This is the main client component from qubic.li. It connects to the backend API and receives tasks to perform.
Warning
This information is for the deprecated client version <3.0
. Please update to to latest version.
The Client runs on Docker, Windows and Linux. Below you find the instructions how to use it.
- Security Warning
- Pool Mining
- Download
- What's needed
- Windows
- Linux Option 1: Run qli-Client in a Linux Screen
- Linux option 2: Run qli-Client as Linux Service (Expert)
a. Ubuntu 22.04
b. Debian 12
c. Redhat Enterprise 8.8
d. Monitoring
e. Remove Client - HiveOs
- Appsettings.json Customization a. Trainer Options
- Troubleshooting
The client is able to download runners, which then performs the AI Training tasks. This can potentially be used in a bad manner. Run the client with the least priviliges which are possble. e.g. on windows NOT as Admininstrator; on linux NOT as root.
Find more information about the "principle of least privilege" on wikipedia: https://en.wikipedia.org/wiki/Principle_of_least_privilege
If you don't want to operate your own Qubic infrastructure. You can join the qubic.li pool mining. You can either register an account (highly recomended) on http://pool.qubic.li or you can join pool mining register-less. The simplest way to join is to create an account and login to https://pool.qubic.li, follow the instructions after you have logged in there.
With the qli pools you can choose between PPS (Pay Per Share) or solo training. With PPS the revenue for Qubic is delayed one week but has advantages for smaller environments. It is also allowed to run some workers as PPS and others as solo training where you will see revenue only when you find valid Qubic Solutions.
To Enable/Disable PPS use either "isPps": true
or "isPps": false
in your settings.
We recommend to use our Client Setup Configurator: https://pool.qubic.li/en-US/setup
If you want registration-less pool mining, do the following:
- Create a Qubic Id (e.g. on https://wallet.qubic.li)
- Download Client from below (Version >=1.2)
- Start your Client with
qli-Client <QUBICID> <THREADS>
- Check your performance: https://app.qubic.li/public
You can also put your PayoutId into the configuration file if you don't want to use command line arguments.
We recommend to update your Version if there is a change in the Minor Version (e.g. from 1.3 to 1.4). Bugfix releases (e.g. from 1.3.1 to 1.3.2) are optional.
The QLI Client is the pool client and connects to the pool.
OS | Platform | Version | Download | Description |
---|---|---|---|---|
Windows | x64 | 2.2.1 | https://dl.qubic.li/downloads/qli-Client-2.2.1-Windows-x64.zip | |
Windows | x64 | 2.2.1 | https://dl.qubic.li/downloads/qli-Client-2.2.1-Windows-x64-Plain.zip | Version without default configuration |
Linux | x64 | 2.2.1 | https://dl.qubic.li/downloads/qli-Client-2.2.1-Linux-x64.tar.gz | |
HiveOs | x64 | 2.2.1 | https://github.com/qubic-li/hiveos/releases/download/latest/qubminer-latest.tar.gz | Please follow instructions for hiveos: https://github.com/qubic-li/hiveos (add AutoUpdate to the extra config to get latest version |
The trainer is the binary executable which is responsible for the training. The Trainer is automatically downloaded by the Client. This ensures, that you always have the latest updates and the most optimized training experience.
The following table shows the available trainers.
Type | Version Key (gpuVersion /cpuVersion ) |
Description |
---|---|---|
GPU | CUDA12 |
CUDA Version for all GPU's |
GPU | AMD |
General AMD Version (may not be available all the time; depends on the epoch) |
CPU | GENERIC |
Generic x64 CPU trainer (no specific instructions needed) |
CPU | AVX2 |
AVX2 x64 CPU trainer (AVX2 instructions needed) |
CPU | AVX512 |
AVX512 x64 CPU trainer (AVX512 instructions needed) |
CPU | SKYLAKE |
For specific Intel Lake processors (may not be available all the time) |
The runner on Windows also requires the VC Redistributable, which can be obtained from: https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist?view=msvc-170
The runner on linux needs at least GLIBC 2.31.
