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Task scheduling method and device for heterogeneous hardware of artificial intelligence and readable medium

A heterogeneous hardware and artificial intelligence technology, which is applied in the directions of multi-program device, program startup/switching, resource allocation, etc., can solve problems such as low resource utilization, inability to achieve resource isolation, and difficulty in virtualization, etc., to achieve improved The effect of resource utilization

Active Publication Date: 2018-05-01
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Based on the above, the current AI heterogeneous hardware is difficult to achieve virtualization, resource isolation cannot be achieved, and there is no way to improve resource utilization through mixing, so resource utilization is very low

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  • Task scheduling method and device for heterogeneous hardware of artificial intelligence and readable medium
  • Task scheduling method and device for heterogeneous hardware of artificial intelligence and readable medium
  • Task scheduling method and device for heterogeneous hardware of artificial intelligence and readable medium

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Embodiment Construction

[0059] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0060] figure 1 It is a flow chart of an embodiment of the AI ​​heterogeneous hardware task scheduling method of the present invention. Such as figure 1 As shown, the AI ​​heterogeneous hardware task scheduling method of this embodiment may specifically include the following steps:

[0061] 100. Receive the task execution request of the corresponding function sent by the API, and the task execution request carries the attribute information of the task;

[0062] The AI ​​heterogeneous hardware task scheduling method of this embodiment is executed by the AI ​​heterogeneous hardware task scheduling device, and the AI ​​heterogeneous hardware task scheduling device can be set in the driver of the AI ​​heterogeneous hardware. The AI ​​heterogeneous ...

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Abstract

The invention provides a task scheduling method and device for heterogeneous hardware of artificial intelligence and a readable medium. The method comprises the following steps of: receiving a task execution request of a corresponding function sent by an API, wherein the task execution request carries attribute information of tasks; obtaining priorities of the tasks according to the attribute information of the tasks, wherein the priorities of online services are higher than the priorities of offline tasks; inserting corresponding tasks into a scheduling queue of the corresponding function according to the priorities of the tasks, wherein the tasks in the scheduling queue are arranged according to the priorities from high to low; and sequentially controlling idle calculation units in a plurality of calculation units of the corresponding function to execute corresponding tasks according to the high-to-low priority sequence of the tasks in the scheduling queue. According to the method and device and the readable medium, mixed step of offline model training tasks and online reasoning services can be realized according to different priorities, so as to greatly improve the resource utilization rate.

Description

【Technical field】 [0001] The present invention relates to the field of computer application technology, in particular to a task scheduling method, device and readable medium for heterogeneous hardware of artificial intelligence. 【Background technique】 [0002] Artificial Intelligence (AI) has been widely used in various fields, especially the new method represented by deep learning in recent years, in many fields such as speech recognition, image recognition, click-through-rate (Click-Through-Rate) ; CTR) and natural language processing fields, etc., have achieved the most advanced (state-of-the-art) effect. [0003] The current main methods of AI technology are machine learning and deep learning, which mainly include: model training and model reasoning. Model training is mainly to train a model through historical data, and then use the model for online reasoning in the model reasoning stage. Due to performance reasons, AI heterogeneous hardware is widely used in model tra...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06F9/48
CPCG06F9/4881G06F9/5038G06F9/4837G06F9/485G06F9/5044
Inventor 王勇欧阳剑漆维
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD