Optimizing Storage for AI Workloads with Solidigm
Event: AI Data Infrastructure Field Day 1
Appearance: Solidigm Presents at AI Data Infrastructure Field Day 1
Company: Solidigm
Video Links:
- Vimeo: Optimizing Storage for AI Workloads with Solidigm
- YouTube: Optimizing Storage for AI Workloads with Solidigm
Personnel: Ace Stryker
In this presentation, Ace Stryker from Solidigm discusses the company’s unique value proposition in the AI data infrastructure market, focusing on their high-density QLC SSDs and the recently announced Gen 5 TLC SSDs. He emphasizes the importance of selecting the right storage architecture for different phases of the AI pipeline, from data ingestion to archiving. Solidigm’s QLC SSDs, with their high density and power efficiency, are recommended for the beginning and end of the pipeline, where large volumes of unstructured data are handled. For the middle stages, where performance is critical, Solidigm offers the D7 PS1010 Gen 5 TLC SSD, which boasts impressive sequential and random read performance, making it ideal for keeping GPUs maximally utilized.
The presentation highlights the flexibility of Solidigm’s product portfolio, which allows customers to optimize for various goals, whether it’s power efficiency, GPU utilization, or overall performance. The Gen 5 TLC SSD, the D7 PS1010, is positioned as the performance leader, capable of delivering 14.5 gigabytes per second sequential read speeds. Additionally, Solidigm offers other options like the 5520 and 5430 drives, catering to different performance and endurance needs. The discussion also touches on the efficiency of these drives, with Solidigm’s products outperforming competitors in various AI workloads, as demonstrated by the ML Commons ML Perf Storage Benchmark results.
A notable case study presented is the collaboration with the Zoological Society of London to conserve urban hedgehogs. Solidigm’s high-density QLC SSDs are used in an edge data center at the zoo, enabling efficient processing and analysis of millions of images captured by motion-activated cameras. This setup allows the organization to assess hedgehog populations and make informed conservation decisions. The presentation concludes by emphasizing the importance of efficient data infrastructure in AI applications and Solidigm’s commitment to delivering high-density, power-efficient storage solutions that meet the evolving needs of AI workloads.