Awesome
gominer
gominer is an application for performing Proof-of-Work (PoW) mining on the Decred network after the activation of DCP0011 using BLAKE3. It supports solo and stratum/pool mining using OpenCL and CUDA devices.
Downloading
Binaries are not currently available. See the Building
(Windows, Linux) section for details on how to build
gominer
from source.
Configuring gominer
gominer
needs to acquire work in order to have something to solve. Currently, the only supported method is solo mining via a dcrd
RPC server. There are plans to support dcrpool for pooled mining in the future.
In order to communicate with the dcrd
RPC server, gominer
must be configured
with dcrd
's RPC server credentials.
- Obtain the RPC username and password by finding the
rpcuser
andrpcpass
entries in thedcrd.conf
file- Windows:
%LOCALAPPDATA%\Dcrd\dcrd.conf
- Linux:
~/.dcrd/dcrd.conf
- MacOs:
~/Library/Application Support/Dcrd/dcrd.conf
- Windows:
- Create a
gominer.conf
file at the platform-specific path that contains the exact samerpcuser=
andrpcpass=
lines you obtained from thedcrd.conf
file in the previous step- Windows:
%LOCALAPPDATA%\Gominer\gominer.conf
- Linux:
~/.gominer/gominer.conf
- MacOS:
~/Library/Application Support/Gominer/gominer.conf
- The
gominer.conf
config file should have at least the following lines:
rpcuser=<same rpcuser from dcrd.conf> rpcpass=<same rpcpass from dcrd.conf>
- Windows:
Next, dcrd
must be configured with a mining address to send the payment for
mined blocks. That is accomplished by either launching dcrd
with the
--miningaddr=Ds...
CLI flag or adding a miningaddr=Ds...
to the
aforementioned dcrd.conf
file and restarting dcrd
.
Running
Benchmark mode
gominer
provides a benchmark mode where no work is submitted in order to test
your setup.
gominer -B
Solo Mining on Mainnet
Ensure you have configured gominer
with dcrd
's RPC
credentials as well as dcrd
with a miningaddr
. Once the credentials and
mining address have been configured, simply run gominer to begin mining.
gominer
Stratum/pool Mining on Mainnet
Mining with a Pool Based on Dcrpool
The username for pools running dcrpool is
the payment address for receiving rewards and a unique name identifying the
client formatted as address.name
.
Run the following command replacing the pooldomain:port
with the appropriate
domain name and port of the desired pool to connect to and the address.name
as previously described:
gominer --pool stratum+tcp://pooldomain:port --pooluser address.name
General Pool Mining
There is no other known pool software aside from
dcrpool, that supports the latest Decred
consensus rules at the current time. However, as long as the pool software
supports the stratum protocol with the same semantics implemented by dcrpool
,
the following command should serve as a starting point:
gominer --pool stratum+tcp://pooldomain:port --pooluser username --poolpass password
Status API
There is a built-in status API to report miner information. You can set an
address and port with --apilisten
. There are configuration examples on
sample-gominer.conf. If no port is specified, then it
will listen by default on 3333
.
Example usage:
$ gominer --apilisten="localhost"
Example output:
$ curl http://localhost:3333/
> {
"validShares": 0,
"staleShares": 0,
"invalidShares": 0,
"totalShares": 0,
"sharesPerMinute": 0,
"started": 1504453881,
"uptime": 6,
"devices": [{
"index": 2,
"deviceName": "GeForce GT 750M",
"deviceType": "GPU",
"hashRate": 110127366.53846154,
"hashRateFormatted": "110MH/s",
"fanPercent": 0,
"temperature": 0,
"started": 1504453880
}],
"pool": {
"started": 1504453881,
"uptime": 6
}
}
Building
Linux
Preliminaries
Gominer works with OpenCL (both AMD and NVIDIA) and CUDA (NVIDIA only). At the current time, most users have reported that OpenCL gives them higher hashrates on NVIDIA.
Once you decide on OpenCL or CUDA, you will need to install the graphics driver for your GPU as well as the headers for OpenCL or CUDA depending on your choice.
The exact packages are dependent on the specific Linux distribution, but, generally speaking, you will need the latest AMDGPU-PRO display drivers for AMD cards and the latest NVIDIA graphics display drivers for NVIDIA cards. Then, depending on whether you will build the OpenCL or CUDA version, the specific set of toolsets, headers and libraries will have to be installed.
For OpenCL, the packages are typically named something similar to
mesa-opencl-dev
(for AMD) or nvidia-opencl-dev
(for NVIDIA).
