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MaterHaven Dedicated APU Compute
We compute on our own APUs while others crowd onto general-purpose GPUs — 300%–800% faster on NEB and AIMD bottlenecks.
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Efficiency gain
300%–800% faster on NEB/AIMD workloads
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Exclusive scheduling
Never shared, never queued
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SCF convergence rate
Success rate > 98%
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Written into the contract
Delivery timelines become part of the SLA
GPU cluster vs MaterHaven APU
Performance Comparison
| Computing scenario | General-purpose GPU cluster | MaterHaven APU |
|---|---|---|
| NEB Transition-State Search | ~14 days | 3 days (-79%) |
| AIMD Molecular Dynamics | ~30 days | 7 days (-77%) |
| SCF convergence success rate | Unstable, needs constant tuning | > 98% |
| Queueing | Shared queue, billed by core-hour | Exclusive scheduling, SLA-backed |