Deployment

NVIDIA AI Infrastructure and Operations · 4 questions

• Your enterprise is building out a brand-new data center dedicated to training massive deep learning models from scratch. You need to procure the right mix of high-performance NVIDIA hardware and software tools optimized specifically for this heavy-duty training workload. Which combination should you select?
• Your enterprise is deploying a high-performance AI infrastructure to accelerate machine learning workloads across a distributed environment containing multiple NVIDIA GPUs. To optimize parallel computation on the GPU cores and streamline high-speed communication between the GPUs, which two tools or frameworks must be integrated into the system? (Choose two)
• When designing an enterprise AI development and deployment environment, you must build on top of NVIDIA's core software stack. Which two software components are essential for compiling GPU-accelerated code and optimizing deep learning models for high-performance inference? (Select two)
• To build a complete end-to-end AI workflow, you need to accelerate both the heavy training phase and the subsequent production serving phase. Which two components of the NVIDIA software ecosystem should you integrate to speed up deep neural network training calculations and optimize the final model for low-latency inference? (Choose two)