NCA-AIIO Question 117
Select 3When virtualizing an accelerated infrastructure for AI workloads, which key considerations should be taken into account to ensure optimal performance and resource utilization?
- A
Ensuring GPU passthrough or vGPU support for virtual machines
- B
Using exclusively CPU-based virtualization layers to reduce complexity
- C
Configuring adequate GPU memory allocation for virtual machines
- D
Implementing NUMA (Non-Uniform Memory Access) awareness for resource alignment
- E
Avoiding virtualization of GPUs due to potential performance overhead
Show answer and explanation
Correct answers: A, C, D
Explanation
Virtualizing accelerated infrastructure for AI workloads requires ensuring that GPUs are properly utilized in the virtual environment. This involves enabling GPU passthrough or vGPU support, allocating sufficient GPU memory, and maintaining NUMA awareness to avoid resource misalignment. These considerations are crucial for delivering optimal performance without sacrificing the benefits of virtualization.
- A. Correct.
Ensuring GPU passthrough or vGPU support is critical for virtual machines requiring high-performance GPU acceleration. Without this, the VMs cannot fully utilize the GPU resources, impacting AI workload performance.
- B. Incorrect.
Exclusively using CPU-based virtualization layers reduces complexity but does not address the needs of accelerated AI workloads, which rely heavily on GPUs for performance.
- C. Correct.
Configuring adequate GPU memory allocation ensures that each virtual machine has enough memory to handle its workload, preventing memory bottlenecks and crashes.
- D. Correct.
NUMA awareness is important in virtualized environments to ensure that memory and compute resources are properly aligned to avoid latency and performance degradation.
- E. Incorrect.
Avoiding virtualization of GPUs entirely is not a recommended approach, as modern virtualization technologies provide efficient GPU sharing mechanisms, such as NVIDIA vGPU, to handle AI and ML workloads.