XMR-stak-JK 2.10.7 Compiled with no devfee (Updated: 2019-8-18)

[JaredKaragen]

Seems that there something wrong with my config, kindly check my config and tell me if Im doing it right.. My hashrate getting to low..

here's my config I don't know if I'm doing it right.

Code:

"gpu_threads_conf" : [
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 0,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
{ "index" : 0,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 1,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
{ "index" : 1,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },

Is it right?

is your problem with loading errors?

Looks like formatting;  specifically the ], on the last line which is missing....

[1715177516]

1715177516

[1715177516]

1715177516

[1715177516]

1715177516

[1715177516]

1715177516

[john1010]

Seems that there something wrong with my config, kindly check my config and tell me if Im doing it right.. My hashrate getting to low..

here's my config I don't know if I'm doing it right.

Code:

"gpu_threads_conf" : [
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 0,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
{ "index" : 0,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 1,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
{ "index" : 1,
    "intensity" : 864, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },

Is it right?

is your problem with loading errors?

Looks like formatting;  specifically the ], on the last line which is missing....

Can I post my config here, then if you don't mind, kindly edit it to the proper coding then I will copy it to my amd txt.. Is it okay dude?

Here's my whole config..

Code:

"gpu_threads_conf" : [
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 0,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 1,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 2,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 3,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 4,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 5,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 6,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 7,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 8,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 9,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 10,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 11,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },

],

[JaredKaragen]

*snip*

Code:

"gpu_threads_conf" : [
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 0,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 0,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 1,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 1,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 2,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 2,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 3,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 3,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 4,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 4,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 5,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 5,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 6,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 6,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 7,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 7,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 8,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 8,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 9,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 9,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 10,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 10,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 11,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 11,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },

],

just copy/paste to double the threads.

Its up to you to figure out any intensity or worksize changes.....  I don't have the hardware to test.

[john1010]

*snip*

Code:

"gpu_threads_conf" : [
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 0,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 0,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 1,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 1,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 2,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 2,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 3,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 3,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 4,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 4,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 5,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 5,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 6,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 6,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 7,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 7,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 8,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 8,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 9,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 9,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3712
  // compute units: 32
  { "index" : 10,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 10,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  // gpu: Ellesmere memory:3920
  // compute units: 32
  { "index" : 11,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },
  { "index" : 11,
    "intensity" : 997, "worksize" : 8,
    "affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
    "comp_mode" : true
  },

],

just copy/paste to double the threads.

Its up to you to figure out any intensity or worksize changes.....  I don't have the hardware to test.

Thanks for your help, yeah that intensity running fine in my rig.. I will post an update of what the result I got.

[impynick]

https://bitcointalk.org/index.php?topic=3370685.0

Hey JK, I know you have a 1080ti, I thought you and anyone else using the 1080ti find this useful

I used ethlargement on my 1080 ti (link above) and my hash rate when from 930 to 1070. Check it out lmk what you think.

I have pics of said hash rate as well if you want documentation. Just run it in the background of XMR Stak and thats it!

U should get around 10-20% increase. ONLY ON 1080TI

edit: I did upload my config to xmrstak.com so check it out if you'd like. It should be up in a day or two they usually review submissions first.

[impynick]

Hi JK hope all is well; I just compiled 2.5 with VS17 and CUDA 10.

Guys just so you know compiling this miner isn't really difficult. You will learn alot just by compiling it yourself. I did this and I have 0 coding or programming experience.

https://github.com/fireice-uk/xmr-stak/blob/master/doc/compile_Windows.md

https://www.youtube.com/watch?v=8-V0eonlpD8

I used these as guides to compile. Anyways 2.5 is working but you will notice a slight drop in hash rate most likely due to the new algo. Make sure to update before 10/18!

[JaredKaragen]

Hi JK hope all is well; I just compiled 2.5 with VS17 and CUDA 10.

Guys just so you know compiling this miner isn't really difficult. You will learn alot just by compiling it yourself. I did this and I have 0 coding or programming experience.

https://github.com/fireice-uk/xmr-stak/blob/master/doc/compile_Windows.md

https://www.youtube.com/watch?v=8-V0eonlpD8

I used these as guides to compile. Anyways 2.5 is working but you will notice a slight drop in hash rate most likely due to the new algo. Make sure to update before 10/18!

