Merging upstream version 1.46.3.

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

5 files changed, 0 insertions, 1055 deletions

diff --git a/collectors/python.d.plugin/nvidia_smi/Makefile.inc b/collectors/python.d.plugin/nvidia_smi/Makefile.inc
deleted file mode 100644
index 52fb25a68..000000000
--- a/collectors/python.d.plugin/nvidia_smi/Makefile.inc
+++ /dev/null
@@ -1,13 +0,0 @@
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-# THIS IS NOT A COMPLETE Makefile
-# IT IS INCLUDED BY ITS PARENT'S Makefile.am
-# IT IS REQUIRED TO REFERENCE ALL FILES RELATIVE TO THE PARENT
-
-# install these files
-dist_python_DATA       += nvidia_smi/nvidia_smi.chart.py
-dist_pythonconfig_DATA += nvidia_smi/nvidia_smi.conf
-
-# do not install these files, but include them in the distribution
-dist_noinst_DATA       += nvidia_smi/README.md nvidia_smi/Makefile.inc
-
diff --git a/collectors/python.d.plugin/nvidia_smi/README.md b/collectors/python.d.plugin/nvidia_smi/README.md
deleted file mode 100644
index 7d45289a4..000000000
--- a/collectors/python.d.plugin/nvidia_smi/README.md
+++ /dev/null
@@ -1,157 +0,0 @@
-<!--
-title: "Nvidia GPU monitoring with Netdata"
-custom_edit_url: "https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/nvidia_smi/README.md"
-sidebar_label: "nvidia_smi-python.d.plugin"
-learn_status: "Published"
-learn_topic_type: "References"
-learn_rel_path: "Integrations/Monitor/Devices"
--->
-
-# Nvidia GPU collector
-
-Monitors performance metrics (memory usage, fan speed, pcie bandwidth utilization, temperature, etc.) using `nvidia-smi` cli tool.
-
-## Requirements and Notes
-
--   You must have the `nvidia-smi` tool installed and your NVIDIA GPU(s) must support the tool. Mostly the newer high end models used for AI / ML and Crypto or Pro range, read more about [nvidia_smi](https://developer.nvidia.com/nvidia-system-management-interface).
--   You must enable this plugin, as its disabled by default due to minor performance issues:
-    ```bash
-    cd /etc/netdata   # Replace this path with your Netdata config directory, if different
-    sudo ./edit-config python.d.conf
-    ```
-    Remove the '#' before nvidia_smi so it reads: `nvidia_smi: yes`.
-
--   On some systems when the GPU is idle the `nvidia-smi` tool unloads and there is added latency again when it is next queried. If you are running GPUs under constant workload this isn't likely to be an issue.
--   Currently the `nvidia-smi` tool is being queried via cli. Updating the plugin to use the nvidia c/c++ API directly should resolve this issue. See discussion here: <https://github.com/netdata/netdata/pull/4357>
--   Contributions are welcome.
--   Make sure `netdata` user can execute `/usr/bin/nvidia-smi` or wherever your binary is.
--   If `nvidia-smi` process [is not killed after netdata restart](https://github.com/netdata/netdata/issues/7143) you need to off `loop_mode`.
--   `poll_seconds` is how often in seconds the tool is polled for as an integer.
-
-## Charts
-
-It produces the following charts:
-
--   PCI Express Bandwidth Utilization in `KiB/s`
--   Fan Speed in `percentage`
--   GPU Utilization in `percentage`
--   Memory Bandwidth Utilization in `percentage`
--   Encoder/Decoder Utilization in `percentage`
--   Memory Usage in `MiB`
--   Temperature in `celsius`
--   Clock Frequencies in `MHz`
--   Power Utilization in `Watts`
--   Memory Used by Each Process in `MiB`
--   Memory Used by Each User in `MiB`
--   Number of User on GPU in `num`
-
-## Configuration
-
-Edit the `python.d/nvidia_smi.conf` configuration file using `edit-config` from the Netdata [config
-directory](https://github.com/netdata/netdata/blob/master/docs/configure/nodes.md), which is typically at `/etc/netdata`.
-
-```bash
-cd /etc/netdata   # Replace this path with your Netdata config directory, if different
-sudo ./edit-config python.d/nvidia_smi.conf
-```
-
-Sample:
-
-```yaml
-loop_mode    : yes
-poll_seconds : 1
-exclude_zero_memory_users : yes
-```
-
-
-### Troubleshooting
-
-To troubleshoot issues with the `nvidia_smi` module, run the `python.d.plugin` with the debug option enabled. The 
-output will give you the output of the data collection job or error messages on why the collector isn't working.
-
-First, navigate to your plugins directory, usually they are located under `/usr/libexec/netdata/plugins.d/`. If that's 
-not the case on your system, open `netdata.conf` and look for the setting `plugins directory`. Once you're in the 
-plugin's directory, switch to the `netdata` user.
