High-density storage design, with a storage capacity full-stack AI exceeding 600TB in a 2U space

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The KR2266V2 incorporates a significant number of Redriver chips to enhance the storage data link driving capabilities, improving the overall storage link performance and ensuring that each drive can achieve maximum performance.

The outstanding performance of the KR2266V2 full-stack AI in storage scenarios is attributed to its patented three-layer pull-out design for the drive bay. The server supports 28 3.5-inch drives, increasing storage density by 133% compared to the industry average. The design optimizes the drive tray, reshapes the 2U three-layer space architecture, introduces an innovative mortise and tenon frame structure, upgrades the die-casting component structure, and innovates the roller slide rail pull-out mechanism, which is all designed for storage performance improvement. To maintain signal integrity, the drive bay eliminates cable, adopts on-board routing, and utilizes an I/O board design. From components to the system, the KR2266V2 full-stack ensures stability and reliability in all aspects. This includes disrupting traditional vertical backplane design by adopting a flat drive backplane design, which reduces air resistance and ensures more stable drive operation. By suppressing resonance, improving fans, and implementing a vibration buffering design, it enhances drive performance by over 17%. Furthermore, the drive tray structure adopts an integrated metal casting design, meeting the product's structural reliability requirements. It has undergone an authoritative institution's Level 9 seismic resistance testing and adopts a design that ensures high-reliability service operation through derating and tuning.
In response to the essential need for data security, the KR2266V2 full-stack AI has undergone multiple optimizations in terms of the overall design, protection mechanisms, and feature settings. Through the built-in PFR protection mechanism, firmware can self-repair from malicious attacks. It supports one-click secure data erasure to prevent information leakage and provides support for TPM/TCM trusted modules, ensuring customer data and asset security. With BIOS/BMC chip-level redundancy design, it avoids flash software and hardware damage, ensuring that the entire startup or upgrade process is secure and reliable.
Comprehensive intelligent management, cloud-based monitoring, and one-click deployment
In response to the intelligent and efficient O&M requirements of hyper-scale data centers, the KR2266V2 full-stack AI has established an intelligent control platform. Through one-click Call-home, devices can be reported for repair within seconds, significantly reducing fault locating time with an intelligent diagnose accuracy rate of over 95%. It can also predict drive failures 5 to 30 days in advance and detect drive performance anomalies 5 to 10 minutes in advance. By proactively warning against potential issues, it minimizes the impact of equipment risks, ensuring service continuity. Through intelligent memory health analysis, fault prediction, and self-healing, the system's downtime rate is 69% lower than the industry average.
In addition, in pursuit of sustainable development goals to reduce carbon emissions and achieve energy efficiency, the KR2266V2 full-stack AI possesses intelligent environmental sensing capabilities. It enhances cooling efficiency by 10% through ultra-wide heatsinks and aviation-grade counter-rotating twin rotor fans. It also has efficient fan control algorithms and an industry-leading dual-sensor design for temperature and pressure, ensuring quick and precise fan response for temperature control and allowing for personalized thermal regulation.
In conclusion, the KR2266V2 full-stack AI achieves maximum storage density in a 2U space. It has made significant advances in storage density, computing power, network bandwidth, and intelligent management. It features a balanced and symmetrical system architecture that increases data capacity, throughput, and data processing capabilities. It is suitable for scenarios such as big data, content delivery networks (CDNs), and distributed storage.

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