #0 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
GPU: GPU #3 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
GPU: GPU #2 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
GPU: GPU #1 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
7260.449 MK/s (GPU 7212.931 MK/s)
So 7260 / 4 = 1815 MK/s
GPU: GPU #0 GeForce GTX 750 (4x128 cores) Grid(32x128)
104.960 MK/s (GPU 94.405 MK/s) (2^32.12)
Added 3-May-2019
i7-7700K CPU Number of CPU thread: 8
22.092 MK/s (GPU 0.000 MK/s)
With -t 7
Number of CPU thread: 7
21.609 MK/s
Added 8-May-2019
EVGA RTX 2080 XC ULTRA
1427.967 MK/s (GPU 1424.946 MK/s)
Added 23-May-2019
GPU: GPU #0 GeForce GTX 1660 Ti
961.319 MK/s (GPU 961.319 MK/s)
GPU: GPU #0 GeForce RTX 2080 Ti (68x64 cores) Grid(544x128)
GPU: GPU #1 GeForce RTX 2080 Ti (68x64 cores) Grid(544x128)
5128.213 MK/s (GPU 5128.213 MK/s)
So 5128 / 2 = 2564 MK/s
Added 8-June-2019
GPU: GPU #0 GeForce GTX 960M (5x128 cores) Grid(40x128)
117.802 MK/s (GPU 117.802 MK/s)
Added 23-July-2019
GPU: GPU #0 GeForce GTX 1660 (22x64 cores) Grid(176x128)
839.061 MK/s (GPU 839.061 MK/s)
Added 25-July-2019
GPU: GPU #0 GeForce GTX 1650 (14x64 cores) Grid(112x128)
511.906 MK/s (GPU 511.906 MK/s) (2^36.97)
Added 21-Nov-2019
GPU: GPU #0 GeForce GTX 970 (13x128 cores) Grid(104x128)
360.322 MK/s (GPU 331.442 MK/s) (2^32.77)
Added 25-Nov-2019
GPU: GPU #0 GeForce GTX 980 (16x128 cores) Grid(128x128)
375.384 MK/s (GPU 375.384 MK/s)
GPU: GPU #0 GeForce RTX 2060 SUPER (34x64 cores) Grid(272x256)
[1361.71 Mkey/s][GPU 1361.71 Mkey/s]
GPU: GPU #0 GeForce RTX 2080 SUPER (48x64 cores) Grid(384x256)
[2001.52 Mkey/s][GPU 2001.52 Mkey/s]
Anything else?
-Dave
Last updated 25-Nov-2019.
I know it's a newer project and Jean_Luc is working VERY VERY hard on it so getting accurate numbers is going to be a moving target. But for now all we can do is look through the thread and see who is running what to get a general idea.
So far I have pulled from this thread:
GPU: GPU #0 GeForce GTX 1080 Ti (28x128 cores) Grid(224x128)
914.418 MK/s (GPU 896.216 MK/s)
GPU: GPU #0 GeForce GTX 1050 Ti (6x128 cores) Grid(48x128)
220.180 MK/s (GPU 220.180 MK/s)
GPU: GPU #0 GeForce GT 520M (1x48 cores) Grid(8x128)
10.233 MK/s (GPU 7.026 MK/s)
GPU: GPU #0 GeForce RTX 2070 (36x64 cores) Grid(288x128)
1535.880 MK/s (GPU 1470.257 MK/s)
Added 30-April-2019
GPU: GPU #0 GeForce GTX 1060 3GB (9x128 cores) Grid(72x128)
321.929 MK/s (GPU 321.929 MK/s)
GPU: GPU #0 GeForce GTX 1080 (20x128 cores) Grid(160x128)
672.062 MK/s (GPU 672.062 MK/s)
Added 1-May-2019
GPU: GPU #0 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
GPU: GPU #3 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
GPU: GPU #2 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
GPU: GPU #1 Tesla V100-SXM2-16GB (80x64 cores) Grid(640x128)
7260.449 MK/s (GPU 7212.931 MK/s)
So 7260 / 4 = 1815 MK/s
GPU: GPU #0 GeForce GTX 750 (4x128 cores) Grid(32x128)
104.960 MK/s (GPU 94.405 MK/s) (2^32.12)
Added 3-May-2019
i7-7700K CPU Number of CPU thread: 8
22.092 MK/s (GPU 0.000 MK/s)
With -t 7
Number of CPU thread: 7
21.609 MK/s
Added 8-May-2019
EVGA RTX 2080 XC ULTRA
1427.967 MK/s (GPU 1424.946 MK/s)
Added 23-May-2019
GPU: GPU #0 GeForce GTX 1660 Ti
961.319 MK/s (GPU 961.319 MK/s)
GPU: GPU #0 GeForce RTX 2080 Ti (68x64 cores) Grid(544x128)
GPU: GPU #1 GeForce RTX 2080 Ti (68x64 cores) Grid(544x128)
