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The VoltGrid preprint examines rapid power transients caused by Bulk Synchronous Parallelism in distributed deep-learning clusters. When large numbers of accelerators finish matrix multiplication together and enter collective communication barriers such as NCCL AllReduce, cluster current can collapse in under 15 microseconds. The authors connect this steep dI/dt to inductive voltage drops across power-delivery components, including substation transformers and server voltage-regulator modules, potentially triggering protective circuit breakers and limiting usable data-center power. VoltGrid is presented as a zero-overhead C++/CUDA interposition engine, distributed as libnccl-voltflow.so, that introduces deterministic microsecond-scale cascading among ranks without changing application code or container environments. On a physical cluster with four NVIDIA GeForce RTX 4090 GPUs and a sustained 1,677.7-watt load, the system reportedly reduced instantaneous sub-millisecond dI/dt power-step shock by 97.52%. The reported result preserved 100% of compute throughput and added less than 0.05% step latency impact. The associated software is documented at voltgrid.org.