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Showing 20 of 42 results by Marynarz
Hi,
I would like to add the hashrate sharing option to another mine in the Antminer L3+ firmware, will anyone be willing to do it? I am not interested in ready-made modifications from Russian websites, but in adding this option to the original firmware.
Sorry in advance if this is a bad department.
I would like to add the hashrate sharing option to another mine in the Antminer L3+ firmware, will anyone be willing to do it? I am not interested in ready-made modifications from Russian websites, but in adding this option to the original firmware.
Sorry in advance if this is a bad department.
Re: SEGWIT LTC.TBDICE.ORG 0.5% fee SOLO MM LTC/DGE POOL 3K+ LTC/7K+ DGE blks solved
I have no payout. 2 days before I send an application to GD National Police.
I'm really curious how that is going to work out for you.
Fee address active https://chain.so/address/DOGE/DFeviTwbDbJXgjPRS6zxe74Z4hodvRrTKP
Last activity 4 mar 2021.
I waiting my payout 6+ months.
I need to economy on simple things, but pool op thinking all is good.
I waiting payout of this blocks another 2 days, then i open an application. I think time to visit GD National Police.
19946 19915 19914 19913 19912 19778 19714 19713 19712
19707 19695 19693 19690 19689 19688 19685 19684 19667
19614 19613 19600
I think they interested in that, now my losts ~91500 USD.
DOGE wallet i used to mining: DA25CpemT7UmvJwLDGZRUSugxPkUUzf72p (split-mined confirmed blocks with LW2c3axqLoGrcBf5gzzEW614AYGuvsbkuL litecoin address)
That's a big shame to beg my own money from thief.
What the unscrupulous act from loshia - stealing money from all pool users.
Legendary member of bitcointalk...
Whats a shame. No words.
People have fair mined 4 000 000 DOGE on fee address, and + more stealed split mined blocks of coins stored in pool wallet.dat, and cant payout money of some users in this theme. Thats really stupid situation.
Download DOGE wallet.dat from pool and see how many blocks of DOGE you stealed from moment of pool establishment.
When miner find both Litecoin and DOGE blocks, and DOGE confirmed blocks no payout to users DOGE address, and stored in the pool wallet.
Did you set the correct path in the password "x:doge address" ?
On the page it says "If you do not put the DOGE address in the password, the DOGE earnings will be generated on: DFeviTwbDbJXgjPRS6zxe74Z4hodvRrTKP and will be treated as donations in the pool.
Any invalid usernames for LTC will turn RED on the Users page, if you do not have a DOGE address in your password, the MM address on the Users page will be Pool. If you have it correct, it will say Self. "
Re: SEGWIT LTC.TBDICE.ORG 0.5% fee SOLO MM LTC/DGE POOL 3K+ LTC/7K+ DGE blks solved
Re: SEGWIT LTC.TBDICE.ORG 0.5% fee SOLO MM LTC/DGE POOL 3K+ LTC/7K+ DGE blks solved
Hola,
What are your experiences with this mine? Is it solvent? I read a lot of opinions about it, but some people write that it pays, while others say that it is a scam.
What are your experiences with this mine? Is it solvent? I read a lot of opinions about it, but some people write that it pays, while others say that it is a scam.
Re: Wallet lost after windows installation? Used portable version.
I recommend it for data recovery https://sourceforge.net/projects/lparted/
Compile with ccap=35 and then see the result. Then try to set grid 30,768.
https://en.m.wikipedia.org/wiki/Thread_block_(CUDA_programming)
https://en.m.wikipedia.org/wiki/Thread_block_(CUDA_programming)
30,768,30,768
Code:
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
I set 175,256,175,256 and my image in the monitor turned black and sometimes it flashed to a delicate white color, after restart the image works, does it mean that this card is damaged? is it simply the fault of the drivers?
Code:
Kangaroo v2.2
GPU #0 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)
GPU #1 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)
GPU #0 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)
GPU #1 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)
Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.
Does anyone know why my speed is so small, the card is GTX Titan Z.
At the beginning of the process, the speed was the same ?
Avoid to have too large hashtable in RAM even if you have enough RAM on your system, it is preferable to use -wsplit and merge workfile offline.
Unfortunately I am not using Kangaroo in server mode.
A few days ago I bought a Titan card and wanted to resume working (previously I used 2 x ASUS GTX 1060 6GB = 460 MK/s) and to my surprise this speed is from the start and no matter what DP is set. I have the latest graphics drivers installed and CUDA 10.2 and the truth is, my hands are dropping, I have no idea where the problem is. Will there be any good soul to help solve this problem?
