Abstract: This application provides a model inference method and apparatus based on a graphics rendering pipeline, and a storage medium for model inference based on a graphics rendering pipeline. The method includes: obtaining an instruction stream in a render thread; extracting and saving texture data information from the instruction stream, where the texture data information includes texture data; and inputting the texture data information to a graphics processing unit (GPU) rendering pipeline, where the GPU rendering pipeline is used to perform GPU model-based inference on the texture data based on a GPU model to obtain an inference result of the texture data, and the GPU model is a model running in a GPU. This implements model inference on the texture data, and avoids conversion of the texture data into another data type, thereby reducing I/O memory overheads.

Abstract: An application management method includes collecting a plurality of objects in an application example used for serverless computing and generating a base tree according to a reference hierarchical relationship of the plurality of objects; performing internal memory object rearrangement on a plurality of application examples according to the base tree; and performing internal memory merging on the plurality of rearranged application examples.

Abstract: A container-based application management method and apparatus are disclosed. A container-based serverless computing system is configured such that an application instance is allowed to be in one of an online state and a low-power state at runtime. In response to scaling down an application, at least one first application instance of the application in the online state is caused to enter the low-power state; and in response to scaling up the application, at least one second application instance of the application in the low-power state is caused to enter the online state. In this way, not only the cost of the application instance can be reduced, but also rapid elastic scaling can be performed on the application instance.

Abstract: An application and system fast launch may provide a virtual memory address area (VMA) container to manage the restore of a context of a process, i.e., process context, saved in response to a checkpoint to enhance performance and to provide a resource efficient fast launch. More particularly, the fast launch may provide a way to manage, limit and/or delay the restore of a process context saved in response to a checkpoint, by generating a VMA container comprising VMA container pages, to restore physical memory pages following the checkpoint based on the most frequently used or predicted to be used. The application and system fast launch with the VMA container may avoid unnecessary input/output (I/O) bandwidth consumption, page faults and/or memory copy operations that may otherwise result from restoring the entire context of a VMA container without regard to frequency of use.

Abstract: An application and system fast launch may provide a virtual memory address area (VMA) container to manage the restore of a context of a process, i.e., process context, saved in response to a checkpoint to enhance performance and to provide a resource efficient fast launch. More particularly, the fast launch may provide a way to manage, limit and/or delay the restore of a process context saved in response to a checkpoint, by generating a VMA container comprising VMA container pages, to restore physical memory pages following the checkpoint based on the most frequently used or predicted to be used. The application and system fast launch with the VMA container may avoid unnecessary input/output (I/O) bandwidth consumption, page faults and/or memory copy operations that may otherwise result from restoring the entire context of a VMA container without regard to frequency of use.