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Managing 500 Billion+ Files for AI Workloads

How do you optimize a distributed file system that manages over 500 billion files in a single volume? This talk covers critical AI scenarios: large-file sequential reads (breaking FUSE limits to reach 70+ GB/s), massive small files (scaling metadata IOPS linearly), and high-concurrency random reads (boosting from 7,000 to 20,000+ IOPS via a warm cache). Learn practical tuning strategies that perfect the last mile of AI data access. Because at P99 CONF, we know that there’s always room for optimization and GPUs should never starve.

23 minutes
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Joe Zhou, Lead Developer Advocate at Juicedata Inc.

Joe is an enthusiastic advocate for cloud-native technologies. Having served as the CTO of a dynamic start-up company, Joe excels at directing and inspiring team members to deliver exceptional results. Currently, Joe proudly serves as the Lead Developer Advocate in North America at JuiceFS, a high-performance, cloud-native, distributed file system. He dedicates his role to promoting this innovative solution and enabling AI/ML engineers, software developers, and platform teams to utilize JuiceFS capabilities for optimal performance and efficiency.

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