GPU Infrastructure
Validation you can only do with real hardware.
Graph learning at scale is expensive to get right. We run on H200 and B300-class GPUs so experiments finish in hours, not weeks.
GPU class
NVIDIA H200 / B300
Workload
Graph & sequence learning
Comparison
7 baselines + 3 hybrids
Output
Top-K predictions
What it enables
More hardware means more honest science.
Graph learning
Train large GNNs on real user–item graphs without sampling away the signal.
Honest benchmarks
Room to run every baseline properly, not just the one that flatters the result.
Fast iteration
Short training cycles mean more experiments and tighter feedback loops.
Production paths
Research that's built to survive the trip from notebook to service.
Start a project
Need serious compute behind your models?
If your validation is bottlenecked on hardware, let's talk about what H200 / B300-class infrastructure unlocks.