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NVIDIA AI Infrastructure Sample Questions (Q113-Q118):
NEW QUESTION # 113
A data scientist reports that training performance on a DGX A100 server has significantly degraded over the past week. 'nvidia-smi' shows all GPUs functioning, but 'nvprof' reveals substantially increased 'cudaMemcpy' times. What is the MOST likely bottleneck?
Answer: B
Explanation:
Increased ScudaMemcpy' times indicate a bottleneck in data transfer between the CPU and GPIJs or within the GPU memory itself. While PCle saturation or failing NVLink connections could contribute, a heavily loaded CPU is often the primary culprit. CPU-bound preprocessing tasks or general system load can create contention for system memory, slowing down data movement to the GPUs. The NVLink being used is less likely because 'nvidia-smi' would likely report errors or lower speeds between the GPUs
NEW QUESTION # 114
You're deploying a BlueField-2 DPU in a cloud environment and need to ensure the integrity of the DPU's firmware. You want to verify that the firmware hasn't been tampered with. Which of the following methods provides the strongest level of assurance for firmware integrity?
Answer: E
Explanation:
Digitally signed firmware provides the strongest guarantee of integrity. The signature verifies that the firmware hasn't been tampered with since it was signed by NVIDIA. SHA256 checksums are good, but digital signatures are cryptographically stronger. MD5 checksums are considered weak and easily compromised. Firmware version and file size offer minimal assurance against sophisticated attacks.
NEW QUESTION # 115
You have a dataset with many small files (e.g., images). Directly reading these files can result in high metadata access overhead. What are the MOST effective strategies to mitigate this problem?
Answer: B,C,E
Explanation:
Combining small files reduces the number of metadata operations. A key-value store can provide efficient access to small data items. Increasing metadata servers reduces the load on individual metadata servers. Smaller block sizes exacerbate the problem. Replicating data doesn't address metadata overhead.
NEW QUESTION # 116
A customer reports that after installing an additional NVIDIA GPU into their existing AI server, they are experiencing IOMMU related errors during VM startup that leverage GPU pass-through. The error message indicates a problem with address translation. Which troubleshooting steps should be taken? (Select TWO)
Answer: A,C
Explanation:
IOMMU errors often stem from incorrect configuration or outdated firmware. Disabling IOMMU is generally not recommended as it reduces security. Ensuring IOMMIJ is enabled in the BIOS/UEFI and kernel command line is crucial. Updating the BIOS/IJEFI addresses potential bugs in IOMMU implementation. While memory allocation could be a factor, it is not the most likely immediate cause. Reinstalling drivers within the VM is less likely to resolve IOMMU-related errors.
NEW QUESTION # 117
You are tasked with validating the NVLink performance between GPUs in an NVIDIA DGXAI 00 system. Which tool is the most appropriate for measuring the bandwidth and latency of NVLink interconnections under a synthetic workload?
Answer: B
Explanation:
NCCL tests, specifically , are designed for benchmarking the communication performance between GPUs using NVLink. 'nvidia-smr provides GPU monitoring information but not detailed bandwidth/latency tests. 'iostat' is for 1/0 statistics. 'memtest86'' tests system memory. 'dmesg' displays kernel messages.
NEW QUESTION # 118
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