-
-```bash
-cd /usr/libexec/netdata/plugins.d/
-sudo su -s /bin/bash netdata
-```
-
-Now you can manually run the `nvidia_smi` module in debug mode:
-
-```bash
-./python.d.plugin nvidia_smi debug trace
-```
-
-## Docker
-
-GPU monitoring in a docker container is possible with [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) installed on the host system, and `gcompat` added to the `NETDATA_EXTRA_APK_PACKAGES` environment variable.
-
-Sample `docker-compose.yml`
-```yaml
-version: '3'
-services:
-  netdata:
-    image: netdata/netdata
-    container_name: netdata
-    hostname: example.com # set to fqdn of host
-    ports:
-      - 19999:19999
-    restart: unless-stopped
-    cap_add:
-      - SYS_PTRACE
-    security_opt:
-      - apparmor:unconfined
-    environment:
-      - NETDATA_EXTRA_APK_PACKAGES=gcompat
-    volumes:
-      - netdataconfig:/etc/netdata
-      - netdatalib:/var/lib/netdata
-      - netdatacache:/var/cache/netdata
-      - /etc/passwd:/host/etc/passwd:ro
-      - /etc/group:/host/etc/group:ro
-      - /proc:/host/proc:ro
-      - /sys:/host/sys:ro
-      - /etc/os-release:/host/etc/os-release:ro
-    deploy:
-      resources:
-        reservations:
-          devices:
-          - driver: nvidia
-            count: all
-            capabilities: [gpu]
-
-volumes:
-  netdataconfig:
-  netdatalib:
-  netdatacache:
-```
-
-Sample `docker run`
-```yaml
-docker run -d --name=netdata \
-  -p 19999:19999 \
-  -e NETDATA_EXTRA_APK_PACKAGES=gcompat \
-  -v netdataconfig:/etc/netdata \
-  -v netdatalib:/var/lib/netdata \
-  -v netdatacache:/var/cache/netdata \
-  -v /etc/passwd:/host/etc/passwd:ro \
-  -v /etc/group:/host/etc/group:ro \
-  -v /proc:/host/proc:ro \
-  -v /sys:/host/sys:ro \
-  -v /etc/os-release:/host/etc/os-release:ro \
-  --restart unless-stopped \
-  --cap-add SYS_PTRACE \
-  --security-opt apparmor=unconfined \
-  --gpus all \
-  netdata/netdata
-```
-
-### Docker Troubleshooting
-To troubleshoot `nvidia-smi` in a docker container, first confirm that `nvidia-smi` is working on the host system. If that is working correctly, run `docker exec -it netdata nvidia-smi` to confirm it's working within the docker container. If `nvidia-smi` is fuctioning both inside and outside of the container, confirm that `nvidia-smi: yes` is uncommented in `python.d.conf`.
-```bash
-docker exec -it netdata bash
-cd /etc/netdata
-./edit-config python.d.conf
-```
diff --git a/collectors/python.d.plugin/nvidia_smi/metadata.yaml b/collectors/python.d.plugin/nvidia_smi/metadata.yaml
deleted file mode 100644
index 9bf1e6ca7..000000000
--- a/collectors/python.d.plugin/nvidia_smi/metadata.yaml
+++ /dev/null
@@ -1,166 +0,0 @@
-# This collector will not appear in documentation, as the go version is preferred,
-# https://github.com/netdata/go.d.plugin/blob/master/modules/nvidia_smi/README.md
-#
-# meta:
-#   plugin_name: python.d.plugin
-#   module_name: nvidia_smi
-#   monitored_instance:
-#     name: python.d nvidia_smi
-#     link: ''
-#     categories: []
-#     icon_filename: ''
-#   related_resources:
-#     integrations:
-#       list: []
-#   info_provided_to_referring_integrations:
-#     description: ''
-#   keywords: []
-#   most_popular: false
-# overview:
-#   data_collection:
-#     metrics_description: ''
-#     method_description: ''
-#   supported_platforms:
-#     include: []
-#     exclude: []
-#   multi_instance: true
-#   additional_permissions:
-#     description: ''
-#   default_behavior:
-#     auto_detection:
-#       description: ''
-#     limits:
-#       description: ''
-#     performance_impact:
-#       description: ''
-# setup:
-#   prerequisites:
-#     list: []
-#   configuration:
-#     file:
-#       name: ''
-#       description: ''
-#     options:
-#       description: ''
-#       folding:
-#         title: ''
-#         enabled: true
-#       list: []
-#     examples:
-#       folding:
-#         enabled: true
-#         title: ''
-#       list: []
-# troubleshooting:
-#   problems:
-#     list: []
-# alerts: []
-# metrics:
-#   folding:
-#     title: Metrics
-#     enabled: false
-#   description: ""
-#   availability: []
-#   scopes:
-#   - name: GPU
-#     description: ""
-#     labels: []
-#     metrics:
-#     - name: nvidia_smi.pci_bandwidth
-#       description: PCI Express Bandwidth Utilization
-#       unit: "KiB/s"
-#       chart_type: area
-#       dimensions:
-#       - name: rx
-#       - name: tx
-#     - name: nvidia_smi.pci_bandwidth_percent
