Managed cloud HPC Managed cloud HPC

MAXFlops

A large-scale compute environment for materials research, without procurement or operations overhead. We design and stand up a dedicated HPC cluster you can use the day it goes live.

  • Designed and built in the cloud — usable as soon as it stands up
  • On-demand capacity when your in-house HPC is full or backlogged
  • Tuned per solver — researchers do not have to tinker
  • Operations and monitoring included as a managed service
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Compute that keeps research moving

Cloud
Stood up in the cloud
On-demand
Scale up as needed
Managed
Operations included
Tuned
Solver-specific setup
Features

Core capabilities

From design to operation in one package — so researchers stay focused on the work, not the infrastructure.

Managed cloud HPC

A dedicated cluster designed and built in the cloud. No data center, no in-house admin team needed.

Per-solver tuning

Compiler, library, and MPI settings tuned for DFT, MD, and other workloads — faster results on the same hardware.

Burst capacity

When in-house HPC is full or queues are long, bring up extra nodes immediately so a campaign does not stall.

Job scheduler

Standard Slurm-based scheduling with priorities, quotas, and fair-share policy for team-level resource sharing.

Monitoring & operations

Live view of utilization, queue state, and job history — with incident response handled by the VirtualLab ops team.

Pay for what you run

Cloud billing means you pay for the hours you actually use, with no idle hardware on the books.

How it works

How it is delivered

We listen to your workload, design a cluster for it, and stand it up. From there, you use it — that is the whole flow.

  1. 01

    Define the workload

    Solvers you mostly run, concurrent users, data sizes, and budget — we work through these together.

  2. 02

    Design & stand up

    Instances, network, storage, and software stack are designed in the cloud, tuned for your solvers, and brought online.

  3. 03

    Run & operate

    Researchers just submit jobs. Monitoring, incident response, and scale-outs are handled by VirtualLab.

Use cases

Where teams use it

Large-scale materials campaigns

DFT/MD screening across many candidate structures and thousand-job data-generation pipelines.

AI training data generation

Computational datasets for materials ML — workloads that have to finish within a deadline.

Everyday DFT and MD

Routine calculations stuck waiting on in-house HPC, offloaded to the cloud as needed.

Short-term collaborations and projects

Spin up dedicated resources for the duration of a project, then tear down — no procurement cycle.

Compute that keeps up, infrastructure that gets out of the way

Tell us the solvers you run, the scale you need, and the timeline. We will come back with a fitting design and an expected cost.

Talk to us Get the brief