Apache License 2.0

项目介绍

spark-arena/sparkrun 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 Apache License 2.0 许可证,目前获得 559 个 Star、60 次 Fork。

仓库全名
spark-arena/sparkrun
开源许可证
Apache License 2.0
Star 数
559
Fork 数
60
未关闭 Issue
10

README 摘要

One command to rule them all Launch, manage, and stop LLM inference workloads on one or more NVIDIA DGX Spark systems — no Slurm, no Kubernetes, no fuss. Documentation · Quick Start · Recipes · Spark Arena Install One command — installs sparkrun, then launches the guided setup wizard to create a cluster, configure SSH mesh, detect ConnectX-7 NICs, set up sudoers, and enable earlyoom. Quick Start…

完整内容见 GitHub 原始 README 或本页 。

常见问题

sparkrun 用什么语言开发?

主要使用 Python 编写,采用 Apache License 2.0 许可证,目前有 559 个 Star。

sparkrun 可以免费商用吗?

仓库采用 Apache License 2.0 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 sparkrun 的源码?

可以直接克隆仓库:git clone https://github.com/spark-arena/sparkrun.git,默认分支为 main;安装与运行步骤见仓库 README。

sparkrun 最近还在维护吗?

仓库最近一次更新为 4 天前,当前有 10 个未关闭 Issue;Star 数为 559,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

sparkrun - launch, manage, and stop LLM inference workloads on NVIDIA DGX Spark systems

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
685
价值分
353
活跃状态
活跃

语言占比

Python
Shell
TypeScript

Release

README

sparkrun — Part of the Spark Arena ecosystem

PyPI version License Documentation Spark Arena

One command to rule them all

Launch, manage, and stop LLM inference workloads on one or more NVIDIA DGX Spark systems — no Slurm, no Kubernetes, no fuss.

Documentation · Quick Start · Recipes · Spark Arena


Install

uvx sparkrun setup

One command — installs sparkrun, then launches the guided setup wizard to create a cluster, configure SSH mesh, detect ConnectX-7 NICs, set up sudoers, and enable earlyoom.

Quick Start

# Run an inference workload
sparkrun run qwen3-1.7b-vllm

# Multi-node tensor parallelism (TP maps to node count on DGX Spark)
sparkrun run qwen3-1.7b-vllm --tp 2

# Re-attach to logs, stop a workload, check status
sparkrun logs qwen3-1.7b-vllm
sparkrun stop qwen3-1.7b-vllm
sparkrun status

Ctrl+C detaches from logs — it never kills your inference job. Your model keeps serving.

See the full CLI reference for all commands and options.

Highlights

  • Multi-runtime — vLLM, SGLang, llama.cpp out of the box
  • Multi-node tensor parallelism — --tp 2 = 2 hosts, automatic InfiniBand/RDMA detection
  • VRAM estimation — know if your model fits before you launch (sparkrun show <recipe>)
  • Git-based recipe registries — we publish official recipes, community recipes, and benchmarked recipes via Spark Arena, plus you can add your own registries.
  • Guided setup wizard — cluster creation, SSH mesh, CX7 auto-detection, sudoers, earlyoom
  • Model & container distribution — syncs models and images to cluster nodes over SSH automatically

Spark Arena

Spark Arena is the community hub for DGX Spark recipe benchmarks — browse benchmark results, then run them directly with sparkrun.

Official Recipes

Official Recipes are maintained by the Spark Arena team and hosted on GitHub. They are tested and optimized for NVIDIA DGX Spark systems.

Community Recipes

Community Recipes are contributed by the community and hosted on GitHub.

scitrera.ai

License

Apache License 2.0 — see LICENSE for details.

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