Ahh, they finally released an update.... I've been waiting for this....

I have a separate machine on my main network now I can remote into and have a fresh start with installing VS and the toolkits; and it wont have bandwidth limits like I do at home.  Ill probably get on this soon.

Then the regular stripping of devfee addresses and setting value to 0.0 and compile.

I believe the original intent was Cuda 8.0, and i believe it produced the best hashrates... but i could be wrong.

Looks like I need to get on this tomorrow.  Ill be updating my personal miner with the official release for the short term.

[JaredKaragen]

good news guys, it did compile this time.  I used a fresh new PC.  Everything went well.   Usual changes;  removed donate address and set amount to 0.0.


The not so good news is I compiled under Cuda 10.

Gonna need to update your video drivers most-likely.

I am downloading the updated video drivers at home right now.   Once I get the miner app confirmed mining on my 1080;  Ill upload to mega and update Post #1.

[impynick]

Nice! Yeah I used cuda 10 as well. Good thing u waited i recompiled 2.5.1 this time luckily it took only 10 min.


If I run into any issues with my miner I have your's to fall back on

[JaredKaragen]

Nice! Yeah I used cuda 10 as well. Good thing u waited i recompiled 2.5.1 this time luckily it took only 10 min.


If I run into any issues with my miner I have your's to fall back on

Yep =)

Went smoothly.  May have something to do with my laptop I had used previously.  The laptop I used this time took ~17 min to compile... but its also running a steamcmd server.... lol.


First post updated.  New version works.

[Hamliss]

Hi JK hope all is well; I just compiled 2.5 with VS17 and CUDA 10.

Guys just so you know compiling this miner isn't really difficult. You will learn alot just by compiling it yourself. I did this and I have 0 coding or programming experience.

https://github.com/fireice-uk/xmr-stak/blob/master/doc/compile_Windows.md

https://www.youtube.com/watch?v=8-V0eonlpD8

I used these as guides to compile. Anyways 2.5 is working but you will notice a slight drop in hash rate most likely due to the new algo. Make sure to update before 10/18!

Ahh, they finally released an update.... I've been waiting for this....

I have a separate machine on my main network now I can remote into and have a fresh start with installing VS and the toolkits; and it wont have bandwidth limits like I do at home.  Ill probably get on this soon.

Then the regular stripping of devfee addresses and setting value to 0.0 and compile.

I believe the original intent was Cuda 8.0, and i believe it produced the best hashrates... but i could be wrong.

Looks like I need to get on this tomorrow.  Ill be updating my personal miner with the official release for the short term.

Thanks for all the efforts. You said you comipled with CUDA, does the miner also work with AMD cards properly?

[JaredKaragen]

Yeah, AMD backend is still as per normal from what I can tell.    Its working with the RX560 in my test rig consisting of a number of mixed AMD/Nvidia/legacy.

If you have any amd issues, its most likely driver related;  and I would recommend to read the alerts on the fireice-uk github at the source about the driver issues people have had;  I saw the alert when I was reading the release notes before compiling.




For those of you whom can't/won't update driver for some reason; you can download the official release from github, and copy the xmrstak_cuda_backend.dll file, but rename it to xmrstak_cuda_backend_cuda9_2.dll and put it in the folder with my release.   This will give you library support for the older drivers/devices as it was with 2.4.x

I had to do this because if I install nvidia driver 400+, my older legacy devices (GTX 5-series and older) will not load a driver in windows.   The require the 3xx version of the nvidia driver to work....   This copying of fireice-uk's cuda DLL is a good alternative.

[MagicSmoker]

I just got 2.5.1-JK running on two different rigs and it was painless for one and quite painful for the other. The painless one is my "daily driver" desktop with a single RX 570 and Ryzen 5 1600, Windows 10 1803 (ie - just got the fall update), AMD 18.5.1 driver, and MSI AB 4.4.0 set to -25% power, 1200 core and 1900 mem.

