Metadata-Version: 2.4
Name: kempnerpulse
Version: 0.5.0
Summary: Real-time GPU monitoring dashboard for NVIDIA DCGM metrics on HPC clusters
Author: Kempner Institute, Harvard University
License: MIT License
        
        Copyright (c) 2026 Kempner Institute, Harvard University
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Project-URL: Homepage, https://github.com/KempnerInstitute/kempnerpulse
Project-URL: Issues, https://github.com/KempnerInstitute/kempnerpulse/issues
Keywords: gpu,monitoring,dcgm,nvidia,dashboard,hpc
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: System :: Monitoring
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: rich>=13.0
Dynamic: license-file

# KempnerPulse

[![PyPI](https://img.shields.io/pypi/v/kempnerpulse)](https://pypi.org/project/kempnerpulse/) [![Tests](https://github.com/KempnerInstitute/kempnerpulse/actions/workflows/tests.yml/badge.svg)](https://github.com/KempnerInstitute/kempnerpulse/actions/workflows/tests.yml)

> `nvidia-smi` says 100% GPU utilization — but are your tensor cores even active? KempnerPulse shows what's *actually* happening.

A terminal dashboard for **NVIDIA DCGM hardware-counter metrics**, with
SLURM/CUDA GPU-visibility awareness. It reads DCGM profiling counters (SM Active,
Tensor Active, DRAM Active, …) directly from `dcgmi dmon` (~100 ms) or from a
[dcgm-exporter](https://github.com/NVIDIA/dcgm-exporter) endpoint, synthesizes a
weighted **Real Utilization** score and a **12-category workload
classification**, and renders four interactive views in the terminal.

![KempnerPulse demo](https://raw.githubusercontent.com/KempnerInstitute/kempnerpulse/main/docs/images/kempner_pulse_screen_record.gif)

## Highlights

- **Four views** — Fleet, Focus (per-GPU sparkline history), Plot (line charts), Job (running processes).
- **Real Utilization** — a weighted composite of SM / Tensor / DRAM / GR-engine counters, with AI, HPC, and memory-bound presets.
- **12-category workload classification** plus health monitoring (thermal, PCIe replay, ECC), from NVIDIA's DCGM profiling guidance.
- **Three backends** — `dcgm` (direct `dcgmi dmon`), `prometheus` (`dcgm-exporter`), and `replay` (a saved capture, no GPU needed).
- **SLURM / CUDA aware** — shows only your allocated GPUs.
- **Lightweight** — standard library + `rich`; ~8% of one CPU core.

## Install

```bash
uv tool install kempnerpulse     # isolated `kempnerpulse` + `kp` commands
# or: pip install kempnerpulse
```

Requires Linux, Python ≥ 3.9, and NVIDIA data-center GPUs; the `dcgm` backend
needs the DCGM host engine. See the
[installation guide](https://kempnerinstitute.github.io/kempnerpulse/getting-started/install.html)
for uv specifics, the supported-GPU list, and running on a SLURM compute node.

## Quick start

```bash
kempnerpulse                      # live dashboard (or `kp`)
kp --focus-gpu 0                  # start focused on GPU 0
kp --hpc-weights                  # HPC weight preset
kp --export all > metrics.csv     # CSV capture
kp --backend prometheus --source http://host:9400/metrics
```

Press `Ctrl-C` to quit; type `:focus <id>`, `:plot`, `:job`, or `:q` to switch views.

## Documentation

**Full documentation: <https://kempnerinstitute.github.io/kempnerpulse/>**

- [Quickstart](https://kempnerinstitute.github.io/kempnerpulse/getting-started/quickstart.html) and [Views](https://kempnerinstitute.github.io/kempnerpulse/getting-started/views.html)
- [CLI reference](https://kempnerinstitute.github.io/kempnerpulse/guide/cli.html) — every flag and interactive command
- [Architecture](https://kempnerinstitute.github.io/kempnerpulse/architecture.html) — the four-layer pipeline
- [Workload classification](https://kempnerinstitute.github.io/kempnerpulse/classification.html) and [canonical schema](https://kempnerinstitute.github.io/kempnerpulse/schema.html)
- [CSV export](https://kempnerinstitute.github.io/kempnerpulse/export.html) and [DCGM metrics](https://kempnerinstitute.github.io/kempnerpulse/metrics.html)

## License

MIT. See [LICENSE](LICENSE).
