runqd 0.4.12

A lightweight, single-node job scheduler written in Rust.

gflow - A lightweight, single-node job scheduler

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gflow is a lightweight, single-node job scheduler written in Rust, inspired by Slurm. It is designed for efficiently managing and scheduling tasks, especially on machines with GPU resources.

Demo

Core Features

• Daemon-based Scheduling: A persistent daemon (gflowd) manages the job queue and resource allocation.
• Rich Job Submission: Supports dependencies, priorities, job arrays, and time limits via the gbatch command.
• Time Limits: Set maximum runtime for jobs (similar to Slurm's --time) to prevent runaway processes.
• Webhooks: Send HTTP POST notifications on job state changes and other events.
• Service and Job Control: Provides clear commands to inspect the scheduler state (ginfo), query the job queue (gqueue), and control job states (gcancel).
• tmux Integration: Uses tmux for robust, background task execution and session management.
• Output Logging: Automatic capture of job output to log files via tmux pipe-pane.
• Simple Command-Line Interface: Offers a user-friendly and powerful set of command-line tools.

Component Overview

The gflow suite consists of several command-line tools:

• gflowd: The scheduler daemon that runs in the background, managing jobs and resources.
• ginfo: Displays scheduler and GPU information.
• gbatch: Submits jobs to the scheduler, similar to Slurm's sbatch.
• gqueue: Lists and filters jobs in the queue, similar to Slurm's squeue.
• gjob: Job inspection and control (logs, attach, update, redo, ...).
• gctl: Daemon/runtime control utilities (e.g. GPU restriction).
• gcancel: Cancels jobs.

Installation

Install via PyPI (Recommended)

Install gflow using pipx (recommended for CLI tools):

pipx install runqd

Or using uv:

uv tool install runqd

Or using pip:

pip install runqd

This will install pre-built binaries for Linux (x86_64, ARM64).

Install Nightly Build

To try the latest development version, install from TestPyPI:

pip install --index-url https://test.pypi.org/simple/ runqd

Install via cargo

cargo install gflow

cargo install(main branch)

cargo install --git https://github.com/AndPuQing/gflow.git --locked

This will install all the necessary binaries (gflowd, ginfo, gbatch, gqueue, gcancel, gjob, gctl).

Build Manually

1. Clone the repository:

   git clone https://github.com/AndPuQing/gflow.git
   cd gflow
   

2. Build the project:

   cargo build --release
   

   The executables will be available in the target/release/ directory.

Quick Start

0. (Optional) Initialize configuration:

   gflowd init
   

   This creates ~/.config/gflow/gflow.toml with sensible defaults.

1. Start the scheduler daemon:

   gflowd up
   

   Run this in a dedicated terminal or tmux session and leave it running. You can check its health at any time with gflowd status and inspect resources with ginfo.

2. Submit a job: Create a script my_job.sh:

   #!/bin/bash
   echo "Starting job on GPU: $CUDA_VISIBLE_DEVICES"
   sleep 30
   echo "Job finished."
   

   Submit it using gbatch:

   gbatch --gpus 1 ./my_job.sh
   

3. Check the job queue:

   gqueue
   

   You can also watch the queue update live: watch --color gqueue.

4. Stop the scheduler:

   gflowd down
   

   This shuts down the daemon and cleans up the tmux session.

Documentation

• Website: https://andpuqing.github.io/gflow/
• Installation: docs/src/getting-started/installation.md
• Quick start: docs/src/getting-started/quick-start.md
• Job submission: docs/src/user-guide/job-submission.md
• Time limits: docs/src/user-guide/time-limits.md
• Configuration: docs/src/user-guide/configuration.md
• Command quick reference: docs/src/reference/quick-reference.md

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Contributing

If you find any bugs or have feature requests, feel free to create an Issue and contribute by submitting Pull Requests.

License

gflow is licensed under the MIT License. See LICENSE for more details.