Targeted automation transformation of the core links of the intelligent computing center's computing power scheduling production line (computing node deployment, topology adjustment, and dynamic allocation of computing power) can compress scheduling response latency by 40% -65%, increase computing power utilization to over 85%, and directly eliminate bottleneck errors in manual operations.
1, Core automation transformation content
(1) Automated control of computing power nodes throughout their entire lifecycle
AGV+RFID automatic positioning is used for node placement/removal, replacing manual handling and registration. The deployment time for a single node has been reduced from 120min to within 15min
Node health detection is predicted through edge automatic sampling and AI algorithm, replacing manual inspection of each node. The detection frequency has been increased to 4 times/hour (previously only 1 time/8 hours manually), and fault warning is triggered 24 hours in advance. (II) Dynamic automation adjustment of computing power topology
Based on real-time computing load data, link weights are automatically adjusted through Software Defined Networking (SDN), replacing manual configuration. Topology switching latency is reduced from 180s to within 20s
The switching of computing power failure nodes adopts automated redundant link takeover, without the need for manual intervention, and the fault recovery time is shortened from 300 seconds to within 10 seconds. (III) Automated closed-loop scheduling of computing power tasks
The entire process of task issuance, computing power matching, and result recovery is completed through an automated scheduling engine, replacing manual scheduling and improving task processing efficiency by over 50%
Energy consumption and computing power optimization linkage: Automated algorithms dynamically adjust the computing power output threshold based on node load, reducing no-load energy consumption by 15% -20%. Secondly, key supporting conditions for efficiency improvement
An automated scheduling system that complies with GB/T 33145-2016 "Cloud Computing Service Capability Requirements" should be adopted to connect with the existing PUE monitoring system of the intelligent computing center
The transformation requires synchronous updating of the digital interface of the nodes to ensure real-time data collection and instruction transmission (delay ≤ 10ms)
The transformation process involving high-voltage cabinets and high-speed networks must be operated by certified professionals, and unauthorized personnel are strictly prohibited from intervening in the safety boundary of the transformation
The operation of high-voltage equipment shall comply with GB 7251.1-2013 "Low voltage switchgear and control equipment - Part 1: General", and the safety threshold of automation equipment shall be pre-set with overcurrent and overvoltage protection
The network of the automated scheduling system needs to use encrypted transmission, with three-level hierarchical control of operation and maintenance permissions to prevent illegal operations from causing computing power abnormalities
