# HPC as a service (HPCaaS): what it is and what it changes

What HPC as a service means in practice: the responsibility split against owning a cluster, how consumption pricing behaves, and when owning is still better.

Source: https://university.eugo.io/hpc-as-a-service

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HPC as a service (HPCaaS) is high-performance computing consumed on demand rather than owned. The computing is the same; what changes is the responsibility split, and that turns out to be most of the cost and nearly all of the delay. Buying a cluster means owning procurement, capacity planning, the scheduler, and every idle hour between jobs. HPCaaS moves all of that to the provider, changing the unit of commitment from a capital purchase to a cluster you can shut down.

## Common questions

### What is HPC as a service?

High-performance computing consumed on demand rather than owned. You request a cluster for the length of one run and stop paying when it ends, with no hardware to procure, no capacity to plan, and no shared queue to wait in.

### How is HPCaaS different from just renting cloud instances?

Renting instances gives you machines; HPCaaS gives you a working cluster. With raw instances you still choose instance types, install a toolchain, configure networking and shared storage, and keep all of it running. That is where most of the engineering time in a self-built HPC setup actually goes.

### Is HPCaaS cheaper than owning a cluster?

For variable demand, usually. For sustained flat demand, often not. Owning is a capital purchase you pay for whether or not it is busy, so it wins when you can keep a large cluster genuinely occupied year-round. On-demand wins when your load has peaks and troughs, because the troughs cost nothing.

### What is the biggest hidden cost of HPC as a service?

Clusters left running after their work finished. The meter runs on elapsed time, not on work done, so an idle cluster bills exactly like a busy one, and nothing shuts it down for you. It is reliably the largest avoidable line item on any consumption-priced platform.

### Do I need to know MPI or write batch scripts?

Not on Eugo. Classic HPC required both because you were submitting a job to a scheduler that arbitrated a shared machine pool. Requesting compute per run removes the contention that made the queue necessary, so there is no submission script. A decorator on an ordinary Python function is the whole interface.

### What workloads suit HPCaaS?

Anything that divides into independent pieces and has outgrown one machine: ML training and inference, geospatial and imagery pipelines, simulation, genomics, risk and financial modeling, and large dataframe work that no longer fits in memory.

### How quickly can I start?

Minutes. There is nothing to install locally and no procurement step. You open a session in the browser, launch a cluster, and dispatch work to it.