The CPU where you run the Client must support AVX2
or AVX512
CPU instructions.
Depending on your environment you might want to enable huge pages. This can increase your iterations per second.
The trainer will tell you what is the optimal setting when it detects a wrong value.
2024-03-16 11:34:13 INFO Trainer: WARNING: Free number of hugepages is smaller than needed, have: 10 - want: 1612 (52 x number of threads). Falling back to use malloc memory.
2024-03-16 11:34:13 INFO Trainer: To add more hugepages, please run this command as root before starting the miner
2024-03-16 11:34:13 INFO Trainer: /usr/sbin/sysctl -w vm.nr_hugepages=1612
2024-03-16 11:34:13 INFO Trainer: OR: /sbin/sysctl -w vm.nr_hugepages=1612
if you see this, you can run the command /usr/sbin/sysctl -w vm.nr_hugepages=1612
as root or sudo /usr/sbin/sysctl -w vm.nr_hugepages=1612
You can either start the Client by providing command line arguments or using an appsettings.json file.
Argument | Default Value | Description |
---|---|---|
PayoutId | NULL | The Qubic ID you want to receive the mining payouts if you participate in pool mining |
Threads | 1 | How many threads should be used for the AI Training. |
Alias | qubic.li Client | You can give your Client a Name which will be displayed in the |
You can run the client directly in your Windows. The Client provices a .exe file which can be executed by a double click.
Download the Client from the above link. The Client must not be installed.
To run the qubic.li client you can use this streamlined installation guide. Please consider adapt the commands to suit your directory preferences. Note that all commands must be executed as the root user, or you should precede them with the sudo command for proper authorization.
1. Download and Unpack the qli-Client:
Execute the following command to download and extract the qli-Client. This example uses the package qli-Client-1.8.8-Linux-x64.tar.gz. Please ensure you replace it with the latest available version.
mkdir ~/qubic;
cd ~/qubic;
wget https://dl.qubic.li/downloads/qli-Client-2.2.1-Linux-x64.tar.gz;
tar -xvf qli-Client-2.2.1-Linux-x64.tar.gz;
rm qli-Client-2.2.1-Linux-x64.tar.gz;
2. edit and set your appsettings.json according to your preferences
nano appsettings.json
sample appsettings.json for GPU (Client >= 1.9.4):
{
"Settings": {
"baseUrl": "https://mine.qubic.li/",
"accessToken": "YOURACCESSTOKEN",
"alias": "YOURALIAS",
"trainer": { "gpu": true, "gpuVersion": "CUDA11" }
}
}
Note
Please refer to QLI Trainer Options for available gpuVersion
values.
sample appsettings.json for GPU (Client < 1.9.4):
{
"Settings": {
"baseUrl": "https://mine.qubic.li/",
"allowHwInfoCollect": true,
"overwrites": {
"CUDA": "12"
},
"accessToken": "YOURACCESSTOKEN",
"alias": "YOURALIAS"
}
}
sample appsettings.json for CPU set to 10 threads:
{
"Settings": {
"baseUrl": "https://mine.qubic.li/",
"overwrites": {},
"accessToken": "YOURACCESSTOKEN",
"amountOfThreads": 10,
"alias": "YOURALIAS"
}
}
3. run qli-Client in a screen session named "qubic"
screen -S qubic ./qli-Client
basic screen commands:
- exit screen : ctrl a + d
- kill screen : ctrl + c
- display qubic screen:
screen -r qubic
To install the qubic.li Service you can use our quick installation guide. Please consider to check the content of the service installation script.
All commands should either be executed by root or you need to prepend the sudo
command.
The installerscript places all qubic.li stuff in /q
.
Don't forget to replace the token from the below examples with your own.
