见证历史！华为，重大发布

Core Viewpoint - Huawei has officially launched a groundbreaking AI technology called Flex:ai, which can enhance the average utilization rate of computing resources by 30% in AI workload scenarios where full card computing power is not utilized [2]. Group 1: Flex:ai Overview - Flex:ai is a software for pooling and scheduling various types of processors (XPU) built on Kubernetes, similar to Nvidia's Run:ai technology, but with two unique advantages [2]. - The technology is considered an important tool for the industrialization of AI, and Huawei plans to open-source it to the Magic Engine community to build a complete ModelEngine open-source ecosystem [2][15]. Group 2: Importance of AI Container Technology - In the era of large models, container technology is seen as a natural partner for AI, allowing for the packaging of model code and runtime environments into lightweight images for seamless cross-platform migration [5]. - Container technology can dynamically mount GPU and NPU computing resources, enhancing overall resource utilization in clusters [6]. - It is projected that by 2027, over 75% of AI workloads will be deployed and run using container technology [6]. Group 3: Key Capabilities of Flex:ai - Flex:ai offers three key capabilities: resource slicing, multi-level intelligent scheduling, and cross-node resource aggregation [7]. - The resource slicing feature allows a single GPU/NPU card to be divided into multiple virtual computing units with a precision of up to 10%, enabling multiple AI workloads to run simultaneously on a single card [7]. Group 4: Advantages Over Competitors - Flex:ai has two distinct advantages over Nvidia's Run:ai: virtualization and intelligent scheduling [11]. - The unique "remote virtualization" technology allows for the aggregation of idle XPU computing power across nodes into a shared computing pool without complex distributed task settings [11]. - Flex:ai's intelligent scheduling can automatically sense cluster load and resource status, optimizing the allocation of local and remote virtualized GPU and NPU resources based on workload priorities and requirements [11][12]. Group 5: Contribution to ModelEngine Ecosystem - The release and open-sourcing of Flex:ai will help Huawei build a complete ModelEngine open-source ecosystem, which includes previously released tools like Nexent intelligent framework and AppEngine [15]. - Flex:ai can facilitate the exploration of AI container technology in various industry scenarios, providing foundational capabilities to enhance computing resource utilization [18].