# How Adobe Reduced GPU Idle Time in Generative AI Training Through Faster Data Access and Checkpointing

DevFeed: [How Adobe Reduced GPU Idle Time in Generative AI Training Through Faster Data Access and Checkpointing](<https://devfeed.tech/articles/why-your-gpu-is-sitting-idle-the-data-pipeline-problem-no-one-talks-about-12325.md>)

Original publisher: [Read original article](<https://www.backblaze.com/blog/why-your-gpu-is-sitting-idle-the-data-pipeline-problem-no-one-talks-about/>)

Author: Maddie Presland

Published: 2026-08-25T15:22:30Z

Content type: article

Language: en

Sources: [Backblaze Blog | Cloud Storage & Cloud Backup](<https://devfeed.tech/sources/backblaze-blog-cloud-storage-cloud-backup.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Training AI Models](<https://devfeed.tech/topics/training-ai-models.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [networking](<https://devfeed.tech/topics/networking.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [ai-ml](<https://devfeed.tech/tags/ai-ml.md>), [ai-training](<https://devfeed.tech/tags/ai-training.md>), [b2cloud](<https://devfeed.tech/tags/b2cloud.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cloud-storage](<https://devfeed.tech/tags/cloud-storage.md>), [compute](<https://devfeed.tech/tags/compute.md>), [ethernet](<https://devfeed.tech/tags/ethernet.md>), [featured](<https://devfeed.tech/tags/featured.md>), [featured-cloud-storage](<https://devfeed.tech/tags/featured-cloud-storage.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [model-training](<https://devfeed.tech/tags/model-training.md>), [networking](<https://devfeed.tech/tags/networking.md>)

## AI overview

Adobe's generative AI training pipeline left roughly two-thirds of GPU time waiting for data. The article attributes the waste to storage and retrieval bottlenecks, networking limits, and checkpointing overhead, and describes Adobe's use of a high-performance networking fabric and fragmented checkpoint storage to reduce delays.

## Source excerpt

Adobe's experience reveals why GPUs sit idle during AI model training: slow storage, insufficient throughput, and uneven workloads. Learn how storage bottlenecks and uneven data loading leave expensive GPUs idle--and how always-hot, high-throughput object storage keeps AI training pipelines running efficiently at scale while reducing wasted compute costs. The post Why Your GPU Is Sitting Idle: The Data Pipeline Problem No One Talks About appeared first on Backblaze Blog | Cloud Storage & Cloud Backup