AI inference is rapidly growing, and QLC NAND Flash has become the new favorite in enterprise storage solutions.
Compared to traditional TLC NAND, QLC offers higher storage density and lower costs, making it suitable for AI inference workloads that are primarily read-intensive.
Research institutions predict that by 2025, QLC NAND production capacity will reach 2,504.8 billion Gb, accounting for 22.2% of total NAND production, with its penetration rate gradually increasing.
AI inference servers are primarily responsible for analyzing and processing large amounts of data, and their access patterns are predominantly read-oriented with relatively low write frequency, perfectly aligning with the characteristics of QLC SSDs.
With higher storage density and lower per-unit costs than TLC NAND, QLC NAND has become an ideal choice for AI servers, cloud computing, and big data analytics applications.
As the number of hyperscale data centers grows, the adoption rate of QLC SSDs in AI server environments continues to rise.
Industry experts point out that while QLC NAND offers high density and low costs, its durability and write lifespan are lower than those of TLC NAND, which has historically limited its acceptance in the enterprise market.
However, with advancements in NAND Flash manufacturing processes and SSD controller technology, QLC SSDs have improved in both performance and lifespan.
In the data center sector, HDDs have long been the primary storage devices. However, QLC SSDs offer faster access speeds and lower power consumption, and as NAND Flash costs per Gb continue to decline, the price gap between QLC SSDs and HDDs is narrowing.
Enterprise-grade QLC SSDs have now reached capacities of up to 128TB, offering higher performance and density than HDDs, and are expected to gradually replace HDDs in the field of big data storage.
Related:
Disclaimer:
- This channel does not make any representations or warranties regarding the availability, accuracy, timeliness, effectiveness, or completeness of any information posted. It hereby disclaims any liability or consequences arising from the use of the information.
- This channel is non-commercial and non-profit. The re-posted content does not signify endorsement of its views or responsibility for its authenticity. It does not intend to constitute any other guidance. This channel is not liable for any inaccuracies or errors in the re-posted or published information, directly or indirectly.
- Some data, materials, text, images, etc., used in this channel are sourced from the internet, and all reposts are duly credited to their sources. If you discover any work that infringes on your intellectual property rights or personal legal interests, please contact us, and we will promptly modify or remove it.