If you're using OpenCL, it is also recommended to install your distribution's
equivalent of the clinfo
package if you have any issues to ensure your device
can be detected by OpenCL. When clinfo
is unable to detect your device,
gominer
will not be able to either.
For CUDA, on distributions where it is available via the standard package
manager, the required files are usually found as nvidia-cuda-toolkit
. NVIDIA
also provides its own CUDA Toolkit
downloads.
The following sections provide instructions for building various combinations
of gominer
:
NVIDIA on Ubuntu 23.04
This section provides instructions for building gominer
on a computer with an
NVIDIA graphics card running Ubuntu 23.04. Both OpenCL and CUDA build
instructions are provided.
Prerequisites
The following steps are applicable for both OpenCL and CUDA builds of gominer
:
- Detect the model of your NVIDIA GPU and the recommended driver
ubuntu-drivers devices
- Install the NVIDIA graphics driver
- If you agree with the recommended drivers
sudo ubuntu-drivers autoinstall
- Alternatively, install a specific driver (for example)
sudo apt install nvidia-driver-525-server
- If you agree with the recommended drivers
- Install the basic development tools
git
andgo
sudo apt install git golang
- Reboot to allow the graphics driver to load
sudo reboot
- Obtain the
gominer
source codegit clone https://github.com/decred/gominer
- Jump to the appropriate section for either
OpenCL or CUDA
depending on which GPU library you want to build
gominer
for
OpenCL on Ubuntu
- Install the OpenCL headers
sudo apt install nvidia-opencl-dev
- Build
gominer
cd gominer
go build -tags opencl
- Test
gominer
detects your GPU(s)./gominer -l
- You may now configure and run
gominer
CUDA on Ubuntu
- Install the NVIDIA CUDA Toolkit:
sudo apt install nvidia-cuda-toolkit
- Build
gominer
:cd gominer
go generate -tags cuda .
- Test
gominer
detects your GPU(s):./gominer -l
- You may now configure and run
gominer
Debian Bookworm
This section provides instructions for building gominer
on a computer running
Debian bookworm. Both OpenCL (using either AMD or NVIDIA graphics cards)
and CUDA (NVIDIA graphics cards only) build instructions are provided.
Prerequisites
- Enable the non-free (closed source) repository by using your favorite editor
to modify
/etc/apt/sources.list
and appendingcontrib non-free
to thedeb
repository$EDITOR /etc/apt/sources.list
- It should look similar to the following
deb http://ftp.us.debian.org/debian bookworm-updates main contrib non-free deb http://security.debian.org bookworm-security main contrib non-free
- It should look similar to the following
- Update the Apt package manager with the new sources
sudo apt update
- Install the basic development tools
git
andgo
:sudo apt install git golang
- Obtain the
gominer
source codegit clone https://github.com/decred/gominer
Proceed to install the appropriate graphics card driver and supporting firmware, based on the hardware available on the computer:
- For AMD GPUs: Install the AMD graphics driver and supporting firmware
sudo apt install firmware-linux firmware-linux-nonfree libdrm-amdgpu1 xserver-xorg-video-amdgpu
- For NVIDIA GPUs: Install the NVIDIA graphics driver:
sudo apt install nvidia-driver
- Restart the computer to ensure the driver is loaded
- Jump to the appropriate section for either
OpenCL or CUDA
depending on which GPU library you want to build
gominer
for
OpenCL on Debian
This build mode supports both AMD and NVIDIA graphics cards.
- Install the OpenCL headers, OpenCL Installable Client driver and OpenCL lib
sudo apt install opencl-headers mesa-opencl-icd ocl-icd-libopencl1
- Help the loader find the OpenCL library by creating a symbolic link to it:
ln -s /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/libOpenCL.so
- Build
gominer
cd gominer
go build -tags opencl
- Test
gominer
detects your GPU(s)./gominer -l
- You may now configure and run
gominer
CUDA on Debian
Note that this requires having an NVIDIA graphics card installed on the computer.
- Install the NVIDIA CUDA Toolkit:
sudo apt install nvidia-cuda-toolkit
- Build
gominer
:cd gominer
go generate -tags cuda .
- Test
gominer
detects your GPU(s):./gominer -l
- You may now configure and run
gominer
Windows
Windows Preliminaries
Gominer works with OpenCL (both AMD and NVIDIA) and CUDA (NVIDIA only).
