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NEW QUESTION # 170
You are evaluating the integration of NVIDIA BlueField DPUs into your data center's storage architecture to optimize AI workloads. The storage solution chosen has incorporated BlueField DPUs to enhance performance and efficiency. Which of the following benefits directly results from this integration?
Answer: D
Explanation:
NVIDIA BlueField Data Processing Units (DPUs) are designed to offload, accelerate, and isolate infrastructure tasks that traditionally consume significant host CPU cycles. In modern AI storage architectures, tasks such as NVMe-over-Fabrics (NVMe-oF) target emulation, hardware-accelerated encryption, and data compression are extremely CPU-intensive. By integrating BlueField DPUs into the storage fabric, these "Infrastructure" tasks are handled by the DPU's dedicated ARM cores and hardware acceleration engines. Thisreduces the load on the host CPU, freeing up those cores to focus entirely on application logic and feeding the GPUs. While DPUs do enhance I/O performance and reduce latency (Options B and D), those are indirect benefits of the fundamental architectural shift ofoffloading. The direct, primary benefit cited in NVIDIA's DOCA and BlueField documentation is the reclamation of host CPU resources, effectively turning a standard server into a more efficient "AI-ready" node.
NEW QUESTION # 171
A system administrator needs to validate a GPU-based server and ensure that no errors occur under load. What command should be used?
Answer: C
Explanation:
nvsm stress-test is used to place the DGX/GPU-based server under load and validate that the system remains stable without reporting hardware or GPU errors during the test.
NEW QUESTION # 172
After upgrading to HPL-AI 2.0 on a DGX A100 cluster, a 2x performance gain is observed. Which optimization is primarily responsible for this improvement?
Answer: B
Explanation:
HPL-AI 2.0 improves performance mainly by using MPI-aware GPU communication that allows data movement to occur more efficiently between GPUs. This reduces CPU involvement, lowers communication overhead, and keeps GPUs active instead of waiting on host-side communication bottlenecks.
NEW QUESTION # 173
During server maintenance, a system administrator wants to ensure that the NVIDIA DGX server has sufficient disk space for operational activities. The administrator is scripting an alert system that will notify the team if disk space falls below a threshold. Which command could be included in the maintenance script to check the available disk space on the server?
Answer: A
Explanation:
The correct command is df -h | grep ' /var ' because df reports filesystem capacity, used space, available space, and mount utilization. In DGX systems, monitoring disk space is important because system logs, container runtime data, package caches, telemetry, temporary files, and service data can consume space under operational filesystems such as /var. If /var fills up, services such as Docker, containerd, logging, monitoring agents, NVIDIA management tools, or package management can fail or behave unpredictably. nvidia-smi -- query-disk-space is incorrect because nvidia-smi reports GPU telemetry, not filesystem capacity. du -sh /home
/* summarizes directory usage under /home, but it does not directly show remaining filesystem space or a threshold-ready view of the mounted filesystem. lsof +L1 is useful for finding deleted files still held open by processes, but it is not the primary command for checking available disk capacity. In NVIDIA AI infrastructure, routine OS-level checks like filesystem capacity are part of reliable server operations and help prevent avoidable workload failures.
NEW QUESTION # 174
You are evaluating the integration of NVIDIA BlueField DPUs into your data center's storage architecture to optimize AI workloads. The storage solution chosen has incorporated BlueField DPUs to enhance performance and efficiency. Which of the following benefits directly results from this integration?
Answer: D
Explanation:
NVIDIA BlueField DPUs improve storage architecture efficiency by offloading infrastructure and data-processing tasks from the host CPU. This frees CPU resources for AI workloads while the DPU handles storage, networking, and security-related processing more efficiently.
NEW QUESTION # 175
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