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KempnerPulse

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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 endpoint, synthesizes a weighted Real Utilization score and a 12-category workload classification, and renders four interactive views in the terminal.

KempnerPulse demo

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

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 for uv specifics, the supported-GPU list, and running on a SLURM compute node.

Quick start

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/

License

MIT. See LICENSE.

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