When training a neural network, what is the most common pattern of storage access?

The correct answer is B. Sequential read. Training neural networks typically involves streaming large datasets from storage in a sequential read pattern. This ordered access maximizes throughput and minimizes seek overhead, as training pipelines ingest data in batches for processing across epochs. Writes (e.g., model…

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Question

Options

ARandom write
BSequential read
CSequential write

How the community answered

(40 responses)

A
8% (3)
B
88% (35)
C
5% (2)

Explanation

Training neural networks typically involves streaming large datasets from storage in a sequential read pattern. This ordered access maximizes throughput and minimizes seek overhead, as training pipelines ingest data in batches for processing across epochs. Writes (e.g., model checkpoints) are less frequent and typically sequential, while random writes are rare, making sequential reads the dominant pattern. (Note: The document incorrectly lists C as the answer; B aligns with NVIDIA's documentation.)

Topics

#Neural Network Training#Data Loading#Storage I/O#Sequential Read

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