-#       description: PCI Express Bandwidth Percent
-#       unit: "percentage"
-#       chart_type: area
-#       dimensions:
-#       - name: rx_percent
-#       - name: tx_percent
-#     - name: nvidia_smi.fan_speed
-#       description: Fan Speed
-#       unit: "percentage"
-#       chart_type: line
-#       dimensions:
-#       - name: speed
-#     - name: nvidia_smi.gpu_utilization
-#       description: GPU Utilization
-#       unit: "percentage"
-#       chart_type: line
-#       dimensions:
-#       - name: utilization
-#     - name: nvidia_smi.mem_utilization
-#       description: Memory Bandwidth Utilization
-#       unit: "percentage"
-#       chart_type: line
-#       dimensions:
-#       - name: utilization
-#     - name: nvidia_smi.encoder_utilization
-#       description: Encoder/Decoder Utilization
-#       unit: "percentage"
-#       chart_type: line
-#       dimensions:
-#       - name: encoder
-#       - name: decoder
-#     - name: nvidia_smi.memory_allocated
-#       description: Memory Usage
-#       unit: "MiB"
-#       chart_type: stacked
-#       dimensions:
-#       - name: free
-#       - name: used
-#     - name: nvidia_smi.bar1_memory_usage
-#       description: Bar1 Memory Usage
-#       unit: "MiB"
-#       chart_type: stacked
-#       dimensions:
-#       - name: free
-#       - name: used
-#     - name: nvidia_smi.temperature
-#       description: Temperature
-#       unit: "celsius"
-#       chart_type: line
-#       dimensions:
-#       - name: temp
-#     - name: nvidia_smi.clocks
-#       description: Clock Frequencies
-#       unit: "MHz"
-#       chart_type: line
-#       dimensions:
-#       - name: graphics
-#       - name: video
-#       - name: sm
-#       - name: mem
-#     - name: nvidia_smi.power
-#       description: Power Utilization
-#       unit: "Watts"
-#       chart_type: line
-#       dimensions:
-#       - name: power
-#     - name: nvidia_smi.power_state
-#       description: Power State
-#       unit: "state"
-#       chart_type: line
-#       dimensions:
-#       - name: a dimension per {power_state}
-#     - name: nvidia_smi.processes_mem
-#       description: Memory Used by Each Process
-#       unit: "MiB"
-#       chart_type: stacked
-#       dimensions:
-#       - name: a dimension per process
-#     - name: nvidia_smi.user_mem
-#       description: Memory Used by Each User
-#       unit: "MiB"
-#       chart_type: stacked
-#       dimensions:
-#       - name: a dimension per user
-#     - name: nvidia_smi.user_num
-#       description: Number of User on GPU
-#       unit: "num"
-#       chart_type: line
-#       dimensions:
-#       - name: users
diff --git a/collectors/python.d.plugin/nvidia_smi/nvidia_smi.chart.py b/collectors/python.d.plugin/nvidia_smi/nvidia_smi.chart.py
deleted file mode 100644
index 556a61435..000000000
--- a/collectors/python.d.plugin/nvidia_smi/nvidia_smi.chart.py
+++ /dev/null
@@ -1,651 +0,0 @@
-# -*- coding: utf-8 -*-
-# Description: nvidia-smi netdata python.d module
-# Original Author: Steven Noonan (tycho)
-# Author: Ilya Mashchenko (ilyam8)
-# User Memory Stat Author: Guido Scatena (scatenag)
-
-import os
-import pwd
-import subprocess
-import threading
-import xml.etree.ElementTree as et
-
-from bases.FrameworkServices.SimpleService import SimpleService
-from bases.collection import find_binary
-
-disabled_by_default = True
-
-NVIDIA_SMI = 'nvidia-smi'
-
-NOT_AVAILABLE = 'N/A'
-
-EMPTY_ROW = ''
-EMPTY_ROW_LIMIT = 500
-POLLER_BREAK_ROW = '</nvidia_smi_log>'
-
-PCI_BANDWIDTH = 'pci_bandwidth'
-PCI_BANDWIDTH_PERCENT = 'pci_bandwidth_percent'
-FAN_SPEED = 'fan_speed'
-GPU_UTIL = 'gpu_utilization'
-MEM_UTIL = 'mem_utilization'
-ENCODER_UTIL = 'encoder_utilization'
-MEM_USAGE = 'mem_usage'
-BAR_USAGE = 'bar1_mem_usage'
-TEMPERATURE = 'temperature'
-CLOCKS = 'clocks'
-POWER = 'power'
-POWER_STATE = 'power_state'
-PROCESSES_MEM = 'processes_mem'
-USER_MEM = 'user_mem'
-USER_NUM = 'user_num'
-
-ORDER = [
-    PCI_BANDWIDTH,
-    PCI_BANDWIDTH_PERCENT,
-    FAN_SPEED,
-    GPU_UTIL,
-    MEM_UTIL,
-    ENCODER_UTIL,
-    MEM_USAGE,
-    BAR_USAGE,
-    TEMPERATURE,
-    CLOCKS,
-    POWER,
-    POWER_STATE,
-    PROCESSES_MEM,
-    USER_MEM,
-    USER_NUM,
-]
-
-# https://docs.nvidia.com/gameworks/content/gameworkslibrary/coresdk/nvapi/group__gpupstate.html
-POWER_STATES = ['P' + str(i) for i in range(0, 16)]
-
-# PCI Transfer data rate in gigabits per second (Gb/s) per generation
-PCI_SPEED = {
-    "1": 2.5,