At the current time, most users have reported that OpenCL gives them higher
hashrates on NVIDIA. Additionally, building the CUDA-enabled version of
gominer
on Windows is a much more involved process. For these reasons, unless
you really want to run the CUDA version for a specific reason, it is recommended
to use OpenCL.
Windows Prerequisites
The following steps are applicable for both OpenCL and CUDA builds of gominer
:
- Download and install MSYS2
- Make sure you uncheck
Run MSYS2 now.
- Make sure you uncheck
- Launch the
MSYS2 MINGW64
shell from the start menu- NOTE: The
MSYS2
installer will launch theUCRT64
shell by default if you didn't uncheckRun MSYS2 now
as instructed. That shell will not work, so close it if you forgot to uncheck it in the installer.
- NOTE: The
- From within the
MSYS2 MINGW64
shell enter the following commands to installgcc
,git
,go
,unzip
:pacman -S mingw-w64-x86_64-gcc mingw-w64-x86_64-tools mingw-w64-x86_64-go git unzip
git clone https://github.com/decred/gominer
- Close the
MSYS2 MINGW64
shell and relaunch it- NOTE: This is necessary to ensure all of the new environment variables are set properly
- Jump to the appropriate section for either
OpenCL or CUDA
depending on which GPU library you want to build
gominer
for
OpenCL Prerequisites on Windows
The following is needed when performing an OpenCL build:
- Still in the
MSYS2 MINGW64
shell enter the following commands to install the light OpenCL SDK:wget https://github.com/GPUOpen-LibrariesAndSDKs/OCL-SDK/files/1406216/lightOCLSDK.zip
unzip -d /c/appsdk lightOCLSDK.zip
- Jump to the appropriate section for either OpenCL with AMD or OpenCL with NVIDIA depending on which type of GPU you have
OpenCL with AMD
- Change to the library directory C:\appsdk\lib\x86_64
cd /c/appsdk/lib/x86_64
- Copy and prepare the AMD Display Library (ADL) for linking
cp /c/Windows/SysWOW64/atiadlxx.dll .
gendef atiadlxx.dll
dlltool --output-lib libatiadlxx.a --input-def atiadlxx.def
- Build gominer
cd ~/gominer
go build -tags opencl
- Test
gominer
detects your GPU(s)./gominer -l
- You may now configure and run
gominer
OpenCL with NVIDIA
- Build gominer
cd ~/gominer
go build -tags opencl
- Test
gominer
detects your GPU(s)./gominer -l
- You may now configure and run
gominer
CUDA with NVIDIA
Building the CUDA-enabled gominer
on a Windows platform is tricky, requires
several GB worth of downloads and while we have made attempts at detecting the
necessary tools and automating the building process, it is not guaranteed to
work, in particular as newer or older versions of the various tools are
installed.
This guide has been tested on a Windows 10 machine, with an NVIDIA graphics card
installed, using Microsoft Visual Studio Community Edition 2022 and NVIDIA CUDA
Toolkit version 12.2. If the automatic builder for gominer
does not work on
your system, you many need to manually setup the various
tools.
After fulfilling the Windows prerequisites, follow the following instructions:
- Download and install the appropriate NVIDIA driver
- Download and install the NVIDIA CUDA Toolkit:
- Download and install Microsoft Visual Studio:
- https://visualstudio.microsoft.com/vs/community/
- Ensure the "Desktop Development with C++" component will be installed
- Build gominer:
go generate -tags cuda .
- The warnings about deprecated symbols are safe to ignore
- Test
gominer
detects your GPU(s):./gominer -l
- You may now configure and run
gominer
User Reported Hashrates
OpenCL
GPU | Hashrate |
---|---|
NVIDIA GTX 1060 | 3.0 Gh/s |
AMD RX 580 | 3.7 Gh/s |
NVIDIA 1660 Super | 5.0 Gh/s |
AMD Vega 56 | 7.0 Gh/s |
NVIDIA RTX 3060 Ti | 8.7 Gh/s |
NVIDIA GTX 3080 Mobile | 9.4 Gh/s |
NVIDIA RTX 3070 | 10.1 Gh/s |
NVIDIA RTX 2080 | 10.4 Gh/s |
NVIDIA Tesla V100 | 13.9 Gh/s |
NVIDIA Tesla V100S | 14.6 Gh/s |
NVIDIA RTX 4070 | 14.9 Gh/s |
NVIDIA RTX 3080 | 15.2 Gh/s |
NVIDIA RTX 3090 | 17.6 Gh/s |
AMD 7900 XTX | 23.8 Gh/s |