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GPU cloud for physics, climate, and CFD
This page is a beginner guide for scientists and engineers who simulate physics, weather, or how air and water move, and who want to rent extra computers for a run. A GPU is a graphics processing unit: a chip that is very good at repeating the same math thousands of times at once. GPU cloud means you rent those chips by the hour, then shut them off when the run ends.
Who it is for: researchers, lab compute buyers, and engineers who have a solver that is slow on CPUs (ordinary computer chips) and have heard GPUs might help. You do not need to be an HPC specialist to follow this page. HPC means high-performance computing: big scientific jobs on many machines.
This page is physics, climate, and CFD. CFD is computational fluid dynamics: simulating how air or liquid flows around an object or through a space. It is not the page for gene data or molecule simulations. Those live on GPU cloud for life sciences and drug discovery. Self-driving simulation lives on GPU cloud for AV simulation.
You rent GPUs when a climate run, an airflow study, or a physics solver would take weeks on CPUs and you can turn the machines off when the campaign ends. If the same partition is busy for years, the next problem is usually electricity and a site. That is powered land.
What scientific GPUs actually do
Many scientific codes spend their time on the same kind of grid math: update a million cells, then do it again for the next time step. GPUs shine when that update is written for them and the working grid fits in the GPU's own memory (VRAM).
CUDA is NVIDIA's software layer that lets those programs use NVIDIA chips. The NVIDIA HPC SDK is a toolkit of compilers and math libraries for that path. NVIDIA PhysicsNeMo is a framework for physics-informed machine learning (teaching a model about physical laws, not only from pictures or text). NVIDIA Earth-2 is NVIDIA's climate and weather platform. OpenFOAM is a widely used CFD toolkit.
You do not have to use any of those names. You do have to confirm that the solver you actually run has a GPU build. Many famous CPU codes do not magically go faster on a rented GPU. If the code is still CPU-only, renting GPUs wastes money.
You rent GPUs when a CFD campaign is a burst
You rent GPUs when a new geometry, a design sweep, or a one-off airflow study has a stop date. Elastic capacity (machines you can add and remove) beats a lab full of idle chips.
A typical rental CFD job looks like this: confirm the solver's GPU path, copy the mesh (the 3D grid of the object) next to the GPUs, run, save results, and shut the meter off.
Ask about GPU memory. A mesh that does not fit will spill and crawl. Ask about several GPUs in one server, and about several servers, if the case is large. Ask whether the message-passing layer (software that splits one job across machines, often called MPI) can talk to the GPUs directly.
OpenFOAM is a common name in this world. Do not assume every OpenFOAM case is GPU-ready. Confirm the exact solver and build with the provider before you move a production case.
You rent GPUs when a climate or physics run is a campaign, and the solver is GPU-aware
Climate and weather models step a planet or a region through time. NVIDIA Earth-2 documents a platform for climate and weather on NVIDIA GPUs. Physics-informed models (PhysicsNeMo-class work) train or run a model that is supposed to respect physical constraints. You rent GPUs when the experiment is a campaign: a new resolution, a new ensemble (a set of related runs), a paper deadline. You do not rent as the only copy of an operational forecast that cannot slip.
Physics here means continuum solvers, wave problems, and scientific machine-learning about physical systems. The buyer question is simple: is this code written for GPUs, or are you hoping? If it has a documented CUDA path, rental can cut wall-clock (the time you wait). If the bottleneck is a slow setup step or files on another continent, GPUs will not save you. Keep working sets in the same region as the GPUs. Checkpointing (saving a snapshot so a crash does not wipe a week) matters more than the famous GPU name. Spot machines (cheaper GPUs the provider can take back) are fine if you can restart.
What to check before you rent
Name the code, the GPU build, and the CUDA toolkit version. If the provider cannot run a small test case, do not move the production case. Does the grid fit in GPU memory? Do several GPUs connect quickly inside the server? Price copies (egress is the fee for data leaving the cloud). Research datasets still have residency and export rules. Campaign-shaped calendars belong on rental. A queue that never drains is a cluster.
GPU cloud partners (placeholder)
Partner rows below are placeholders until terms are signed. No live rates. No outbound URLs. When links go live, they will use rel="sponsored".
| Best for | GPU types | Notes |
|---|---|---|
| Partner TBD - GPU-aware CFD campaigns | NVIDIA data-center GPUs | Placeholder. Confirm the solver's GPU build, memory, and MPI. rel="sponsored" when live. |
| Partner TBD - climate and weather campaign runs | Multi-GPU NVIDIA nodes | Placeholder. Storage next to GPUs and a restart story. rel="sponsored" when live. |
| Partner TBD - physics-informed model experiments | High-memory NVIDIA GPUs | Placeholder. CUDA toolkit and a meter that can hit zero. rel="sponsored" when live. |
This table is not a ranking. It will reflect partner relationships once partners exist.
GPU cloud pricing varies. Verify live rates.
There is no honest single dollar-per-hour number on this page. List prices move with GPU type, region, and whether you pay only when the machine is on. Quoted "from" rates often skip storage, data transfer, and idle reservations. See the GPU cloud pricing index for how we talk about rates. We will not invent hourly prices here. Treat every public figure as stale until you re-check the provider.
Compare hours you will actually run. A two-week ensemble is a different bill from a forecast factory that never sleeps.
When GPU rental stops working
Rental stops working when utilization is high and predictable, the hardware mix is stable, and the next constraint is megawatts and a site, not another login. A megawatt is a large unit of electrical power. You are then running a scientific cluster that happens to live on someone else's floor.
The honest alternative is powered land: a development site with a credible path to large-load electricity. Browse the U.S. data center directory, then read when GPU clusters need powered land. Hybrid is normal. Rent the campaigns. Site the partition that never turns off.
Find powered land when you need a site. Rent GPUs when you need capacity now.
Related
- GPU cloud for life sciences and drug discovery
- GPU cloud for AV simulation and perception training
- When GPU clusters need powered land
FAQ
Will renting a GPU speed up my scientific code?
Only if that code has a GPU path and the working grid fits. A CPU-only solver on a rented GPU is still a CPU-only solver, plus a higher bill. Run a small test case first.
Is this the right page for GROMACS or genomics?
No. Molecule simulation and gene pipelines live on GPU cloud for life sciences. This page is physics, climate, and CFD.
Can I run OpenFOAM on GPU cloud?
Only if the exact solver and build you use has a GPU path, and the image has the CUDA toolkit that build expects. Confirm with a test case. Do not assume the name "OpenFOAM" means GPU-ready.
Should a deadline run use spot GPUs?
Only if you can restart from a checkpoint and a kill is acceptable. Deadline campaigns usually want on-demand or dedicated nodes.
When is a dedicated cluster cheaper than renting?
When the same GPUs would be busy most hours for a planning horizon in years, not one paper. Count real hours. We do not publish dollar-per-hour rates. Use the pricing index, then re-check the provider.
What if the limiter is power and a site, not another GPU?
Then rental is the wrong product. Use the powered-land GPU guide and what powered land is.
Sources
- NVIDIA HPC SDK
- NVIDIA CUDA Toolkit
- NVIDIA PhysicsNeMo
- NVIDIA Earth-2
- OpenFOAM
- What is powered land
- U.S. data center directory
- Powered Lands data center map
Need land or power instead? See the map or contact.