-    "2": 5,
-    "3": 8,
-    "4": 16,
-    "5": 32
-}
-# PCI encoding per generation
-PCI_ENCODING = {
-    "1": 2 / 10,
-    "2": 2 / 10,
-    "3": 2 / 130,
-    "4": 2 / 130,
-    "5": 2 / 130
-}
-
-
-def gpu_charts(gpu):
-    fam = gpu.full_name()
-
-    charts = {
-        PCI_BANDWIDTH: {
-            'options': [None, 'PCI Express Bandwidth Utilization', 'KiB/s', fam, 'nvidia_smi.pci_bandwidth', 'area'],
-            'lines': [
-                ['rx_util', 'rx', 'absolute', 1, 1],
-                ['tx_util', 'tx', 'absolute', 1, -1],
-            ]
-        },
-        PCI_BANDWIDTH_PERCENT: {
-            'options': [None, 'PCI Express Bandwidth Percent', 'percentage', fam, 'nvidia_smi.pci_bandwidth_percent',
-                        'area'],
-            'lines': [
-                ['rx_util_percent', 'rx_percent'],
-                ['tx_util_percent', 'tx_percent'],
-            ]
-        },
-        FAN_SPEED: {
-            'options': [None, 'Fan Speed', 'percentage', fam, 'nvidia_smi.fan_speed', 'line'],
-            'lines': [
-                ['fan_speed', 'speed'],
-            ]
-        },
-        GPU_UTIL: {
-            'options': [None, 'GPU Utilization', 'percentage', fam, 'nvidia_smi.gpu_utilization', 'line'],
-            'lines': [
-                ['gpu_util', 'utilization'],
-            ]
-        },
-        MEM_UTIL: {
-            'options': [None, 'Memory Bandwidth Utilization', 'percentage', fam, 'nvidia_smi.mem_utilization', 'line'],
-            'lines': [
-                ['memory_util', 'utilization'],
-            ]
-        },
-        ENCODER_UTIL: {
-            'options': [None, 'Encoder/Decoder Utilization', 'percentage', fam, 'nvidia_smi.encoder_utilization',
-                        'line'],
-            'lines': [
-                ['encoder_util', 'encoder'],
-                ['decoder_util', 'decoder'],
-            ]
-        },
-        MEM_USAGE: {
-            'options': [None, 'Memory Usage', 'MiB', fam, 'nvidia_smi.memory_allocated', 'stacked'],
-            'lines': [
-                ['fb_memory_free', 'free'],
-                ['fb_memory_used', 'used'],
-            ]
-        },
-        BAR_USAGE: {
-            'options': [None, 'Bar1 Memory Usage', 'MiB', fam, 'nvidia_smi.bar1_memory_usage', 'stacked'],
-            'lines': [
-                ['bar1_memory_free', 'free'],
-                ['bar1_memory_used', 'used'],
-            ]
-        },
-        TEMPERATURE: {
-            'options': [None, 'Temperature', 'celsius', fam, 'nvidia_smi.temperature', 'line'],
-            'lines': [
-                ['gpu_temp', 'temp'],
-            ]
-        },
-        CLOCKS: {
-            'options': [None, 'Clock Frequencies', 'MHz', fam, 'nvidia_smi.clocks', 'line'],
-            'lines': [
-                ['graphics_clock', 'graphics'],
-                ['video_clock', 'video'],
-                ['sm_clock', 'sm'],
-                ['mem_clock', 'mem'],
-            ]
-        },
-        POWER: {
-            'options': [None, 'Power Utilization', 'Watts', fam, 'nvidia_smi.power', 'line'],
-            'lines': [
-                ['power_draw', 'power', 'absolute', 1, 100],
-            ]
-        },
-        POWER_STATE: {
-            'options': [None, 'Power State', 'state', fam, 'nvidia_smi.power_state', 'line'],
-            'lines': [['power_state_' + v.lower(), v, 'absolute'] for v in POWER_STATES]
-        },
-        PROCESSES_MEM: {
-            'options': [None, 'Memory Used by Each Process', 'MiB', fam, 'nvidia_smi.processes_mem', 'stacked'],
-            'lines': []
-        },
-        USER_MEM: {
-            'options': [None, 'Memory Used by Each User', 'MiB', fam, 'nvidia_smi.user_mem', 'stacked'],
-            'lines': []
-        },
-        USER_NUM: {
-            'options': [None, 'Number of User on GPU', 'num', fam, 'nvidia_smi.user_num', 'line'],
-            'lines': [
-                ['user_num', 'users'],
-            ]
-        },
-    }
-
-    idx = gpu.num
-
-    order = ['gpu{0}_{1}'.format(idx, v) for v in ORDER]
-    charts = dict(('gpu{0}_{1}'.format(idx, k), v) for k, v in charts.items())
-
-    for chart in charts.values():
-        for line in chart['lines']:
-            line[0] = 'gpu{0}_{1}'.format(idx, line[0])
-
-    return order, charts
-
-
-class NvidiaSMI:
-    def __init__(self):
-        self.command = find_binary(NVIDIA_SMI)
-        self.active_proc = None
-
-    def run_once(self):
