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NVIDIA AI Infrastructure Sample Questions (Q35-Q40):

NEW QUESTION # 35
You are tasked with designing a high-performance network for a large-scale recommendation system. The system requires low latency and high throughput for both training and inference. Which interconnect technology is MOST suitable for connecting the nodes within the cluster?

A. Fibre Channel
B. 100 Gigabit Ethernet
C. InfiniBand
D. Gigabit Ethernet
E. 10 Gigabit Ethernet

Answer: C

Explanation:
InfiniBand is designed for high-performance computing and offers significantly lower latency and higher bandwidth compared to Ethernet or Fibre Channel, making it the most suitable choice for demanding workloads like recommendation systems. While 100 Gigabit Ethernet provides high bandwidth, InfiniBand generally offers lower latency.

NEW QUESTION # 36
You are deploying a multi-tenant AI infrastructure where different users or groups have isolated network environments using VXLAN. Which of the following is the MOST important consideration when configuring the VTEPs (VXLAN Tunnel Endpoints) on the hosts to ensure proper network isolation and performance?

A. Ensuring that each tenant has a unique VXLAN Network Identifier (VNI) to isolate their traffic.
B. Using the same IP address for all VTEPs to simplify routing.
C. Using the same VNI for all tenants to maximize network utilization.
D. Disabling multicast routing to prevent broadcast traffic.
E. Using the default MTU size of 1500 bytes for VXLAN traffic.

Answer: A

Explanation:
The most critical aspect of VXLAN configuration for multi-tenancy is ensuring that each tenant has a unique VNI. The VNI is a 24-bit identifier that segments the VXLAN network into isolated logical networks. Using unique VNIs guarantees that traffic from one tenant remains isolated from other tenants, preventing data leakage and ensuring security. Using overlapping or shared VNIs would defeat the purpose of VXLAN- based isolation.

NEW QUESTION # 37
You are installing the NGC CLI using 'pip' behind a corporate proxy. The installation fails due to connection errors. How do you configure pip' to use the proxy during the NGC CLI installation?

A. Download the NGC CLI package manually and install it offline.
B. NGC CLI does not support the use of proxies
C. Use the '-proxy option with the 'pip install' command, specifying the proxy server address and port.
D. Set the 'http_proxy' and 'https_proxy' environment variables with the proxy server address and port.
E. Create a 'pip.conf file in the appropriate directory (e.g., '-/.pip/pip.conf) and configure the proxy settings within the file.

Answer: C,D,E

Explanation:
You can configure 'pip' to use a proxy by setting environment variables (A), using the '-proxy' option with the 'pip install' command (B), or creating a 'pip.conf file (C). Downloading the package manually (D) is a workaround for the initial installation but doesn't address ongoing communication with NGC. Option E is incorrect since NGC CLI does support proxy configuration.

NEW QUESTION # 38
A user reports that their GPU-accelerated application is crashing with a CUDA error related to 'out of memory'. You have confirmed that the GPU has sufficient physical memory What are the likely causes and troubleshooting steps?

A. The application is requesting a larger block of memory than is available in a single allocation. Try breaking the allocation into smaller chunks or using managed memory.
B. The CUDA driver version is incompatible with the CUDA runtime version used by the application. Update the CUDA driver to match the runtime version.
C. The application is leaking GPU memory. Use a memory profiling tool like 'cuda-memcheck' to identify the source of the leak.
D. The system's virtual memory is exhausted. Increase the swap space.
E. The process has exceeded the maximum number of GPU contexts allowed. Reduce the number of concurrent CUDA applications running on the GPU.

Answer: A,C

Explanation:
Memory leaks and single-allocation limits are common causes of 'out of memory' errors, even when sufficient physical memory exists. 'cuda-memcheck' is specifically designed to find memory errors in CUDA applications. While driver incompatibility is possible, leaks and allocation size limits are more frequent occurrences.

NEW QUESTION # 39
You are tasked with replacing a redundant power supply unit (PSU) in a GPU server. The server has two 2000W PSUs. One PSU has failed, but the server is still running. Which of the following actions is the safest and most efficient way to replace the faulty PSU?

A. Hot-swap the faulty PSU with a new one while the server is running.
B. Wait for a scheduled maintenance window to power down the server and replace the PSU.
C. Replace the faulty PSU, then reboot the server to ensure the new PSU is working.
D. Immediately power down the server and replace the faulty PSIJ.
E. Document the failure and wait until the remaining PSU fails before taking action.

Answer: A

Explanation:
Hot-swapping is the designed method for replacing redundant PSUs in many server systems. This allows the server to remain operational while the faulty PSU is replaced, minimizing downtime. Powering down the server immediately is unnecessary and causes downtime. Waiting for a maintenance window or until the remaining PSU fails increases the risk of a complete server outage.

NEW QUESTION # 40
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