What hardware configuration is characterized by powerful multi-GPU, multi-node setups for distributed computing?

The DGX SuperPOD is recognized as a powerful hardware configuration designed specifically for high-performance distributed computing, particularly in the context of artificial intelligence and deep learning tasks. It integrates multiple GPUs across various nodes, enabling efficient parallel processing and enhancing computational capabilities significantly. This architecture allows for the handling of large datasets and the execution of complex models with speed and scalability that would not be possible with single-node or simpler multi-GPU configurations.

In contrast, the other options relate to different aspects of hardware and computing. CUDA cores refer specifically to the parallel processors within NVIDIA GPUs, which enable acceleration of compute-intensive tasks but do not specify a configuration format. A TPU Cluster denotes a setup using Google's Tensor Processing Units optimized for machine learning but lacks the extensive multi-GPU support and configuration found in a DGX SuperPOD. A Data Center Configure is a more general term and does not specifically denote a powerful multi-GPU, multi-node setup tailored for advanced distributed computing tasks as the DGX SuperPOD does. Thus, the DGX SuperPOD is the most accurate choice for the description of powerful multi-GPU, multi-node setups.