Storage optimization: Practice Questions — Troubleshoot and Optimize (NVIDIA-Certified Professional: AI Infrastructure)
Storage Optimization Practice Questions for NVIDIA-Certified Professional: AI Infrastructure These practice questions focus specifically on storage...
Storage Optimization Practice Questions for NVIDIA-Certified Professional: AI Infrastructure
These practice questions focus specifically on storage optimization within advanced NVIDIA AI infrastructure environments, a key component of the Troubleshoot and Optimize domain of the certification exam.
Which of the following is the most effective method to improve storage I/O performance in an AI infrastructure server?
- A. Increase the number of CPU cores
- B. Use RAID 0 configuration with SSDs
- C. Upgrade to a higher capacity HDD
- D. Disable write caching
Correct Answer: B
Explanation: RAID 0 stripes data across multiple SSDs, significantly increasing I/O throughput and reducing latency, which is critical for AI workloads. Increasing CPU cores does not directly improve storage I/O, HDDs have slower speeds than SSDs, and disabling write caching reduces performance.
What is the primary benefit of implementing NVMe over Fabrics (NVMe-oF) in an AI infrastructure storage system?
- A. Reduces network bandwidth usage
- B. Enables remote access to high-speed NVMe storage with low latency
- C. Increases storage capacity without hardware changes
- D. Simplifies RAID configuration
Correct Answer: B
Explanation: NVMe-oF allows remote access to NVMe storage devices over a network with minimal latency, maintaining high throughput essential for AI data processing. It does not inherently reduce bandwidth usage or increase capacity without hardware, nor does it simplify RAID setup.
Which storage optimization technique helps reduce latency when accessing frequently used AI datasets?
- A. Data deduplication
- B. Tiered storage with SSD caching
- C. Increasing RAID parity levels
- D. Using larger block sizes for all files
Correct Answer: B
Explanation: Tiered storage with SSD caching places frequently accessed data on faster SSDs, reducing latency. Data deduplication saves space but does not directly reduce latency. Higher RAID parity levels can increase overhead, and larger block sizes may not be optimal for all file types.
During storage optimization, which metric is most indicative of a bottleneck caused by slow disk write speeds?
- A. High CPU utilization
- B. Increased disk queue length
- C. Low network throughput
- D. High memory usage
Correct Answer: B
Explanation: A high disk queue length indicates that write requests are waiting longer to be processed, signaling slow disk write speeds. CPU utilization, network throughput, and memory usage may be affected but are not direct indicators of disk write bottlenecks.
Which of the following is a recommended practice to optimize storage performance for AI model training data?
- A. Store all data on a single large HDD
- B. Use parallel file systems like Lustre or GPFS
- C. Disable RAID to reduce overhead
- D. Use only cloud storage without local caching
Correct Answer: B
Explanation: Parallel file systems distribute data across multiple storage nodes, enabling high throughput and scalability needed for AI training. Single HDDs are slow, disabling RAID removes redundancy and performance benefits, and relying solely on cloud storage without caching can increase latency.
What is the effect of enabling write-back caching on SSDs in an AI infrastructure?
- A. It decreases write performance but increases data safety
- B. It improves write performance but risks data loss on power failure
- C. It disables read caching
- D. It increases storage capacity
Correct Answer: B
Explanation: Write-back caching temporarily stores write operations in cache to improve performance but can risk data loss if power is lost before data is written to disk. It does not disable read caching or increase capacity.
Which tool would be most appropriate to monitor real-time storage performance metrics in an NVIDIA AI infrastructure?
- A. nvidia-smi
- B. iostat
- C. top
- D. ping
Correct Answer: B
Explanation: iostat provides detailed real-time statistics on storage device I/O, helping identify performance bottlenecks. nvidia-smi monitors GPU status, top monitors CPU and process usage, and ping tests network connectivity.
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