My motherboard is ASUS CROSSHAIR V FORMULA-Z,
16 GB RAM,
Corsair 850W power supply
AMD FX 8350 processor
I will be very grateful for any help.
Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.
i run kangaroo like this
Does anyone know why my speed is so small, the card is GTX Titan Z.
i run kangaroo like this
Code:
Kangaroo.exe -t 0 -d 28 -gpu -gpuId 0,1 -ws -i save.work4 -w save.work4 -wi 600 -o found.txt in2.txt
Code:
Kangaroo v2.2
Loading: save.work4
Start:0
Stop :7FFFFFFFFFFFFFFFFFFFFF
Keys :1
LoadWork: [HashTable 3.0/3.7GB] [20s]
Number of CPU thread: 0
Range width: 2^87
Jump Avg distance: 2^42.96
Number of kangaroos: 2^21.49
Suggested DP: 19
Expected operations: 2^46.56
Expected RAM: 26.7MB
DP size: 28 [0xFFFFFFF000000000]
GPU: GPU #0 GeForce GTX TITAN Z (15x192 cores) Grid(30x384) (119.5 MB used)
SolveKeyGPU Thread GPU#0: creating kangaroos...
GPU: GPU #1 GeForce GTX TITAN Z (15x192 cores) Grid(30x384) (119.5 MB used)
SolveKeyGPU Thread GPU#1: creating kangaroos...
SolveKeyGPU Thread GPU#1: 2^20.49 kangaroos [10.0s]
SolveKeyGPU Thread GPU#0: 2^20.49 kangaroos [10.1s]
[324.91 MK/s][GPU 324.91 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 3.7d)][3.0/3.7G
[512.78 MK/s][GPU 512.78 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.3d)][3.0/3.7G
[520.19 MK/s][GPU 520.19 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.3d)][3.0/3.7G
[484.27 MK/s][GPU 484.27 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.5d)][3.0/3.7G
[452.12 MK/s][GPU 452.12 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.7d)][3.0/3.7G
[429.34 MK/s][GPU 429.34 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.8d)][3.0/3.7G
[416.00 MK/s][GPU 416.00 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[407.24 MK/s][GPU 407.24 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.43 MK/s][GPU 410.43 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[408.74 MK/s][GPU 408.74 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.46 MK/s][GPU 411.46 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.52 MK/s][GPU 410.52 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.84 MK/s][GPU 411.84 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.98 MK/s][GPU 411.98 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.49 MK/s][GPU 410.49 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
Loading: save.work4
Start:0
Stop :7FFFFFFFFFFFFFFFFFFFFF
Keys :1
LoadWork: [HashTable 3.0/3.7GB] [20s]
Number of CPU thread: 0
Range width: 2^87
Jump Avg distance: 2^42.96
Number of kangaroos: 2^21.49
Suggested DP: 19
Expected operations: 2^46.56
Expected RAM: 26.7MB
DP size: 28 [0xFFFFFFF000000000]
GPU: GPU #0 GeForce GTX TITAN Z (15x192 cores) Grid(30x384) (119.5 MB used)
SolveKeyGPU Thread GPU#0: creating kangaroos...
GPU: GPU #1 GeForce GTX TITAN Z (15x192 cores) Grid(30x384) (119.5 MB used)
SolveKeyGPU Thread GPU#1: creating kangaroos...
SolveKeyGPU Thread GPU#1: 2^20.49 kangaroos [10.0s]
SolveKeyGPU Thread GPU#0: 2^20.49 kangaroos [10.1s]
[324.91 MK/s][GPU 324.91 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 3.7d)][3.0/3.7G
[512.78 MK/s][GPU 512.78 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.3d)][3.0/3.7G
[520.19 MK/s][GPU 520.19 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.3d)][3.0/3.7G
[484.27 MK/s][GPU 484.27 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.5d)][3.0/3.7G
[452.12 MK/s][GPU 452.12 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.7d)][3.0/3.7G
[429.34 MK/s][GPU 429.34 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.8d)][3.0/3.7G
[416.00 MK/s][GPU 416.00 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[407.24 MK/s][GPU 407.24 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.43 MK/s][GPU 410.43 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[408.74 MK/s][GPU 408.74 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.46 MK/s][GPU 411.46 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.52 MK/s][GPU 410.52 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.84 MK/s][GPU 411.84 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.98 MK/s][GPU 411.98 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.49 MK/s][GPU 410.49 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G