🖥️ PyTorch FSDP • DeepSpeed ZeRO-3 • GPU Memory Sizing • 8x H100 Clusters
Distributed Training VRAM & ZeRO Estimator
Size your GPU clusters before launching expensive cloud training runs. Model weights, gradients, optimizer states (AdamW), and activation memory sharding.
Training Configuration
GPU Cluster Size (Total GPUs) 8 GPUs
💡 ZeRO-3 Communication Tradeoff
ZeRO-3 shards all model states across GPUs, reducing per-GPU memory by 1/N, but introduces a 50% all-gather network communication overhead during forward and backward passes.
Memory Footprint per GPU
Fits on 80GB H100Weights
17.5 GB
Gradients
17.5 GB
Optimizer
14.0 GB
Total / GPU
53.0 GB
Recommended Hardware & Cluster Configuration