4.1 Introduction to PCluster
What is AWS ParallelCluster?
AWS ParallelCluster is an open-source cluster management tool that makes it easy to deploy and manage High Performance Computing (HPC) clusters on AWS. It uses a simple YAML configuration file to model and provision all the resources needed for your HPC applications in an automated and secure manner.
ParallelCluster supports job schedulers like Slurm, multiple instance types, automatic scaling, and shared storage — so you can focus on your research rather than infrastructure.
The Problem It Solves
Traditional HPC infrastructure requires significant upfront investment, long procurement cycles, and dedicated sysadmin expertise. ParallelCluster gives researchers elastic, on-demand HPC capacity that scales with their workload and costs nothing when idle.
| Challenge | How PCluster Helps |
|---|---|
| HPC hardware is expensive and fixed | Elastic clusters that scale to zero when idle |
| Cluster setup requires sysadmin expertise | YAML config file + automated provisioning |
| Long wait times for shared HPC queues | Your own dedicated cluster, ready in minutes |
| Software installation is painful | Spack package manager + shared filesystems |
| Collaboration requires shared infrastructure | Shareable config files for reproducible clusters |
Key Benefits
| Benefit | Description |
|---|---|
| Automatic Scaling | Compute nodes spin up when jobs are submitted and shut down when idle |
| Easy Cluster Management | Provision resources in a safe, repeatable manner via config files |
| Cost Efficiency | Pay only for what you use — zero cost when no jobs are running |
| Flexible Hardware | Access to CPU, GPU, and HPC-optimized instance types |
| Shared Storage | FSx for Lustre and EBS volumes shared across all nodes |
Who Should Use It?
Use PCluster if you:
- Need to run HPC workloads (CFD, molecular dynamics, weather modeling, etc.)
- Want elastic compute that scales with your job queue
- Need high-performance networking (EFA) between nodes
- Want to share cluster configurations with collaborators
- Need access to HPC-optimized instance types
Consider Compute Service or Loome if you:
- Just need a single VM for interactive analysis
- Don’t need multi-node parallel computing
- Prefer a fully managed portal experience
PCluster vs Other Platforms
| Feature | PCluster | Compute Service | Loome |
|---|---|---|---|
| Cloud Provider | AWS | AWS | Azure |
| Multi-Node HPC | ✅ Full Slurm clusters | ❌ Single VMs | ✅ HPC clusters |
| Auto-Scaling | ✅ Scale to zero | ❌ Manual | ✅ Configurable |
| Job Scheduler | Slurm | N/A | Slurm, PBS |
| High-Speed Networking | ✅ EFA (100 Gbps) | ❌ Standard | Varies |
| Setup Complexity | Medium | Low | Low |
| Best For | HPC research workloads | General research VMs | Azure HPC workloads |
Common Use Cases
| Use Case | Description | Recommended Instances |
|---|---|---|
| Computational Fluid Dynamics | OpenFOAM, ANSYS Fluent simulations | hpc6a, c6i (CPU-optimized) |
| Molecular Dynamics | GROMACS, LAMMPS simulations | hpc6a (high core count) |
| Weather Modeling | WRF, climate simulations | hpc6a, c6i (CPU + memory) |
| Fire Dynamics | FDS fire modeling | c6i (multi-core) |
| Machine Learning | Distributed training | GPU instances (p4d, g5) |
How It Works
- Configure — Write a YAML config file describing your cluster (or use a template)
- Create — ParallelCluster provisions head node, storage, and networking
- Connect — Access the head node via DCV remote desktop or SSH
- Install Software — Use Spack or manual installation on shared storage
- Submit Jobs — Use Slurm to submit jobs; compute nodes scale up automatically
- Monitor — Track job status, node utilization, and costs
- Clean Up — Delete the cluster when done; pay nothing when idle
Ready to get started? Next up: Getting Access