The problematic rig is 4x RX 560 2GB on an Onda D1800 6-GPU mining mobo running Windows 10 1709 (ie - NOT updated), AMD 18.6.1 (ie - newer driver) and uses OverDrivenTool to setup the GPUs rather than MSI AB. This rig kept crashing either during the bin file compiling or as soon as it logged into the pool. After wrestling with different things for an hour I finally tried bumping up all the voltages in the mem and core clock profiles by 25mV and that stopped the crashing. Of course, that increases the power consumption slightly, but the hashrate is otherwise the same (this is mining Lethean (formerly IntenseCoin), which is still running what is essential CNv7).

[Joz76]

Hi, I'm new with XMR-stack, plz help with the config. I want to mine with CPU and join to nanopool, but cant connect to pool with this error:

Fast-connecting to xmr-eu1.nanopool.org:14433 pool ...
Pool xmr-eu1.nanopool.org:14433 connected. Logging in...
SOCKET ERROR - [xmr-eu1.nanopool.org:14433] RECEIVE error: socket closed

My bat file is this:
xmr-stak.exe -o xmr-eu1.nanopool.org:14433 -u myaddress.cpu_gamer/joz976@gmail.com --currency monero -i 0 -p "" -r "" --noNVIDIA --noUAC

and this is my config file:
/ generated by xmr-stak/2.5.1/4e72408ff/master/win/nvidia-amd-cpu/20

/*
 * Network timeouts.
 * Because of the way this client is written it doesn't need to constantly talk (keep-alive) to the server to make
 * sure it is there. We detect a buggy / overloaded server by the call timeout. The default values will be ok for
 * nearly all cases. If they aren't the pool has most likely overload issues. Low call timeout values are preferable -
 * long timeouts mean that we waste hashes on potentially stale jobs. Connection report will tell you how long the
 * server usually takes to process our calls.
 *
 * call_timeout - How long should we wait for a response from the server before we assume it is dead and drop the connection.
 * retry_time   - How long should we wait before another connection attempt.
 *                Both values are in seconds.
 * giveup_limit - Limit how many times we try to reconnect to the pool. Zero means no limit. Note that stak miners
 *                don't mine while the connection is lost, so your computer's power usage goes down to idle.
 */
"call_timeout" : 10,
"retry_time" : 30,
"giveup_limit" : 0,

/*
 * Output control.
 * Since most people are used to miners printing all the time, that's what we do by default too. This is suboptimal
 * really, since you cannot see errors under pages and pages of text and performance stats. Given that we have internal
 * performance monitors, there is very little reason to spew out pages of text instead of concise reports.
 * Press 'h' (hashrate), 'r' (results) or 'c' (connection) to print reports.
 *
 * verbose_level - 0 - Don't print anything.
 *                 1 - Print intro, connection event, disconnect event
 *                 2 - All of level 1, and new job (block) event if the difficulty is different from the last job
 *                 3 - All of level 1, and new job (block) event in all cases, result submission event.
 *                 4 - All of level 3, and automatic hashrate report printing
 *
 * print_motd    - Display messages from your pool operator in the hashrate result.
 */
"verbose_level" : 3,
"print_motd" : true,

/*
 * Automatic hashrate report
 *
 * h_print_time - How often, in seconds, should we print a hashrate report if verbose_level is set to 4.
 *                This option has no effect if verbose_level is not 4.
 */
"h_print_time" : 60,

/*
 * Manual hardware AES override
 *
 * Some VMs don't report AES capability correctly. You can set this value to true to enforce hardware AES or
 * to false to force disable AES or null to let the miner decide if AES is used.
 *
 * WARNING: setting this to true on a CPU that doesn't support hardware AES will crash the miner.
 */
"aes_override" : null,

