Getting Started

Overview

Lattice is a distributed workload scheduler for HPC and AI infrastructure. It schedules both batch jobs (training runs, simulations) and long-running services (inference endpoints, monitoring) on shared GPU-accelerated clusters.

If you’re coming from Slurm, most concepts map directly — see the Slurm migration guide for a quick comparison.

Prerequisites

A running Lattice cluster (ask your admin for the API endpoint)
The lattice CLI installed on your workstation or login node
Your tenant credentials (OIDC token or mTLS certificate)

Installing the CLI

# Determine architecture
ARCH=$(uname -m | sed 's/aarch64/arm64/')

# Download from GitHub Releases
curl -sSfL "https://github.com/witlox/lattice/releases/latest/download/lattice-${ARCH}.tar.gz" | tar xz
sudo mv lattice /usr/local/bin/

# Or build from source
cargo build --release -p lattice-cli
sudo cp target/release/lattice /usr/local/bin/

Configuration

Create ~/.config/lattice/config.yaml:

endpoint: "lattice-api.example.com:50051"
tenant: "my-team"
# Optional: default vCluster
vcluster: "gpu-batch"

Or use environment variables:

export LATTICE_ENDPOINT="lattice-api.example.com:50051"
export LATTICE_TENANT="my-team"

Your First Job

Submit a batch script

lattice submit train.sh
# Submitted allocation a1b2c3d4

Check status

lattice status
# ID        NAME           STATE    NODES  WALLTIME   ELAPSED    VCLUSTER
# a1b2c3d4  train.sh       Running  4      24:00:00   00:12:34   gpu-batch

View logs

lattice logs a1b2c3d4
# [2026-03-05T10:00:12Z] Epoch 1/100, loss=2.341
# [2026-03-05T10:01:45Z] Epoch 2/100, loss=1.892

Cancel a job

lattice cancel a1b2c3d4

Next Steps

Submitting Workloads — detailed submission options
Interactive Sessions — attach a terminal to running jobs
DAG Workflows — multi-step pipelines with dependencies
Python SDK — programmatic access from notebooks and agents

Keyboard shortcuts

Lattice Documentation