Why can't a GPU server reach full compute utilization?

Five common causes: data-loading bottleneck (CPU can't feed the GPUs), multi-GPU communication bottleneck (misconfigured InfiniBand), insufficient VRAM causing frequent paging, batch size too small, and low parallel efficiency of the model itself. ZhongLianDa offers a free GPU utilization diagnosis — we collect runtime data with NVIDIA DCGM, locate the bottleneck and deliver an optimization plan. We also help tune cluster scheduler parameters and data pipelines, typically raising GPU utilization from 30–50% to above 80%.