JUmPER Extension

This is JUmPER IPython extension for real-time performance monitoring in IPython environments and Jupyter notebooks. It allows you to gather performance data on CPU usage, memory consumption, GPU utilization, and I/O operations for individual cells and present it in the notebook/IPython session either as text report or as a plot. The extension can be naturally integrated with JUmPER Jupyter kernel for most comprehensive analysis of notebook.

Installation

pip install .

Quick Start

Load the Extension

%load_ext jumper_extension

Basic Usage

1. Start monitoring:

   %perfmonitor_start [interval]

   interval is an optional argument for configuring frequency of performance data gathering (in seconds), set to 1 by default. This command launches a performance monitoring daemon.

2. Run your code

3. View performance report:

   %perfmonitor_perfreport [cell]

   Will print aggregate performance report for entire notebook execution so far:

   ----------------------------------------
   Performance Report
   ----------------------------------------
   Duration: 11.08s
   Metric                    AVG      MIN      MAX      TOTAL   
   -----------------------------------------------------------------
   CPU Util (Across CPUs)    10.55    3.86     45.91    -       
   Memory (GB)               7.80     7.74     7.99     15.40   
   GPU Util (Across GPUs)    27.50    5.00     33.00    -       
   GPU Memory (GB)           0.25     0.23     0.32     4.00    
   

   Pass cell number to see only this cell performance report. Refer to %cell_history to identify it from notebook execution history.

4. Plot performance data:

   %perfmonitor_plot [cell]

   Plot a more detailed overview of performance metrics over time.

5. Stop monitoring:

   %perfmonitor_stop

6. Export data for external analysis

   %perfmonitor_export_perfdata my_performance.csv
   %perfmonitor_export_cell_history my_cells.json

   Export performance measurements for entire notebook and cell execution history with timestamps, allowing you to project measurements onto specific cells.

Available Commands

Command	Description
%perfmonitor_help	Show all available commands
%perfmonitor_resources	Display available hardware resources
%perfmonitor_start [interval]	Start monitoring (default: 1 second interval)
%perfmonitor_stop	Stop monitoring
%perfmonitor_perfreport [cell]	Show performance report for specific cell or latest
%perfmonitor_plot [cell]	Plot performance data for specific cell or all data
%cell_history [--df]	Show execution history of all cells (or DataFrame)
%cell_history_stats	Show detailed cell execution statistics
%perfmonitor_enable_perfreports	Auto-generate reports after each cell
%perfmonitor_disable_perfreports	Disable auto-reports
%perfmonitor_export_perfdata [filename]	Export performance data to CSV
%perfmonitor_export_cell_history [filename]	Export cell history to CSV/JSON