Big, fast, and efficient storage makes the foundation for powerful and adaptable AI systems. It allows you to train on massive datasets, optimize resource allocation to expensive GPU clusters, and prepare for the future demands of AI.
Why Is Big, Fast and Efficient Important?
AI models learn and improve through a process called training. It is just one step in the typical AI workflow. Training involves ingesting and processing massive datasets such as text, images, videos, or other formats relevant to the task.
Big storage capacity ensures that there is enough space to house the burgeoning datasets that are utilized in the AI workflow. With traditional hard disk drives (HDDs) topping out around 30TB, NAND storage devices have emerged as the preferred choice. They are over double in size, and have a significantly smaller physical footprint, making a sizeable difference in how storage systems are scaled within the datacentre.
Performance is key in AI. The faster a storage can access and deliver data, the quicker the AI models can train and make predictions. This efficiency is crucial for real-time applications, such as fraud detection, where time-sensitive decisions need to be made. It is equally important during the training phase where large checkpoint files are stored and retrieved from the disk. Slow data access can cost serious money in this cycle due to lost training time. Technologies like NAND storage have significantly faster data retrieval speeds compared to HDDs.
Efficiency is twofold, as it relates to energy-friendly operations, as well as efficient use of space. HDDs rely on spinning platters and magnetic recording heads. The physical size of these components limits how much data they can store in a given space, and the amount of energy they consume. NAND flash storage don’t have spinning platters which translates to lower power consumption and higher energy-efficiency.
NAND flash memory utilizes flash memory chips that are incredibly small, and allows for a much higher density of data storage per unit volume compared to HDDs. This poses a significant advantage for large AI deployments that require constant data access.
Solidigm, a Leader in NAND Solutions
A relatively young company, Solidigm was established in December 2021. With roots running deep in the world of memory and storage, it emerged from a strategic partnership between two industry giants – Intel and SK Hynix. Intel’s NAND and SSD business division brought decades of experience in developing innovative flash memory and solid-state drive technologies to which, SK Hynix, a leading South Korean semiconductor manufacturer, added global reach and tremendous manufacturing prowess.
This fusion created a powerhouse in the data storage landscape. Today, Solidigm is a key player in the evolving data storage landscape, and is extremely well-positioned to develop advanced storage solutions. Already the portfolio boasts a large number of market-leading products and solutions. Supermicro, a leading name in high-performance servers, is a top adopter of its SSDs.
Solidigm’s QLC Portfolio for AI Work
The Solidigm QLC SSD portfolio is designed to meet the demands of capacity and performance needs of AI workloads, all whilst providing crucial performance in workflows like checkpointing and data ingestion and processing.
In particular, the D5-P5336 is a preferred solution for AI tasks. Available in capacities of up to 61.44TB per drive, it comes in a slim E1.L 9.5mm form factor. To give you a sense of the density that can be achieved in this form factor, a 2U configuration can accommodate a whopping 64 disks. That translates to around 3.93PB of raw capacity. There is no getting near to this amount of capacity in such a small footprint when using HDDs. The ruler saves significant money in expensive data centre real estate and related costs like network ports.
The small footprint, however, does not impact performance at all. The D5-P5336 QLC SSD boasts some serious performance numbers to keep those AI workflows running optimally. It offers up to 7,000 MB/s sequential read and 3,000 MB/s write bandwidth. This translates to better user experience and cost-savings which traditional HDDs can’t compete with.
Wrapping up
The exponential growth of AI workloads demands robust storage solutions that are capable of handling massive datasets, and delivering lightning-fast performance. This demand for infrastructure efficiency will push QLCs to the forefront. Solidigm expects QLCs to account for 30% of the drives shipped in 2024.
As AI applications become more complex, and real-time decision-making becomes prevalent, high-density, high-performance storage like Solidigm’s QLC SSD line will take the center stage. By adopting Solidigm’s advanced storage solutions, businesses can gain competitive advantage and significant cost-savings in the AI race.
Faster training times, bumpless real-time operations, and optimized resource allocation contribute to more powerful and adaptable AI systems, and paves the path for ground-breaking advancements in the fields of healthcare, finance, automotives, and more. Solidigm, with its innovative solutions and commitment to pushing boundaries, is well-positioned to be a leader in this exciting future.
For more, be sure to check out Solidigm’s presentations from the recent AI Field Day event.