# update your sources
apt update
# download service installation script with autoupdate
wget -O qli-Service-install.sh https://dl.qubic.li/cloud-init/qli-Service-install-auto.sh
# download service installation script without auto update
# wget -O qli-Service-install.sh https://dl.qubic.li/cloud-init/qli-Service-install.sh
# set the script as executable
chmod u+x qli-Service-install.sh
# install qubic.li client as systemd service
# Syntax: qli-Service-install.sh <threads> <accessToken|payoutId> [alias]
./qli-Service-install.sh 2 eyJhbGciOiJIUzUxMiIsInR5cCI6IkpXVCJ9.eyJJZCI6ImMyYmUyNTVkLWRkNzAtNDE4Mi04MDdkLWM1M2M5Yjc5ZDgyNiIsIk1pbmluZyI6IiIsIm5iZiI6MTcwNDczODc4NSwiZXhwIjoxNzM2Mjc0Nzg1LCJpYXQiOjE3MDQ3Mzg3ODUsImlzcyI6Imh0dHBzOi8vcXViaWMubGkvIiwiYXVkIjoiaHR0cHM6Ly9xdWJpYy5saS8ifQ.j8oI56OqV-gjoHxacwegetd2nha1zHLfSjW-REcNsp8q0lWW-NbvClPIuy_nig-YqpbyPXRPAZvYjh1SUjkw7g
for ubuntu 20.04 you might need to install a more recent libc version.
# add repo (use a mirror near your location from: https://packages.ubuntu.com/jammy/amd64/libc6/download)
echo "deb http://cz.archive.ubuntu.com/ubuntu jammy main" >> /etc/apt/sources.list
apt update
apt install libc6
apt install -y g++-11
# download service installation script with autoupdate
# wget -O qli-Service-install.sh https://dl.qubic.li/cloud-init/qli-Service-install-auto.sh
# download service installation script
wget -O qli-Service-install.sh https://dl.qubic.li/cloud-init/qli-Service-install.sh
# set the script as executable
chmod u+x qli-Service-install.sh
# install qubic.li client as systemd service
# Syntax: qli-Service-install.sh <threads> <accessToken|payoutId> [alias]
./qli-Service-install.sh 2 eyJhbGciOiJIUzUxMiIsInR5cCI6IkpXVCJ9.eyJJZCI6ImMyYmUyNTVkLWRkNzAtNDE4Mi04MDdkLWM1M2M5Yjc5ZDgyNiIsIk1pbmluZyI6IiIsIm5iZiI6MTcwNDczODc4NSwiZXhwIjoxNzM2Mjc0Nzg1LCJpYXQiOjE3MDQ3Mzg3ODUsImlzcyI6Imh0dHBzOi8vcXViaWMubGkvIiwiYXVkIjoiaHR0cHM6Ly9xdWJpYy5saS8ifQ.j8oI56OqV-gjoHxacwegetd2nha1zHLfSjW-REcNsp8q0lWW-NbvClPIuy_nig-YqpbyPXRPAZvYjh1SUjkw7g
for debian 11 you might need to install a more recent libc version.
DEPRECATED
# Update packages
sudo yum update
# download service installation script with autoupdate
# wget -O qli-Service-install.sh https://dl.qubic.li/cloud-init/qli-Service-install-auto.sh
# download service installation script
rm qli-Service-install.sh || wget https://dl.qubic.li/cloud-init/qli-Service-install.sh
# set the script as executable
chmod u+x qli-Service-install.sh
# install qubic.li client as systemd service
# Syntax: qli-Service-install.sh <threads> <accessToken|payoutId> [alias]
sudo ./qli-Service-install.sh 2 eyJhbGciOiJIUzUxMiIsInR5cCI6IkpXVCJ9.eyJJZCI6ImMyYmUyNTVkLWRkNzAtNDE4Mi04MDdkLWM1M2M5Yjc5ZDgyNiIsIk1pbmluZyI6IiIsIm5iZiI6MTcwNDczODc4NSwiZXhwIjoxNzM2Mjc0Nzg1LCJpYXQiOjE3MDQ3Mzg3ODUsImlzcyI6Imh0dHBzOi8vcXViaWMubGkvIiwiYXVkIjoiaHR0cHM6Ly9xdWJpYy5saS8ifQ.j8oI56OqV-gjoHxacwegetd2nha1zHLfSjW-REcNsp8q0lWW-NbvClPIuy_nig-YqpbyPXRPAZvYjh1SUjkw7g
You can manage your qubic.li Client with the systemd control.
