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NEW QUESTION # 35
Refer to the output:
~ $ sudo nvsm show healthinfo
-Timestamp: Sat Dec 16 16:26:32 2017 -0800
Version: 17.12-5
Checks-BIOS Revision [5.11].........................
DGX Serial Number [YSY72800016)..................
Verify installed DIMM memory sticks........................Healthy
...[output truncated)
Verify Ethernet controllers...........................Healthy
Verify installed GPU's..............................Unhealthy
Checking output of 'lspci' for expected GPU's
Missing GPU at PCI address '07:00.0'
Verify installed InfiniBand controllers....................Healthy
Verify PCIe switches..................................Healthy
...[output truncated)
What insights can a system administrator gain regarding the DGX system's health?
Answer: C
Explanation:
The output provided is a result of theNVIDIA System Management (NVSM)tool, specifically the nvsm show healthinfo command. NVSM is an essential diagnostic framework for NVIDIA DGX systems that monitors hardware health, identifies faults, and helps ensure the system remains within its validated operational state.
In this specific diagnostic trace, the system reports that the "Verify installed GPU's" check has returned a status ofUnhealthy. To provide a root cause, NVSM cross-references the live hardware enumeration from the lspci command against the system's known "Golden Configuration" (the hardware manifest defined in the firmware). The explicit error message,"Missing GPU at PCI address '07:00.0'", indicates that the system expects a GPU module to be present at that specific PCIe bus address, but the hardware is not responding or visible to the bus.
This insight allows a system administrator to conclude that aGPU is missingfrom the logical perspective of the system. This is a critical hardware fault rather than a software or driver issue. In a DGX H100 or A100 system, this could be caused by a physical module failure, a power delivery issue to that specific segment of the GPU baseboard, or a failure in the PCIe switch fabric. Because the DGX relies on a full set of 8 GPUs for high-speed collective communications (NCCL), a single missing GPU will prevent the node from participating in large-scale training jobs, requiring physical inspection or a GPU tray replacement (RMA).
NEW QUESTION # 36
Consider this Python code snippet used for loading data for a deep learning model:
Assuming the images are stored on a remote file system accessed over NFS, and training is slow due to I/O bottlenecks, which change to the 'DataLoader' would MOST directly improve performance?
Answer: C
Explanation:
Explanation: Increasing 'num_workerS allows the DataLoader to load data in parallel, which can help to overcome the I/O bottleneck when using NFS. Setting it to the number of CPU cores on each training node often yields the best performance. Increasing 'batch_size' helps, but it has diminishing returns if I/O is the primary bottleneck. Decreasing 'num_workers' will worsen the bottleneck. Primarily improves GPU memory transfer performance, not I/O performance from NFS. Multithreading inside _getitem is more complex and can lead to contention if not implemented carefully.
NEW QUESTION # 37
An enterprise IT team has completed the physical installation of an AI factory with a Spectrum-X Ethernet network connected to all GPU servers. They now need to ensure the environment is ready for scalable AI workload deployment. What is the recommended sequence of validation steps?
Answer: C
Explanation:
After physical installation, the environment should be validated from the infrastructure layer upward. Confirming firmware and configuration first ensures supported component baselines, link and port checks verify physical connectivity, network benchmarks validate Spectrum-X fabric performance, software stack validation confirms the runtime environment, and staged AI workload tests confirm readiness for scalable production deployment.
NEW QUESTION # 38
A systems administrator needs to provide an AI workload environment for a developer. Which profile type should the Administrator choose for vGPU?
Answer: A
Explanation:
C-series vGPU profiles are intended for compute workloads such as AI, deep learning, data science, and high-performance computing. They provide a vGPU profile type optimized for GPU- accelerated workload environments rather than graphics-focused use cases.
NEW QUESTION # 39
During BCM cluster setup, an engineer must configure bonded network interfaces on DGX nodes for high availability. Which cmsh command sequence properly configures a bond0 interface with two physical NICs?
Answer: A
Explanation:
In BCM cmsh, a bonded interface is created by adding a bond interface, appending the two physical NICs as bond members, setting the bonding mode, and assigning the bond to the appropriate network. This configures bond0 with the two physical interfaces for high availability on the internal network.
NEW QUESTION # 40
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