-        proc = subprocess.Popen([self.command, '-x', '-q'], stdout=subprocess.PIPE)
-        stdout, _ = proc.communicate()
-        return stdout
-
-    def run_loop(self, interval):
-        if self.active_proc:
-            self.kill()
-        proc = subprocess.Popen([self.command, '-x', '-q', '-l', str(interval)], stdout=subprocess.PIPE)
-        self.active_proc = proc
-        return proc.stdout
-
-    def kill(self):
-        if self.active_proc:
-            self.active_proc.kill()
-            self.active_proc = None
-
-
-class NvidiaSMIPoller(threading.Thread):
-    def __init__(self, poll_interval):
-        threading.Thread.__init__(self)
-        self.daemon = True
-
-        self.smi = NvidiaSMI()
-        self.interval = poll_interval
-
-        self.lock = threading.RLock()
-        self.last_data = str()
-        self.exit = False
-        self.empty_rows = 0
-        self.rows = list()
-
-    def has_smi(self):
-        return bool(self.smi.command)
-
-    def run_once(self):
-        return self.smi.run_once()
-
-    def run(self):
-        out = self.smi.run_loop(self.interval)
-
-        for row in out:
-            if self.exit or self.empty_rows > EMPTY_ROW_LIMIT:
-                break
-            self.process_row(row)
-        self.smi.kill()
-
-    def process_row(self, row):
-        row = row.decode()
-        self.empty_rows += (row == EMPTY_ROW)
-        self.rows.append(row)
-
-        if POLLER_BREAK_ROW in row:
-            self.lock.acquire()
-            self.last_data = '\n'.join(self.rows)
-            self.lock.release()
-
-            self.rows = list()
-            self.empty_rows = 0
-
-    def is_started(self):
-        return self.ident is not None
-
-    def shutdown(self):
-        self.exit = True
-
-    def data(self):
-        self.lock.acquire()
-        data = self.last_data
-        self.lock.release()
-        return data
-
-
-def handle_attr_error(method):
-    def on_call(*args, **kwargs):
-        try:
-            return method(*args, **kwargs)
-        except AttributeError:
-            return None
-
-    return on_call
-
-
-def handle_value_error(method):
-    def on_call(*args, **kwargs):
-        try:
-            return method(*args, **kwargs)
-        except ValueError:
-            return None
-
-    return on_call
-
-
-HOST_PREFIX = os.getenv('NETDATA_HOST_PREFIX')
-ETC_PASSWD_PATH = '/etc/passwd'
-PROC_PATH = '/proc'
-
-IS_INSIDE_DOCKER = False
-
-if HOST_PREFIX:
-    ETC_PASSWD_PATH = os.path.join(HOST_PREFIX, ETC_PASSWD_PATH[1:])
-    PROC_PATH = os.path.join(HOST_PREFIX, PROC_PATH[1:])
-    IS_INSIDE_DOCKER = True
-
-
-def read_passwd_file():
-    data = dict()
-    with open(ETC_PASSWD_PATH, 'r') as f:
-        for line in f:
-            line = line.strip()
-            if line.startswith("#"):
-                continue
-            fields = line.split(":")
-            # name, passwd, uid, gid, comment, home_dir, shell
-            if len(fields) != 7:
-                continue
-            # uid, guid
-            fields[2], fields[3] = int(fields[2]), int(fields[3])
-            data[fields[2]] = fields
-    return data
-
-
-def read_passwd_file_safe():
-    try:
-        if IS_INSIDE_DOCKER:
-            return read_passwd_file()
-        return dict((k[2], k) for k in pwd.getpwall())
-    except (OSError, IOError):
-        return dict()
-
-
-def get_username_by_pid_safe(pid, passwd_file):
-    path = os.path.join(PROC_PATH, pid)
-    try:
-        uid = os.stat(path).st_uid
-    except (OSError, IOError):
-        return ''
-    try:
-        if IS_INSIDE_DOCKER:
-            return passwd_file[uid][0]
-        return pwd.getpwuid(uid)[0]
-    except KeyError:
-        return str(uid)
-
-
-class GPU:
-    def __init__(self, num, root, exclude_zero_memory_users=False):
-        self.num = num
-        self.root = root
-        self.exclude_zero_memory_users = exclude_zero_memory_users
-
-    def id(self):
-        return self.root.get('id')
-
-    def name(self):
-        return self.root.find('product_name').text
-
-    def full_name(self):
-        return 'gpu{0} {1}'.format(self.num, self.name())
-
-    @handle_attr_error
-    def pci_link_gen(self):
-        return self.root.find('pci').find('pci_gpu_link_info').find('pcie_gen').find('max_link_gen').text
-
-    @handle_attr_error
-    def pci_link_width(self):
-        info = self.root.find('pci').find('pci_gpu_link_info')
