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GPU Compute Budget Estimator

Enter how many methods, datasets, and seeds you'll run, and how long each run takes. Get total GPU-hours, an estimated cost, wall-clock time, and a sentence you can paste into a proposal. Everything runs in your browser.

Your experiments

Variants of your method

The full model plus every ablation.

Baselines

Datasets

Seeds per configuration

3 is the minimum reviewers expect; 5+ is better.

Cost of one run

Your method

hours

Wall-clock time for one run.

A baseline

hours

GPUs per run

Multi-GPU runs multiply GPU-hours.

GPUs you can use at once

For the wall-clock estimate.

Hyperparameter tuning

Trials per method, per dataset

Length of a trial

% of a full run

Trials are often shorter than final runs.

Assumes every method is tuned once per dataset, and that ablation variants reuse your method's settings.

Price

Where will you run it?

Illustrative rate. Check your provider's current price.

Price per GPU-hour

USD

Edit this to match your provider's current price.

Contingency

Reruns, bugs, and surprises. 20-30% is common.

Read the guide

SLURM Job Script Examples for PyTorch (Single GPU, Arrays, Multi-GPU)

Three working SLURM job scripts for ML research: one GPU, a job array across seeds, and multi-GPU with torchrun, plus the mistakes that waste the most time.

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Go deeper

HPC & Cloud GPUs for ML Research

SSH, SLURM, and cloud GPUs — run experiments at scale.

$249 · View the course

Free download

SLURM Starter Scripts for ML Research

Three job scripts (single GPU, job array, multi-GPU) and a cheat sheet for university HPC clusters.

Your method	36 runs	144 h
Baselines	27 runs	108 h
Tuning	120 trials	120 h
Contingency		93 h