GPU Fleet Viewer

A fast, privacy-friendly research workstation for finding, understanding, and using NVIDIA GPUs across SSH servers without leaving VS Code.

GPU Fleet Viewer 1.1 research dashboard

Highlights

Find available GPUs across every configured SSH host with explainable availability rules.
Search and filter by server, GPU model, user, process command, or Slurm job.
Responsive server bands and independent process inspectors for dense 8-GPU machines.
GPU utilization, memory, temperature, power draw/limit, and fan speed.
Click-to-inspect process details: owner, PID, full command, runtime, GPU memory, and optional Slurm job.
One-click research terminals with a stable GPU UUID in CUDA_VISIBLE_DEVICES; commands are prepared but never auto-executed.
Lightweight host health for CPU load, RAM, root disk, uptime, and SSH latency.
Local server aliases, groups, favorites, and duplicate physical-host detection.
Configurable metrics, warning thresholds, notifications, refresh interval, and SSH timeout.
Available-GPU count in the VS Code status bar.
Direct Connect SSH action for Remote - SSH users.
High-performance SSH snapshots, bounded concurrency, hidden-panel pausing, cached Slurm metadata, duplicate-query suppression, and overlapping-refresh protection.
No telemetry and no stored passwords or private keys.

Requirements

VS Code 1.80 or newer.
ssh available on the computer running VS Code.
nvidia-smi installed on each monitored server.
Non-interactive SSH authentication, normally an SSH key and BatchMode=yes compatibility.
Optional: Remote - SSH for the Connect SSH button.

Install

Install GPU Fleet Viewer from the Visual Studio Marketplace, search for GPU Fleet Viewer in the VS Code Extensions view, or run:

code --install-extension yruichen.gpu-fleet-viewer

For offline installation, download the latest .vsix from GitHub Releases, then run:

code --install-extension gpu-fleet-viewer-1.1.0.vsix

Reload VS Code and open GPU Fleet from the Activity Bar.

Configure servers

The extension discovers concrete hosts from ~/.ssh/config; wildcard entries are ignored. A minimal entry looks like this:

Host gpu-node-01
    HostName 192.0.2.10
    User researcher
    IdentityFile ~/.ssh/id_ed25519

You can also run GPU Fleet Viewer: Add Server and enter an SSH alias, hostname, IP address, or user@host. Use Configure Servers from the view toolbar to hide hosts you do not want to monitor.

Research workflow

Run GPU Fleet Viewer: Find Available GPU, or filter the dashboard to Available.
Review the availability explanation, free memory, host health, and active users.
Select Open terminal. The extension creates an integrated terminal and prepares an SSH command that exports CUDA_DEVICE_ORDER=PCI_BUS_ID and the selected GPU UUID.
Inspect the command and press Enter when ready. GPU Fleet Viewer never starts or stops research jobs automatically.

When Slurm is installed, the extension detects it automatically and associates local GPU processes with visible job metadata. Ordinary SSH servers continue to work without Slurm.

Settings

Search for GPU Fleet Viewer in VS Code Settings.

Setting	Default	Purpose
`gpu-fleet-viewer.autoRefresh`	`true`	Refresh automatically
`gpu-fleet-viewer.refreshInterval`	`5`	Refresh interval in seconds
`gpu-fleet-viewer.sshTimeout`	`8`	SSH and command timeout in seconds
`gpu-fleet-viewer.maxConcurrentHosts`	`8`	Bound concurrent SSH snapshots
`gpu-fleet-viewer.pauseWhenHidden`	`true`	Stop automatic SSH work while the dashboard is hidden
`gpu-fleet-viewer.compactLayout`	`true`	Use the dense fleet matrix
`gpu-fleet-viewer.showUtilization`	`true`	Show GPU utilization
`gpu-fleet-viewer.showTemperature`	`true`	Show GPU temperature
`gpu-fleet-viewer.showPower`	`true`	Show power draw and limit
`gpu-fleet-viewer.showFanSpeed`	`true`	Show fan speed when supported
`gpu-fleet-viewer.showProcesses`	`true`	Show process inspection
`gpu-fleet-viewer.showHostHealth`	`true`	Show load, RAM, disk, uptime, and latency
`gpu-fleet-viewer.enableSlurmIntegration`	`true`	Detect Slurm and associate jobs
`gpu-fleet-viewer.slurmRefreshInterval`	`30`	Cache duration for Slurm metadata
`gpu-fleet-viewer.availabilityRequireNoProcesses`	`true`	Require no compute processes
`gpu-fleet-viewer.availabilityMaxMemoryMiB`	`512`	Maximum used memory for availability
`gpu-fleet-viewer.availabilityMaxUtilization`	`10`	Maximum utilization for availability
`gpu-fleet-viewer.showStatusBar`	`true`	Show fleet availability in the status bar
`gpu-fleet-viewer.enableNotifications`	`false`	Notify on newly crossed warning thresholds

Target lists, ignored hosts, SSH config path, and warning thresholds are also configurable. Settings from the earlier gpu-server-viewer namespace are migrated automatically on first activation.

Security and privacy

GPU Fleet Viewer invokes your system ssh client with argument-safe execution, key-only batch mode, and a configurable timeout. Hosts and GPU identifiers received from the Webview are validated again in the extension host. It reads your SSH config but never reads or stores private-key contents. Monitoring data stays between VS Code and the servers you configured; the extension has no telemetry service, backend, persistent metric history, or job-control endpoint.

Please report vulnerabilities privately as described in SECURITY.md.

Support

See SUPPORT.md for troubleshooting and support channels. Bug reports and feature requests are welcome in GitHub Issues.

Development

npm ci
npm test
npx vsce package

For a standalone local preview:

npm run preview:build
python3 -m http.server 8765 --bind 127.0.0.1

Then open http://127.0.0.1:8765/preview/.

See CONTRIBUTING.md before submitting a change. Maintainers can find the release checklist in docs/PUBLISHING.md.

Acknowledgements

GPU Fleet Viewer is based on GPU Server Viewer by Riku-0801 and includes substantial UI, performance, reliability, configuration, and testing changes. See NOTICE for attribution.

Licensed under the Apache License 2.0.