-        return info.find('link_widths').find('max_link_width').text.split('x')[0]
-
-    def pci_bw_max(self):
-        link_gen = self.pci_link_gen()
-        link_width = int(self.pci_link_width())
-        if link_gen not in PCI_SPEED or link_gen not in PCI_ENCODING or not link_width:
-            return None
-        # Maximum PCIe Bandwidth = SPEED * WIDTH * (1 - ENCODING) - 1Gb/s.
-        # see details https://enterprise-support.nvidia.com/s/article/understanding-pcie-configuration-for-maximum-performance
-        # return max bandwidth in kilobytes per second (kB/s)
-        return (PCI_SPEED[link_gen] * link_width * (1 - PCI_ENCODING[link_gen]) - 1) * 1000 * 1000 / 8
-
-    @handle_attr_error
-    def rx_util(self):
-        return self.root.find('pci').find('rx_util').text.split()[0]
-
-    @handle_attr_error
-    def tx_util(self):
-        return self.root.find('pci').find('tx_util').text.split()[0]
-
-    @handle_attr_error
-    def fan_speed(self):
-        return self.root.find('fan_speed').text.split()[0]
-
-    @handle_attr_error
-    def gpu_util(self):
-        return self.root.find('utilization').find('gpu_util').text.split()[0]
-
-    @handle_attr_error
-    def memory_util(self):
-        return self.root.find('utilization').find('memory_util').text.split()[0]
-
-    @handle_attr_error
-    def encoder_util(self):
-        return self.root.find('utilization').find('encoder_util').text.split()[0]
-
-    @handle_attr_error
-    def decoder_util(self):
-        return self.root.find('utilization').find('decoder_util').text.split()[0]
-
-    @handle_attr_error
-    def fb_memory_used(self):
-        return self.root.find('fb_memory_usage').find('used').text.split()[0]
-
-    @handle_attr_error
-    def fb_memory_free(self):
-        return self.root.find('fb_memory_usage').find('free').text.split()[0]
-
-    @handle_attr_error
-    def bar1_memory_used(self):
-        return self.root.find('bar1_memory_usage').find('used').text.split()[0]
-
-    @handle_attr_error
-    def bar1_memory_free(self):
-        return self.root.find('bar1_memory_usage').find('free').text.split()[0]
-
-    @handle_attr_error
-    def temperature(self):
-        return self.root.find('temperature').find('gpu_temp').text.split()[0]
-
-    @handle_attr_error
-    def graphics_clock(self):
-        return self.root.find('clocks').find('graphics_clock').text.split()[0]
-
-    @handle_attr_error
-    def video_clock(self):
-        return self.root.find('clocks').find('video_clock').text.split()[0]
-
-    @handle_attr_error
-    def sm_clock(self):
-        return self.root.find('clocks').find('sm_clock').text.split()[0]
-
-    @handle_attr_error
-    def mem_clock(self):
-        return self.root.find('clocks').find('mem_clock').text.split()[0]
-
-    @handle_attr_error
-    def power_readings(self):
-        elem = self.root.find('power_readings')
-        return elem if elem else self.root.find('gpu_power_readings')
-
-    @handle_attr_error
-    def power_state(self):
-        return str(self.power_readings().find('power_state').text.split()[0])
-
-    @handle_value_error
-    @handle_attr_error
-    def power_draw(self):
-        return float(self.power_readings().find('power_draw').text.split()[0]) * 100
-
-    @handle_attr_error
-    def processes(self):
-        processes_info = self.root.find('processes').findall('process_info')
-        if not processes_info:
-            return list()
-
-        passwd_file = read_passwd_file_safe()
-        processes = list()
-
-        for info in processes_info:
-            pid = info.find('pid').text
-            processes.append({
-                'pid': int(pid),
-                'process_name': info.find('process_name').text,
-                'used_memory': int(info.find('used_memory').text.split()[0]),
-                'username': get_username_by_pid_safe(pid, passwd_file),
-            })
-        return processes
-
-    def data(self):
-        data = {
-            'rx_util': self.rx_util(),
-            'tx_util': self.tx_util(),
-            'fan_speed': self.fan_speed(),
-            'gpu_util': self.gpu_util(),
-            'memory_util': self.memory_util(),
-            'encoder_util': self.encoder_util(),
-            'decoder_util': self.decoder_util(),
-            'fb_memory_used': self.fb_memory_used(),
-            'fb_memory_free': self.fb_memory_free(),
-            'bar1_memory_used': self.bar1_memory_used(),
-            'bar1_memory_free': self.bar1_memory_free(),
