In the realm of automotive software development, the integration of large-scale AI models into autonomous vehicles is becoming increasingly prevalent. The models range from vision AI models to end-to-end AI models for autonomous driving. AI and scientific computing applications are great examples of distributed computing problems. The problems are too large and the computations too intensive to run on a single machine. These computations are broken down into parallel tasks that are distributed across thousands of compute engines, such as CPUs and GPUs.

• Improve performance for large-scale AI workloads by optimizing compute, storage, and network layers.
• Connect and optimize all your data—from sensor-rich vehicles to cloud-based development environments.
• Embrace AI-driven IT operations to accelerate machine learning (ML) and advanced analytics across the enterprise.