NCP-AII Question 96
Select 3You are designing an AI training cluster for a deep learning workload that processes large image datasets. The cluster will use NVIDIA GPUs and requires high-speed data access to ensure optimal training performance. Which of the following storage considerations should you prioritize in your cluster design?
- A
Use a high-performance parallel file system like Lustre or GPFS to handle large-scale data processing.
- B
Ensure the storage system provides sufficient IOPS (Input/Output Operations Per Second) to handle frequent small file reads/writes.
- C
Choose a traditional HDD-based storage system to minimize costs.
- D
Implement a tiered storage strategy with SSDs for active datasets and HDDs for archival data.
- E
Ignore storage throughput considerations since GPUs are the primary bottleneck in training workloads.
Show answer and explanation
Correct answers: A, B, D
Explanation
In AI training cluster design, storage plays a critical role in ensuring data is fed to GPUs efficiently. High-performance parallel file systems and sufficient IOPS are required to handle the large-scale data processing and frequent I/O operations typical in AI workloads. Additionally, implementing a tiered storage strategy optimizes performance and cost-effectiveness. Neglecting storage throughput or relying solely on HDDs can result in severe performance bottlenecks.
- A. Correct.
High-performance parallel file systems like Lustre or GPFS are designed to handle the massive data throughput and I/O demands of AI workloads, making them ideal for such environments.
- B. Correct.
Frequent small file reads/writes are common in AI workloads, especially when dealing with datasets like images. Ensuring sufficient IOPS is critical to avoid bottlenecks during training.
- C. Incorrect.
While HDDs are cost-effective, they do not provide the performance required for high-speed data access in AI training workloads, which can lead to significant bottlenecks.
- D. Correct.
A tiered storage strategy allows active datasets to reside on high-speed SSDs for performance, while older or less frequently accessed data can be stored on cost-effective HDDs. This balances cost and performance efficiently.
- E. Incorrect.
Ignoring storage throughput considerations is incorrect because GPUs can only perform optimally if they are fed data at high speeds. Storage throughput is a critical factor in AI training performance.