Solidigm Presents at AI Infrastructure Field Day 2

Getting to Know the Unsung Hero of AI Infrastructure with Solidigm

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Solidigm’s presentation at AI Infrastructure Field Day emphasized the critical role of data storage in the evolving landscape of AI solutions, using the framework of the AI data pipeline. The amount of data used for training an AI model directly correlates with its accuracy, making storage a critical infrastructure component. Ace Stryker, the Director of Market Development at Solidigm, introduced the company’s focus on storage solutions, explaining the importance of efficient data storage in all stages of the AI data pipeline, from data ingestion and preparation to model development, inference, and archiving.

The presentation shows Solidigm as a key player in AI infrastructure by providing a diverse portfolio of SSD offerings that address the growing demands for high-capacity and efficient storage. Ace explained that Solidigm, spun off from Intel’s storage and memory group, has a strong heritage in storage technology, emphasizing the importance of storage solutions in enabling more GPU scaling. Solidigm also introduced a key collaboration with NVIDIA that will enable future generations of storage solutions, specifically in liquid cooling, which allows for future storage solutions.

The presentation explored the nuances of the AI data pipeline, highlighting how storage solutions can improve model accuracy and address crucial challenges within AI infrastructure. The presentation’s core message revolves around how every watt and square inch of data center space counts, especially when tackling advanced AI applications requiring substantial data. The presentation also included a live demo from Metrum AI, illustrating data-intensive inference possibilities and discussing high-density storage solutions.

Personnel: Ace Stryker

AI Data solutions are not One Size Fits All with Solidigm

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Solidigm’s presentation focuses on AI performance and efficiency, highlighting the role of high-performance SSDs in addressing the challenges of rapidly growing AI development and optimizing the total cost of ownership. Scott Shadley, Director of Leadership Narrative and Evangelist at Solidigm, begins by framing the need for diverse storage solutions to accommodate AI’s massive data demands, using humorous AI-generated images and analogies to illustrate the concept of fitting vast data into SSDs.

The presentation underscores the dramatic increase in data generation, particularly with the rise of synthetic data, which requires a strategic approach to storage. Solidigm emphasizes that a one-size-fits-all approach is insufficient. The company’s strategy is to understand customers’ needs and design products to meet those demands. This includes the development of various SSD form factors (EDSFF, E1S, E3S, and U.2) tailored for different workloads and environments, from traditional data centers to edge computing.

Finally, the presentation concludes by previewing Ace Stryke’s upcoming deep dive into how their products align with the AI pipeline and reiterates the company’s focus on providing storage solutions rather than just drives. Solidigm prioritizes partnerships, customer collaboration, and workload-specific designs to offer storage solutions for AI. The talk pivots the focus to defining edge computing and the innovative designs within the product portfolio while promising a deeper discussion on cooling.

Personnel: Scott Shadley

Why Storage Matters to AI in 2025 with Solidigm

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Solidigm focused on the evolving role of storage in AI, specifically highlighting its significance in the AI data pipeline through 2025. The presentation emphasizes that the AI workflow involves a series of distinct tasks, each with unique demands on hardware, and that it’s often distributed among different organizations. The presentation identifies six primary stages in this pipeline: ingestion, data preparation, model training, fine-tuning, inference, and archiving. Solidigm’s perspective underscores the increasing data intensity of these steps, especially during data ingestion, inference, and archiving.

Solidigm explores how storage choices impact these stages, distinguishing between direct-attached storage within GPU servers and network-attached storage. Direct-attached storage is optimized for performance-intensive tasks, while network-attached storage is used for larger datasets and offers capacity and cost-effectiveness. Ace Stryker highlights the rising importance of network storage, driven by advances in network bandwidth and the growing size and complexity of AI models and larger datasets for RAG. The key takeaway is that great storage facilitates larger models, longer interactions, and improved outputs on the inference side.

Finally, the presentation showcases a collaboration with Metrum AI, presenting a real-world demo that addresses the challenges of data-intensive inference by offloading model weights and RAG data to SSDs. This allows running 70 billion parameter models on less powerful hardware, which would have been impossible without storage-based offloading, saving on costs and hardware requirements. The demo emphasizes the potential of SSDs to enhance performance in AI applications by reducing GPU memory usage. The collaboration offers insights into the benefits of leveraging storage in AI, as the partnership also showed that offloading to SSD could provide the same or better performance as DRAM in this application of retrieval augmented generation.

Personnel: Ace Stryker, Steen Graham

Industry First SSDs Tackle AI Challenges with Solidigm

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Solidigm’s Director of Leadership Narrative and Evangelist, Scott Shadley, introduces their new SSDs designed to tackle the challenges of AI infrastructure. Shadley begins by highlighting the industry-first status of their 122TB SSDs, emphasizing their potential to revolutionize storage solutions. He shares a case study involving Dell, who is excited to potentially introduce this product, illustrating a significant reduction in footprint and power consumption compared to traditional hybrid storage solutions using hard drives and SSDs for cache. A 9-to-1 reduction in rack space and a 90% reduction in network footprint lead to the possibility of utilizing 50% more servers within the same infrastructure.

The presentation then delves into the specifics of the 122TB SSD, emphasizing its high reliability and efficiency and its design to ensure longevity. It also reveals how the product is not just a drive but an entire ecosystem. The slide show then goes on to detail the product’s inner workings, from the stacking of the drives to the packaging and how the firmware has been adapted to work in the current state of the technology.

Finally, Shadley showcases a liquid-cooled direct-attach storage solution, designed in partnership with NVIDIA for their GB300 platform. The design uses a single-sided cold plate for cooling, allowing hot-swappable drives within a fully liquid-cooled system. This design innovation eliminates the need for fans while maintaining the flexibility and reliability expected from traditional storage. The presentation concludes with a reiteration of Solidigm’s commitment to continuous innovation and its focus on providing solutions that address the evolving needs of AI infrastructure.

Personnel: Scott Shadley