Start Service: systemctl start qli
Stop Service: systemctl stop qli
Status Service: systemctl status qli
you can also see what is going on by observing the logs.
the service logs to /var/log/qli.log
or /var/log/qli.error.log
.
to live watch it on the console, use tail -f /var/log/qli.log
.
{
"Settings": {
"baseUrl": "https://mine.qubic.li/",
"amountOfThreads": 16,
"alias": "Client 3",
"accessToken": "eyJhbGciOiJIUzUxMiIsInR5cCI6IkpXVCJ9.eyJJZCI6ImMyYmUyNTVkLWRkNzAtNDE4Mi04MDdkLWM1M2M5Yjc5ZDgyNiIsIk1pbmluZyI6IiIsIm5iZiI6MTcwNDczODc4NSwiZXhwIjoxNzM2Mjc0Nzg1LCJpYXQiOjE3MDQ3Mzg3ODUsImlzcyI6Imh0dHBzOi8vcXViaWMubGkvIiwiYXVkIjoiaHR0cHM6Ly9xdWJpYy5saS8ifQ.j8oI56OqV-gjoHxacwegetd2nha1zHLfSjW-REcNsp8q0lWW-NbvClPIuy_nig-YqpbyPXRPAZvYjh1SUjkw7g"
}
}
{
"Settings": {
"baseUrl": "https://mine.qubic.li/",
"amountOfThreads": 16,
"alias": "My super miner",
"payoutId": "VGIWRRNVVRRXSEASPENCIMVNANPCFHAASZVPBIEFLCRYHWSZYSGXHNSBYPVN"
}
}
To remove the qubic.li Client execute the following commands.
# stop service
systemctl stop qli --no-block
# remove service definition
rm /etc/systemd/system/qli.service
# reload systemd
systemctl daemon-reload
# remove all related files
rm -R /q
rm /var/log/qli.log
Appsettings.json contains the configuration of your client and need to be placed at the same location as the executable.
if you opt for the Linux Screen session (Option 1):
- you can customize the settings of your client in the settings file
~/qubic/appsettings.json
if you opt for the Systemd Linux Service (Option 2):
- you can customize the settings of your client in the settings file
/q/appsettings.json
- You can create a custom file with the name
appsettings.production.json
which has higher priority to be loaded.
Setting | Default Value | Description |
---|---|---|
baseUrl | https://wps.qubic.li/ | The Base Url of the API |
amountOfThreads | 1 | How many threads should be used for the AI Training. |
accessToken* | JWT Token | This is you personal JWT Token which you can obtain from the Control Panel at qubic.li |
payoutId* | NULL | This is the ID you want to get token payout for your found solutions. |
alias | qli Client | You can give your Client a Name which will be displayed in the Control Panel. If empty it uses the Hostname. |
allowHwInfoCollect | false | With that option set to true the client will collect CPU model, CPU Cache Size and RAM Size to get optimal runner for that maschine |
threadsDaySchedule | empty | Can be used to schedule the training. e.g. training should only run during night time. |
customRunner | false | Set this to true to use a custom trainer. The Client will not automatically update runner. Details |
serviceLock | false | Set this to true to use a custom trainer with qiner protocol. |
overwrites | {} | An object to overwrite specific settings. (e.g. "AVX512":false to disable AVX512) |
autoupdateEnabled | false | Set this to true to enable auto update of the service client (from version 1.7.8) |
checkUpdateEnabled | true | Checks if there is a new version of the service client when starting |
isPps | true | If the trainer should run in PPS mode |
useLiveConnection | true | The client will use a websocket connection for optimal performance |
trainer | {} | The trainer configuration options |
idleSettings | {} | The configuration options for the Qubic idling period. WARNING: Using idle can affect Qubic performance! |
{
"cpu": false,
"cpuVersion": "AVX512",
"cpuThreads": 16,
"cpuAffinity": "",
"cpuVariant": "",
"gpu": true,
"gpuVersion": "CUDA11",
"gpuCards": "",
"gpuVariant": ""
}
Setting | Default Value | Description |
---|---|---|
*cpu | false | Enable CPU Training |
*gpu | false | Enable GPU Training |
cpuVersion | AUTO | AUTO = it tries to detect your CPU; CPU Version to be used QLI Trainer Options |
gpuVersion | null | GPU Version to be used QLI Trainer Options |
cpuThreads | 1 | Number of Threads used for CPU training |
gpuCards | null | Which GPU Cards should be used (see details below; available from client >=1.9.5 and runner >=105.3 ) |
cpuAffinity | null | CPU Affinity for CPU training |
cpuVariant | null | Which Variant of CPU trainer should be used |
gpuVariant | null | Which Variant of GPU trainer should be used |
*currently only one of both options can be enabled (true)
Note
The gpuCards
property can be used to select gThreads
. The default configuration is auto tune
for all cards.
