Boe Technology Group Co., Ltd.

Beijing Boe Sensor Technology Co., Ltd.

Beijing Bytedance Network Technology Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Binbin Xu

Bin Zhao

Shuai Xu

Ye Zhang

Yongkang Xie

En Shi

Jian Wang

Chuncheng Che

Jie Liu

Chao Xi Chen

Ying Zhao

Xuecheng Hou

Jinyu Li

Liang Tang

Xiaoyu Chen

Shupeng Li

Shengli Liu

Zherui Liu

Zhengyu Qian

Sikai Qi

Zongqiang Zhang

Lianghuo Zhang

Tuobang Wu

Zishuai Lou

Zhiyi Xia

Siyang Li

Wenchen Zhang

Zhenqian Zhao

Jingshu Zhang

Xiaoqian Du

Junyu Wu

Luyao Fan

A resource scheduling method and apparatus, a device, and a storage medium are provided, and relates to the field of computer technology, and in particular to the field of deep learning technology. The method includes: acquiring a graphics processing unit (GPU) topology relationship of a cluster according to GPU connection information of each of computing nodes in the cluster; and in a case where a task request, for applying for a GPU resource, for a target task is received, determining a target computing node of the target task and a target GPU in the target computing node according to the task request and the GPU topology relationship, to complete GPU resource scheduling of the target task. The present disclosure can optimize the resource scheduling.

Resource scheduling method, device, and storage medium

The present disclosure discloses a method and an apparatus for adapting a deep learning model, an electronic device and a medium, which relates to technology fields of artificial intelligence, deep learning, and cloud computing. The specific implementation plan is: obtaining model information of an original deep learning model and hardware information of a target hardware to be adapted; querying a conversion path table according to the model information and the hardware information to obtain a matched target conversion path; and converting, according to the target conversion path, the original deep learning model to an intermediate deep learning model in the conversion path, and converting the intermediate deep learning model to the target deep learning model. Therefore, the deep learning model conversion is performed based on the model conversion path determined by the model information of the original deep learning model and the hardware information of the target hardware, which realizes converting any type of original deep learning model into the target deep learning model adapted to any target hardware, and solves the problem that the deep learning model is difficult to be applied to different hardware terminals.

Method and apparatus for adapting deep learning model, 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 discloses a flat panel detector, a driving method, a driving device and a flat panel detection device. The flat panel detector includes: a base substrate, and a plurality of detection units located on the base substrate; each of the detection units includes a photodiode and a detection transistor; the flat panel detector further includes: a compensation semiconductor material layer including a plurality of compensation structures mutually spaced; each detection transistor is correspondingly provided with a compensation structure, and the compensation structure is located between a gate and a gate insulating layer of the corresponding detection transistor.

Flat panel detector, driving method, driving device and flat panel detection device

A detection substrate and manufacturing method thereof, a flat panel detector and manufacturing method thereof. The detection substrate includes: a substrate including a detection region, a binding region, a controllable on-off region, and a cutting region; a plurality of detection units including transistors and photosensitive devices located in the detection region, a transistor includes a gate, a first electrode and a second electrode; a photosensitive device is connected to the first or second electrode; a plurality of conductive wires, one end is connected to the gate, and the other end is extended to the binding region; a conductive ring disposed in the cutting region; a plurality of detection wires, one end is connected to the conductive ring, the other end is connected to the conductive wires, the detection wires are passed through the controllable on-off region; the detection wires located in the controllable on-off region can have a disconnected state.

Detection substrate and manufacturing method thereof, flat panel detector and manufacturing method thereof

Sensing circuit, detection control method, fingerprint identification module and display apparatus are provided. The sensing circuit comprises a photoelectric conversion element, an energy storage circuit, a switch control circuit, a discharge control circuit and a voltage conversion circuit. The photoelectric conversion element controls potential of first terminal of energy storage circuit according to received optical signal; the switch control circuit controls first terminal of energy storage circuit to be connected to or disconnected from conversion control node; the discharge control circuit controls conversion control node be connected to or disconnected from first voltage terminal; the voltage conversion circuit controls to output voltage signal outputted by output terminal according to second and/or third voltage signals. In the disclosure, by performing fingerprint identification by detecting duration length of the fourth voltage signal from output terminal, fingerprint image information can be obtained simply and efficiently, thereby improving fingerprint identification accuracy and preventing interference.

Sensing circuit, detection control method, fingerprint identification module and display apparatus

Growing community of inventors

Beijing, China

Binbin Xu