/*
 * LARGE PAGE SUPPORT
 * Large pages need a properly set up OS. It can be difficult if you are not used to systems administration,
 * but the performance results are worth the trouble - you will get around 20% boost. Slow memory mode is
 * meant as a backup, you won't get stellar results there. If you are running into trouble, especially
 * on Windows, please read the common issues in the README and FAQ.
 *
 * By default we will try to allocate large pages. This means you need to "Run As Administrator" on Windows.
 * You need to edit your system's group policies to enable locking large pages. Here are the steps from MSDN
 *
 * 1. On the Start menu, click Run. In the Open box, type gpedit.msc.
 * 2. On the Local Group Policy Editor console, expand Computer Configuration, and then expand Windows Settings.
 * 3. Expand Security Settings, and then expand Local Policies.
 * 4. Select the User Rights Assignment folder.
 * 5. The policies will be displayed in the details pane.
 * 6. In the pane, double-click Lock pages in memory.
 * 7. In the Local Security Setting – Lock pages in memory dialog box, click Add User or Group.
 * 8. In the Select Users, Service Accounts, or Groups dialog box, add an account that you will run the miner on
 * 9. Reboot for change to take effect.
 *
 * Windows also tends to fragment memory a lot. If you are running on a system with 4-8GB of RAM you might need
 * to switch off all the auto-start applications and reboot to have a large enough chunk of contiguous memory.
 *
 *
 * use_slow_memory defines our behaviour with regards to large pages. There are three possible options here:
 * always  - Don't even try to use large pages. Always use slow memory.
 * warn    - We will try to use large pages, but fall back to slow memory if that fails.
 * never   - If we fail to allocate large pages we will print an error and exit.
 */
"use_slow_memory" : "warn",

/*
 * TLS Settings
 * If you need real security, make sure tls_secure_algo is enabled (otherwise MITM attack can downgrade encryption
 * to trivially breakable stuff like DES and MD5), and verify the server's fingerprint through a trusted channel.
 *
 * tls_secure_algo - Use only secure algorithms. This will make us quit with an error if we can't negotiate a secure algo.
 */
"tls_secure_algo" : true,

/*
 * Daemon mode
 *
 * If you are running the process in the background and you don't need the keyboard reports, set this to true.
 * This should solve the hashrate problems on some emulated terminals.
 */
"daemon_mode" : false,

/*
 * Output file
 *
 * output_file  - This option will log all output to a file.
 *
 */
"output_file" : "",

/*
 * Built-in web server
 * I like checking my hashrate on my phone. Don't you?
 * Keep in mind that you will need to set up port forwarding on your router if you want to access it from
 * outside of your home network. Ports lower than 1024 on Linux systems will require root.
 *
 * httpd_port - Port we should listen on. Default, 0, will switch off the server.
 */
"httpd_port" : 0,

/*
 * HTTP Authentication
 *
 * This allows you to set a password to keep people on the Internet from snooping on your hashrate.
 * Keep in mind that this is based on HTTP Digest, which is based on MD5. To a determined attacker
 * who is able to read your traffic it is as easy to break a bog door latch.
 *
 * http_login - Login. Empty login disables authentication.
 * http_pass  - Password.
 */
"http_login" : "",
"http_pass" : "",

/*
 * prefer_ipv4 - IPv6 preference. If the host is available on both IPv4 and IPv6 net, which one should be choose?
 *               This setting will only be needed in 2020's. No need to worry about it now.
 */
"prefer_ipv4" : true,


Before mxr-stak i use Claymore CPU miner 4.0, but claymore dont update to the new algo :-(

[impynick]

try using port 14444

[Joz76]

try using port 14444

It works, thanks!

[JaredKaragen]

try using port 14444

yes;  I myself am having issues connecting to nanopool with the TLS settings, and instead am having to choose the standard stratum port for more reliable connections.

Other than that, the switchover seems to be going well.

Look at the network hashrate;  Just on nanopool: from 138Gh to just 33Gh after the fork.....   Shows there are some damned greedy people out there.

Hope they like their bricks.

[STT]

Greed is no surprise, people will just mine whatever makes them the most returns.    Alot of them dont have a choice because the income is required pay off the asset cost of the hardware.   Cant really expect any different really, usually evens out in the end depending on which path is more useful to society overall

[Efemen]

JK, what is your 1080Ti speed for the V8 and the power consumption?

[JaredKaragen]

JK, what is your 1080Ti speed for the V8 and the power consumption?

I have yet to run it on a 1080ti, or hook a power meter up....   I suggest give it a go and share results if anyone has them.   As well as the gpu threads/intensity settings they used =)