Andromeda Cluster
Andromeda Aerospace · HPC software · Windows & Linux

Every computer you own, scheduled as one machine.

Andromeda Cluster pools your workstations, laptops and GPU boxes into one queue. Its AI scheduler learns how long your jobs take and how much memory they need, then packs them onto the machines that will finish them first.

Download free See Pro & Premium No cloud. No account. One executable.
queue · 14 jobs · 3 nodes · 28 CPUsmedian runtime error ±7.4%
lab-ws-0116 CPU · 64 GB · 1.31×
solve --n 4096
cfd mesh=fine
solve --n 2048
render-box8 CPU · RTX 4090 · 1.00×
train.py --epochs 40 · gpu0
infer --batch 256
laptop8 CPU · 16 GB · 0.68×
fft 2^20
fft 2^20
fft 2^20
post.py run_7
fft 2^21
0 min15304560
actual runtimeAI predictionLong jobs go to the fastest node; short ones fill the gaps.
The AI scheduler

It learns your workload from the jobs you already run

There is nothing to configure. Every finished job is a training example, stored and learned on your own coordinator.

  1. Run

    Submit commands as you normally would. Node agents report wall time and peak memory for every job.

  2. Learn

    Each command is fitted as a power law of its numeric arguments. After two or three runs it knows how runtime and memory grow with --n, --steps or mesh=. It also learns how fast each machine really is.

  3. Place

    Short jobs go first, waiting jobs climb the queue, memory is reserved from the prediction so nothing runs out, and long jobs land where they finish soonest.

$ andromeda-cluster predict "./solve --n 8000"
--nmeasuredpeak memoryAI estimate
10000m 38s310 MB·
20002m 31s1.2 GB·
400010m 06s4.9 GB9m 52s
8000not run yet≈ 19.6 GB≈ 40m 20s
Learned exponent 2.0 for runtime, 2.0 for memory. The scheduler will not start this job on a node with less than 23.5 GB free (prediction + 20 % headroom). Example figures.
What you get

A real cluster scheduler, sized for a lab or a home office

All editions

One-click start

Run the app and your computer becomes the coordinator and first node. Other machines join with one command.

All editions

Job arrays

Submit 240 render frames or parameter sweeps in one line with {i} in the command.

All editions

Live dashboard

Nodes, loads, queues and streaming logs in the browser. Cancel, drain and resubmit without a terminal.

Pro

GPU scheduling

NVIDIA GPUs are detected and handed out per job through CUDA_VISIBLE_DEVICES, never shared by accident.

Pro

Pipelines and retries

--after 12,13 waits for earlier jobs. --retries 2 reruns flaky steps automatically.

Pro

Dashboard anywhere

Open the dashboard from your phone or any computer on the network.

Premium

Team tokens

Give each person their own REST API token. They see and submit only their own jobs.

Premium

Fair-share

Whoever used the cluster most in the last 24 hours waits a little longer, so nobody can hog it.

Premium

Webhooks

Get a JSON POST when a job finishes or fails. Wire it into Slack, CI or your own tools.

Editions

Pay once. Keep it forever.

Every licence is perpetual and includes a year of updates. Only the coordinator needs a key. Nodes are always free, so a 30-machine cluster costs the same as a 3-machine one.

Community

€0

For trying it out and small home setups.

  • Up to 4 nodes
  • Priority and first-come scheduling
  • Dashboard and CLI on the coordinator
  • Job arrays and live logs
Download

Pro Most popular

€99one time

For researchers, engineers and render nodes.

  • Up to 32 nodes
  • AI runtime and memory prediction
  • Fastest-node placement and tight packing
  • GPU scheduling
  • Job dependencies and automatic retries
  • Dashboard from any device

Premium

€299one time

For labs and teams sharing machines.

  • Unlimited nodes
  • Everything in Pro
  • Per-user REST API tokens
  • Fair-share between users
  • Webhooks

Enter your email, then choose Pro or Premium. Payment is handled by Stripe.

Prices in EUR. Any applicable tax is shown at checkout. Your key appears on this page right after payment and is also sent by email.

CommunityProPremium
Nodes432Unlimited
Dashboard, CLI, job arrays, logs✓✓✓
AI runtime and memory prediction–✓✓
GPU scheduling–✓✓
Dependencies and retries–✓✓
Dashboard from other devices–✓✓
Per-user API tokens––✓
Fair-share and webhooks––✓
Download

Install it on every computer you want to pool

One download contains the coordinator, the node agent and the dashboard. Every edition uses the same installer; your licence key unlocks Pro or Premium.

Checking for the latest tested release…

Windows

Windows 10 or 11 · x86_64

Windows download unavailable

Run the setup file. It adds Andromeda Cluster to the Start menu and the andromeda-cluster command to your terminal.

Linux

Ubuntu 22.04+ / Debian 12+ · x86_64

Linux download unavailable

Extract the archive and run ./install.sh. It installs the command for your user and adds a menu entry.

Three commands to a working cluster

# 1. On your main computer: start the coordinator and dashboard
andromeda-cluster

# 2. On every other computer: join with the token the dashboard shows
andromeda-cluster node --join 192.168.1.20:7450 --token <cluster-token>

# 3. Submit work from anywhere on the network
andromeda-cluster submit "python simulate.py --n 4000" --cpus 8
Questions

Before you install

Can I mix Windows and Linux machines?

Yes. Each node runs its jobs with its own shell, so pin OS-specific jobs to a node or keep commands portable, like python script.py.

Does my data leave my network?

No. Jobs, logs and the learned model stay on your coordinator. Activation is offline.

Is the traffic encrypted?

Machines authenticate with a challenge so the cluster token never crosses the wire, but job traffic is not encrypted. Use it on a trusted network or over a VPN.

What happens if a machine goes offline?

Its running jobs go back in the queue and start on another node. The scheduler notices within 15 seconds.

Does the AI need the internet?

No. The scheduler learns from your own finished jobs with a small model that runs on the coordinator. There is no LLM and no online AI service.

Does it replace Slurm?

For a few to a few dozen machines without a sysadmin, often yes. For a university cluster with hundreds of nodes, keep Slurm.