-            'gpu_temp': self.temperature(),
-            'graphics_clock': self.graphics_clock(),
-            'video_clock': self.video_clock(),
-            'sm_clock': self.sm_clock(),
-            'mem_clock': self.mem_clock(),
-            'power_draw': self.power_draw(),
-        }
-
-        if self.rx_util() != NOT_AVAILABLE and self.tx_util() != NOT_AVAILABLE:
-            pci_bw_max = self.pci_bw_max()
-            if not pci_bw_max:
-                data['rx_util_percent'] = 0
-                data['tx_util_percent'] = 0
-            else:
-                data['rx_util_percent'] = str(int(int(self.rx_util()) * 100 / self.pci_bw_max()))
-                data['tx_util_percent'] = str(int(int(self.tx_util()) * 100 / self.pci_bw_max()))
-
-        for v in POWER_STATES:
-            data['power_state_' + v.lower()] = 0
-        p_state = self.power_state()
-        if p_state:
-            data['power_state_' + p_state.lower()] = 1
-
-        processes = self.processes() or []
-        users = set()
-        for p in processes:
-            data['process_mem_{0}'.format(p['pid'])] = p['used_memory']
-            if p['username']:
-                if self.exclude_zero_memory_users and p['used_memory'] == 0:
-                    continue
-                users.add(p['username'])
-                key = 'user_mem_{0}'.format(p['username'])
-                if key in data:
-                    data[key] += p['used_memory']
-                else:
-                    data[key] = p['used_memory']
-        data['user_num'] = len(users)
-
-        return dict(('gpu{0}_{1}'.format(self.num, k), v) for k, v in data.items())
-
-
-class Service(SimpleService):
-    def __init__(self, configuration=None, name=None):
-        super(Service, self).__init__(configuration=configuration, name=name)
-        self.order = list()
-        self.definitions = dict()
-        self.loop_mode = configuration.get('loop_mode', True)
-        poll = int(configuration.get('poll_seconds', self.get_update_every()))
-        self.exclude_zero_memory_users = configuration.get('exclude_zero_memory_users', False)
-        self.poller = NvidiaSMIPoller(poll)
-
-    def get_data_loop_mode(self):
-        if not self.poller.is_started():
-            self.poller.start()
-
-        if not self.poller.is_alive():
-            self.debug('poller is off')
-            return None
-
-        return self.poller.data()
-
-    def get_data_normal_mode(self):
-        return self.poller.run_once()
-
-    def get_data(self):
-        if self.loop_mode:
-            last_data = self.get_data_loop_mode()
-        else:
-            last_data = self.get_data_normal_mode()
-
-        if not last_data:
-            return None
-
-        parsed = self.parse_xml(last_data)
-        if parsed is None:
-            return None
-
-        data = dict()
-        for idx, root in enumerate(parsed.findall('gpu')):
-            gpu = GPU(idx, root, self.exclude_zero_memory_users)
-            gpu_data = gpu.data()
-            # self.debug(gpu_data)
-            gpu_data = dict((k, v) for k, v in gpu_data.items() if is_gpu_data_value_valid(v))
-            data.update(gpu_data)
-            self.update_processes_mem_chart(gpu)
-            self.update_processes_user_mem_chart(gpu)
-
-        return data or None
-
-    def update_processes_mem_chart(self, gpu):
-        ps = gpu.processes()
-        if not ps:
-            return
-        chart = self.charts['gpu{0}_{1}'.format(gpu.num, PROCESSES_MEM)]
-        active_dim_ids = []
-        for p in ps:
-            dim_id = 'gpu{0}_process_mem_{1}'.format(gpu.num, p['pid'])
-            active_dim_ids.append(dim_id)
-            if dim_id not in chart:
-                chart.add_dimension([dim_id, '{0} {1}'.format(p['pid'], p['process_name'])])
-        for dim in chart:
-            if dim.id not in active_dim_ids:
-                chart.del_dimension(dim.id, hide=False)
-
-    def update_processes_user_mem_chart(self, gpu):
-        ps = gpu.processes()
-        if not ps:
-            return
-        chart = self.charts['gpu{0}_{1}'.format(gpu.num, USER_MEM)]
-        active_dim_ids = []
-        for p in ps:
-            if not p.get('username'):
-                continue
-            dim_id = 'gpu{0}_user_mem_{1}'.format(gpu.num, p['username'])
-            active_dim_ids.append(dim_id)
-            if dim_id not in chart:
-                chart.add_dimension([dim_id, '{0}'.format(p['username'])])
