An NVIDIA GPU monitoring plugin for the cjm-plugin-system that provides real-time hardware telemetry via nvitop.
Project description
cjm-system-monitor-nvidia
Install
pip install cjm_system_monitor_nvidia
Project Structure
nbs/
├── meta.ipynb # Metadata introspection for the NVIDIA monitor plugin used by cjm-ctl to generate the registration manifest
└── plugin.ipynb # Plugin implementation for NVIDIA GPU monitoring using nvitop
Total: 2 notebooks
Module Dependencies
graph LR
meta["meta<br/>meta"]
plugin["plugin<br/>plugin"]
No cross-module dependencies detected.
CLI Reference
No CLI commands found in this project.
Module Overview
Detailed documentation for each module in the project:
meta (meta.ipynb)
Metadata introspection for the NVIDIA monitor plugin used by cjm-ctl to generate the registration manifest
Import
from cjm_system_monitor_nvidia.meta import (
get_plugin_metadata
)
Functions
def get_plugin_metadata() -> Dict[str, Any]: # Plugin metadata for manifest generation
"""Return metadata required to register this plugin with the PluginManager."""
# Fallback base path (current behavior for backward compatibility)
base_path = os.path.dirname(os.path.dirname(sys.executable))
# Use CJM config if available, else fallback to env-relative paths
cjm_plugin_data_dir = os.environ.get("CJM_PLUGIN_DATA_DIR")
# Plugin data directory
plugin_name = "cjm-system-monitor-nvidia"
if cjm_plugin_data_dir
"Return metadata required to register this plugin with the PluginManager."
plugin (plugin.ipynb)
Plugin implementation for NVIDIA GPU monitoring using nvitop
Import
from cjm_system_monitor_nvidia.plugin import (
NvidiaMonitorPlugin
)
Classes
class NvidiaMonitorPlugin:
def __init__(self):
"""Initialize the NVIDIA monitor plugin."""
self.logger = logging.getLogger(f"{__name__}.{type(self).__name__}")
self.config = {}
@property
def name(self) -> str: # Tool identity, derived from the installed distribution (PILLAR 1c)
"NVIDIA System Monitor using nvitop (a pure-telemetry ToolCapability)."
def __init__(self):
"""Initialize the NVIDIA monitor plugin."""
self.logger = logging.getLogger(f"{__name__}.{type(self).__name__}")
self.config = {}
@property
def name(self) -> str: # Tool identity, derived from the installed distribution (PILLAR 1c)
"Initialize the NVIDIA monitor plugin."
def name(self) -> str: # Tool identity, derived from the installed distribution (PILLAR 1c)
"""Get the tool name (the installed distribution name)."""
from importlib.metadata import metadata, packages_distributions
# `__package__` is None in a notebook/__main__ context, so guard the
# derivation with the known package module name.
pkg = __package__ or "cjm_system_monitor_nvidia"
dist = (packages_distributions().get(pkg) or [pkg.replace("_", "-")])[0]
return metadata(dist)["Name"]
@property
def version(self) -> str: # Tool version
"Get the tool name (the installed distribution name)."
def version(self) -> str: # Tool version
"""Get the tool version string."""
from cjm_system_monitor_nvidia import __version__
return __version__
def initialize(
self,
config: Optional[Dict[str, Any]] = None # Configuration dictionary
) -> None
"Get the tool version string."
def initialize(
self,
config: Optional[Dict[str, Any]] = None # Configuration dictionary
) -> None
"Initialize or reconfigure the plugin."
def get_config_schema(self) -> Dict[str, Any]: # JSON Schema
"""Return JSON Schema for configuration."""
return {} # No config needed for monitoring
def get_current_config(self) -> Dict[str, Any]: # Current config
"Return JSON Schema for configuration."
def get_current_config(self) -> Dict[str, Any]: # Current config
"""Return current configuration."""
return self.config
def _get_gpu_info_internal(self) -> Dict[str, Any]: # Raw GPU data
"Return current configuration."
def get_system_status(self) -> SystemStats: # Current system telemetry
"""Collect host CPU/RAM + aggregated GPU stats as a typed SystemStats.
Per-process GPU usage is exposed separately via `list_processes()`. This
is the native-dispatch surface the substrate's `_get_global_stats` calls
for resource-derived admission (`MonitorToolProtocol`).
"""
# 1. Get Host CPU/RAM (psutil)
vm = psutil.virtual_memory()
# 2. Get GPU Data
gpu_raw = self._get_gpu_info_internal()
# 3. Aggregate GPU Stats for the Scheduler
total_vram_free = 0
total_vram_total = 0
total_vram_used = 0
max_load = 0
if gpu_raw['available']
"Collect host CPU/RAM + aggregated GPU stats as a typed SystemStats.
Per-process GPU usage is exposed separately via `list_processes()`. This
is the native-dispatch surface the substrate's `_get_global_stats` calls
for resource-derived admission (`MonitorToolProtocol`)."
def list_processes(self) -> List[ProcessStats]: # Per-process GPU usage
"Per-process GPU memory usage as typed ProcessStats.
Sources the same nvitop/nvidia-smi enumeration `get_system_status` uses;
returns `[]` when there is no GPU or no per-process attribution available.
The substrate's GPU subtree attribution intersects these PIDs with the
worker's process tree (`attribute_gpu_to_worker_subtree`)."
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