For research labs
Grant-funded GPUs, run like a national lab.
Capital grants buy hardware, not cloud hours. Buy the servers, host them at Yotta, and let every group in the department use them without a student babysitting the rack.
Sound familiar?
What we hear, and what we do.
- Grants fund equipment
- GPU servers are a capital purchase with a clear asset record.
- The department server room can’t take 10 kW
- Servers run at Yotta with the power and cooling they need.
- Many groups, one budget
- One shared cluster, with access set up per group.
- Students graduate; servers stay
- We run the infrastructure year after year, whoever is in the lab.
Recommended hardware
Where teams like yours start.
H200
Hopper · SXM
- Memory
- 141 GB HBM3e per GPU
- Power
- Up to ~10.2 kW per server
B200
Blackwell · SXM
- Memory
- 180 GB HBM3e per GPU
- Power
- Up to ~14.3 kW per server
L40S
Ada Lovelace · PCIe
- Memory
- 48 GB GDDR6 per GPU
- Power
- 2.8 kW of GPU power for 8 cards, plus CPUs and fans
How it works for you
Uptime that doesn’t depend on a PhD student.
Monitoring, remote hands and one escalation path, so a failed drive at 2 a.m. isn’t a research group’s problem.
Questions
Can a university buy GPU servers and host them off campus?
Yes. We supply the servers against your purchase process and host them at Yotta, with access for your users.
How do multiple research groups share one GPU cluster?
With a scheduler such as Slurm and per-group accounts. We host the hardware; your IT or a partner runs the scheduler.
Which GPUs suit research?
H200 or B200 for training large models; L40S for teaching labs, vision and smaller models.