-
-        for dim in chart:
-            if dim.id not in active_dim_ids:
-                chart.del_dimension(dim.id, hide=False)
-
-    def check(self):
-        if not self.poller.has_smi():
-            self.error("couldn't find '{0}' binary".format(NVIDIA_SMI))
-            return False
-
-        raw_data = self.poller.run_once()
-        if not raw_data:
-            self.error("failed to invoke '{0}' binary".format(NVIDIA_SMI))
-            return False
-
-        parsed = self.parse_xml(raw_data)
-        if parsed is None:
-            return False
-
-        gpus = parsed.findall('gpu')
-        if not gpus:
-            return False
-
-        self.create_charts(gpus)
-
-        return True
-
-    def parse_xml(self, data):
-        try:
-            return et.fromstring(data)
-        except et.ParseError as error:
-            self.error('xml parse failed: "{0}", error: {1}'.format(data, error))
-
-        return None
-
-    def create_charts(self, gpus):
-        for idx, root in enumerate(gpus):
-            order, charts = gpu_charts(GPU(idx, root))
-            self.order.extend(order)
-            self.definitions.update(charts)
-
-
-def is_gpu_data_value_valid(value):
-    try:
-        int(value)
-    except (TypeError, ValueError):
-        return False
-    return True
diff --git a/collectors/python.d.plugin/nvidia_smi/nvidia_smi.conf b/collectors/python.d.plugin/nvidia_smi/nvidia_smi.conf
deleted file mode 100644
index 3d2a30d41..000000000
--- a/collectors/python.d.plugin/nvidia_smi/nvidia_smi.conf
+++ /dev/null
@@ -1,68 +0,0 @@
-# netdata python.d.plugin configuration for nvidia_smi
-#
-# This file is in YaML format. Generally the format is:
-#
-# name: value
-#
-# There are 2 sections:
-#  - global variables
-#  - one or more JOBS
-#
-# JOBS allow you to collect values from multiple sources.
-# Each source will have its own set of charts.
-#
-# JOB parameters have to be indented (using spaces only, example below).
-
-# ----------------------------------------------------------------------
-# Global Variables
-# These variables set the defaults for all JOBs, however each JOB
-# may define its own, overriding the defaults.
-
-# update_every sets the default data collection frequency.
-# If unset, the python.d.plugin default is used.
-# update_every: 1
-
-# priority controls the order of charts at the netdata dashboard.
-# Lower numbers move the charts towards the top of the page.
-# If unset, the default for python.d.plugin is used.
-# priority: 60000
-
-# penalty indicates whether to apply penalty to update_every in case of failures.
-# Penalty will increase every 5 failed updates in a row. Maximum penalty is 10 minutes.
-# penalty: yes
-
-# autodetection_retry sets the job re-check interval in seconds.
-# The job is not deleted if check fails.
-# Attempts to start the job are made once every autodetection_retry.
-# This feature is disabled by default.
-# autodetection_retry: 0
-
-# ----------------------------------------------------------------------
-# JOBS (data collection sources)
-#
-# The default JOBS share the same *name*. JOBS with the same name
-# are mutually exclusive. Only one of them will be allowed running at
-# any time. This allows autodetection to try several alternatives and
-# pick the one that works.
-#
-# Any number of jobs is supported.
-#
-# All python.d.plugin JOBS (for all its modules) support a set of
-# predefined parameters. These are:
-#
-# job_name:
-#     name: myname            # the JOB's name as it will appear at the
-#                             # dashboard (by default is the job_name)
-#                             # JOBs sharing a name are mutually exclusive
-#     update_every: 1         # the JOB's data collection frequency
-#     priority: 60000         # the JOB's order on the dashboard
-#     penalty: yes            # the JOB's penalty
-#     autodetection_retry: 0  # the JOB's re-check interval in seconds
-#
-# Additionally to the above, example also supports the following:
-#
-# loop_mode: yes/no                 # default is yes. If set to yes `nvidia-smi` is executed in a separate thread using `-l` option.
-# poll_seconds: SECONDS             # default is 1. Sets the frequency of seconds the nvidia-smi tool is polled in loop mode.
-# exclude_zero_memory_users: yes/no # default is no. Whether to collect users metrics with 0Mb memory allocation.
-#
-# ----------------------------------------------------------------------