5128.213 MK/s (GPU 5128.213 MK/s)
So 5128 / 2 = 2564 MK/s
Added 8-June-2019
GPU: GPU #0 GeForce GTX 960M (5x128 cores) Grid(40x128)
117.802 MK/s (GPU 117.802 MK/s)
Added 23-July-2019
GPU: GPU #0 GeForce GTX 1660 (22x64 cores) Grid(176x128)
839.061 MK/s (GPU 839.061 MK/s)
Added 25-July-2019
GPU: GPU #0 GeForce GTX 1650 (14x64 cores) Grid(112x128)
511.906 MK/s (GPU 511.906 MK/s) (2^36.97)
Added 21-Nov-2019
GPU: GPU #0 GeForce GTX 970 (13x128 cores) Grid(104x128)
360.322 MK/s (GPU 331.442 MK/s) (2^32.77)
Added 25-Nov-2019
GPU: GPU #0 GeForce GTX 980 (16x128 cores) Grid(128x128)
375.384 MK/s (GPU 375.384 MK/s)
GPU: GPU #0 GeForce RTX 2060 SUPER (34x64 cores) Grid(272x256)
[1361.71 Mkey/s][GPU 1361.71 Mkey/s]
GPU: GPU #0 GeForce RTX 2080 SUPER (48x64 cores) Grid(384x256)
[2001.52 Mkey/s][GPU 2001.52 Mkey/s]
Anything else?
-Dave
Last updated 25-Nov-2019.
Actually i think especially in regards to the cuda version of bitcrack, the number of cuda cores for the specific card is really important, and there is actually a bunch of older cards with some great numbers here, for ex. the GTX 680 have 1536 cuda cores, which also happends to be the number of cuda cores for the GTX 770.
For comparison other cards cuda cores:
RTX 2080 TI - 4352
GTX 1080 TI - 3583
RTX 2080 Super - 3072
RTX 2080 Gaming - 2944
GTX 780 TI - 2880
GTX 980 TI - 2816
GTX 2070 TI - 2560
GTX 1080 - 2560
RTX 2070 Gaming - 2304
GTX 780 - 2304
RTX 2060 Super - 2176
GTX 980 - 2048
RTX 2060 - 1920
GTX 1070 - 1920
GTX 1060 1708
GTX 1660 TI - 1536
GTX 770 - 1536
GTX 680 - 1536
GTX 1660 Dual OC - 1408
GTX 670 - 1344
GTX 1660 Armor - 1280
GTX 1060 - 1152
GTX 760 - 1152
GTX 1650 - 896
GTX 1050 TI - 768
GTX 1050 - 640
GTX 580 - 512
I assume it won’t run on an intel Mac, though, so I will have to run it on my raspberry pie alongside my full node....? Poor little guy... Is that even possible since it’s not intel?
Might have to create a virtual Linux box just for this, it’s that cool!
Might have to create a virtual Linux box just for this, it’s that cool!
Theoretically, you can get it to work on MacOS but you have to compile the Linux version on it in XCode and define more macros for the sections that have compile errors. For example, those __mul128 and __div128 instructions but I have no clue if XCode recognizes them (Windows MSVC does not).
It will definitely not run on a Pi, since it's an ARM device.
Any idea what kind of gpu i need and how difficult/custom i can get ? how long with one 3080 for address like 1Bitcoin.... ? Thanks
There's a link in the OP of benchmarks reported by some users, here's the link: /index.php?topic=5112311.msg50823897#msg50823897But it also depends on your luck, it may be faster or slower than the displayed ETA.
For reference, a GPU with 1000 MK/s would roughly search 50% of the search-space of "1Bitcoin....." in 10hours.
That's an average of 5-15± hours.
Any idea what kind of gpu i need and how difficult/custom i can get ? how long with one 3080 for address like 1Bitcoin.... ? Thanks
If you have a 3080 just run it; the program will tell you how long/difficulty. For 1 Bitcoin, not too long.
Any idea what kind of gpu i need and how difficult/custom i can get ? how long with one 3080 for address like 1Bitcoin.... ? Thanks
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