Resource-aware Computation-Communication Overlap for multi-GPU ML Workloads 事件

Resource-aware Computation-Communication Overlap for multi-GPU ML Workloads arXiv:2606.09200v1 Announce Type: cross Abstract: The rapid growth of large-scale machine learning (ML) has made distributed training across multiple GPUs a fundamental component of modern ML systems. As model sizes and computational throughput continue to increase, communication overhead has become a dominant bottleneck in multi-GPU training, particularly when computation and communication are executed sequentially. Th