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GeezerVison is showing github.com — gmond_python_modules/gpu/nvidia at master · longyn/gmond_python_modules

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conf.d
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graph.d
 
 
nvidia-ml-py-3.295.00
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python_modules
python_modules
 
 
README
README
 
 
ganglia_web.patch
ganglia_web.patch
 
 

README

NVIDIA GPU monitoring plugin for gmond
======================================

Installation instructions:
* First install the Python Bindings for the NVIDIA Management Library:
  $ cd nvidia-ml-py-*
  $ sudo python setup.py install
  For the latest bindings see: http://pypi.python.org/pypi/nvidia-ml-py/ 
  You can do a site install or place it in {libdir}/ganglia/python_modules
* Copy python_modules/nvidia.py to {libdir}/ganglia/python_modules
* Copy conf.d/nvidia.pyconf to /etc/ganglia/conf.d
* Copy graph.d/* to {ganglia_webroot}/graph.d/
* A demo of what the GPU graphs look like is available here:
  http://ganglia.ddbj.nig.ac.jp/?c=research+month+gpu+queue&h=t135i&m=load_one&r=hour&s=by+name&hc=4&mc=2

By default all metrics that the management library could detect for your GPU
are collected.  For more information on what metrics are supported on what
models, please refer to NVML documentation.

The following metrics have been implemented:
* gpu_num
* gpu_driver
* gpu_type
* gpu_uuid
* gpu_pci_id
* gpu_mem_total
* gpu_graphics_speed
* gpu_sm_speed
* gpu_mem_speed
* gpu_max_graphics_speed
* gpu_max_sm_speed
* gpu_max_mem_speed
* gpu_temp
* gpu_util
* gpu_mem_util
* gpu_mem_used
* gpu_fan
* gpu_power_usage
* gpu_perf_state
* gpu_ecc_mode

Version 2:

The following metrics have been implemented:
* gpu_max_graphics_speed
* gpu_max_sm_speed
* gpu_max_mem_speed
* gpu_serial
* gpu_power_man_mode
* gpu_power_man_limit

Version 3:

The following metrics have been implemented:
* gpu_ecc_db_error
* gpu_ecc_sb_error’
* gpu_power_violation_report
* gpu_encoder_util
* gpu_decoder_util
* gpu_bar1_memory
* gpu_shutdown_temp
* gpu_slowdown_temp

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