Lemon Inc.

Beijing Bytedance Network Technology Co., Ltd.

Beijing Youzhuju Network Technology Co., Ltd.

Zherui Liu

Jian Wang

Sikai Qi

Zongqiang Zhang

Zhichao Li

Chuanxiong Guo

Jing Wang

Binbin Xu

Shengli Liu

Yibo Zhu

Yang Zhang

Cheng Tan

Zishuai Lou

Zhiyi Xia

Siyang Li

Jian Zhang

Heting Liu

A video memory allocation method and apparatus, and a medium and an electronic device are provided. The method includes: determining a usage capacity of a physical video memory in response to receiving a first call request of an application program for a video memory allocation interface in a target video memory management link library; if a sum of the usage capacity and an applied capacity corresponding to the first call request is greater than a total capacity of the physical video memory, generating a second call request for calling a memory hosting interface according to the first call request, and calling the memory hosting interface based on the second call request; and obtaining a response of the first call request according to a calling result of the second call request.

Video memory allocation method and apparatus, and medium and electronic device

The present disclosure provides a resource allocation method and apparatus, a readable medium and an electronic device. The method includes: acquiring a target resource type corresponding to a target task; acquiring a plurality of resource types of a target processor, wherein each resource type corresponds to one or more virtual processor resources of the target processor; determining a specified resource type that is identical to the target resource type from the plurality of resource types; determining a target processor resource from one or more virtual processor resources corresponding to the specified resource type; and allocating the target processor resource to the target task.

Method and apparatus for segmenting GPU resources into virtual processing resource types and allocating to different target tasks

The present disclosure provides a prediction method and an apparatus for a faulty GPU, an electronic device and a storage medium. The method includes: acquiring parameter information of each GPU in a plurality of GPUs to obtain a parameter information set; inputting the parameter information set into a plurality of pre-trained prediction models to obtain a prediction result corresponding to each prediction model; and determining a faulty GPU from the plurality of GPUs according to the prediction result.

Prediction method and apparatus for faulty GPU, based on prediction model electronic device and storage medium

Embodiments of the disclosure provide a method and apparatus for running a service, and an electronic device. An embodiment of the method includes: determining a target deployment manner of a graphics processing unit (GPU) according to performance data of each service in a service set, where the deployment manner includes: dividing the GPU into sub-GPUs of a respective size and determining a service configured to be run by each sub-GPU; and switching, for the service in the service set, running of the service from a sub-GPU indicated by a current deployment manner to a sub-GPU indicated by the target deployment manner. According to the embodiment, waste of the GPU can be reduced by running a plurality of services on the GPU.

Method and apparatus for runing a service, and electronic device

Growing community of inventors

Beijing, China

Zherui Liu