/gominer-release-docker

Primary LanguageCGNU General Public License v3.0GPL-3.0

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.

User Reported Hashrates

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 and rpcpass entries in the dcrd.conf file
    • Windows: %LOCALAPPDATA%\Dcrd\dcrd.conf
    • Linux: ~/.dcrd/dcrd.conf
    • MacOs: ~/Library/Application Support/Dcrd/dcrd.conf
  • Create a gominer.conf file at the platform-specific path that contains the exact same rpcuser= and rpcpass= lines you obtained from the dcrd.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>

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
  • Install the basic development tools git and go
    • sudo apt install git golang
  • Reboot to allow the graphics driver to load
    • sudo reboot
  • Obtain the gominer source code
    • git 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 appending contrib non-free to the deb 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
  • Update the Apt package manager with the new sources
    • sudo apt update
  • Install the basic development tools git and go:
    • sudo apt install git golang
  • Obtain the gominer source code
    • git 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.
  • Launch the MSYS2 MINGW64 shell from the start menu
    • NOTE: The MSYS2 installer will launch the UCRT64 shell by default if you didn't uncheck Run MSYS2 now as instructed. That shell will not work, so close it if you forgot to uncheck it in the installer.
  • From within the MSYS2 MINGW64 shell enter the following commands to install gcc, 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:

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