Deep learning is a powerful tool that identifies patterns, extracts meaning from large, diverse datasets, and solves complex problems. However, integrating neural networks into existing compute environments is a challenge that often requires specialized and costly infrastructure. New software and hardware options will simplify the complexity. Intel Omni-Path Architecture (Intel OPA) is well suited to the demands of deep learning, enabling near-linear scalability across large numbers of nodes to provide fast time to results for large problems (see Figure 1). A key focus of deep learning implementations is to reduce the time to train the model and to ensure a high level of accuracy.