For each GPU you can use (comma separated):
-1
=> auto tune
0
=> disable GPU
>0
=> number of gThreads
to be used
e.g.:
0,-1,-1,-1,-1,-1
=> GPU#1 disabled, #1-5 auto tuen
e.g.:0
=> GPU#0 disabled, if there are more, all will be auto tuned
e.g.:512,256,256,256,256,512
=> setgThread
to 512 on GPU#0 and GPU#5, 256 to the rest
During the Qubic idling phase. You can run another program or miner.
Warning
An idle program that changes settings or do not close properly when receiving SIGINT or be killed can harm the Qubic performance. Please only use this feature if you know what you do!
{
"command": "ping",
"arguments": "google.com"
}
Setting | Default Value | Description |
---|---|---|
command | "" | the command/programm to execute |
argument | "" | the arguments that should be given to the command/program |
The Client creates a folder log
where all error messages are stored. If the Client stops unexpected or doesn't open check if there is a log file with current date and check the error messages.
If you see an error like this ERROR LIVE AUTHENTICATION FAILED
, you should create a new AccessToken. https://pool.qubic.li
The Community showed several solutions to that Problem.
Try to install the Ubuntu nvidia drivers.
sudo apt update
sudo apt install nvidia-driver
sudo reboot
If you have a second GPU (e.g. from your processor) you can try to disable your mining GPU for windows and let windows use the second GPU to render your windows.
Somtimes the detection of AVX2/AVX512 is not accurate and it loads the wrong trainer. If this happens to you, you can enforce certain configuration.
add "SKYLAKE": true
to overwrites in appsettings.json
{
"Settings": {
"....": "..."
"overwrites": {
"SKYLAKE": true
}
}
}
add "AVX512": false
to overwrites in appsettings.json
{
"Settings": {
"....": "..."
"overwrites": {
"AVX512": false
}
}
}
if your trainer isn't working properly. try the following to reset local configuration:
# stop trainer
systemctl stop qli --no-block
# ensure that all qli services are stopped/killed
pkill -f qli
# delete any existing configuration lock
rm /q/*.lock
# delete current runner
rm /q/qli-runner
# delete old solutions
find /q/. -maxdepth 1 -regextype posix-extended -regex '.*\.e[[:digit:]]+' -delete
# delete state files
find /q/. -maxdepth 1 -regextype posix-extended -regex 'state\.[[:digit:]]+' -delete
# start trainer
systemctl start qli --no-block
if you think the client reports wrong or random hashrate you could restart your server. Or stop all qli services. (e.g. for linux: systemctl stop qli --no-block && pkill -f qli && systemctl start qli
)
Every specific CPU or general Hardware configuration can need speific performance settings. Depending on your Setup you can try:
- Enable/Disable SMT/HT in Bios
- Choose another runner via Webinterface: https://app.qubic.li/main/mining/control
- Enabled/Disable Performance Boost (Windows)
- Enable/Disable specific Power Schema (Ubuntu)
- Add/Remove
wine
in linux. (for ubuntu:apt install wine -y
orapt autoremove wine -y
- Adjust Threads to your needs. Sometimes less threads is more effective thatn to many.