MPI (Moldflow Plastics Insight) information scheduling method based on reinforcement learning under multi-network environment

A multi-network environment and reinforcement learning technology, applied in the field of message scheduling, can solve problems such as unbalanced communication load distribution, poor adaptability to computing environments, and inability to adapt to dynamic changes in network status.

Inactive Publication Date: 2010-09-15
NAT UNIV OF DEFENSE TECH
View PDF4 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0027] The technical problem to be solved in the present invention is to address the defects of the round-robin scheduling method, and propose an MPI message scheduling method based on reinforcement learning, which acquires and saves the experience value of the scheduling process through self-learning, and dispatches messages according to the current st...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • MPI (Moldflow Plastics Insight) information scheduling method based on reinforcement learning under multi-network environment
  • MPI (Moldflow Plastics Insight) information scheduling method based on reinforcement learning under multi-network environment
  • MPI (Moldflow Plastics Insight) information scheduling method based on reinforcement learning under multi-network environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0088] figure 1 It is a flowchart of the round-robin scheduling method in the background technology. The specific implementation is as follows:

[0089] The first step, initialization: set the identification i=0 of the sending network, set the value of the maximum length seg_max of the message segment, set and start the sending timer timer;

[0090] The second step, waiting for the message sending request of the parallel application program: if there is an unprocessed message sending request, take out the message request that arrives first, obtain the MPI message that the request needs to send, and set the scheduling end flag FINISHED=0, turn to the first step Three steps, otherwise continue to wait;

[0091] The third step is to obtain the current message segment according to the value of seg_max: if the MPI message has been fully scheduled, that is, FINISHED=1, then go to the second step; Take a piece of content with a length of seg_max from the part in order from front ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an MPI (Moldflow Plastics Insight) information scheduling method based on reinforcement learning under a multi-network environment, aiming at overcoming the defect of low practical application performance of a high-performance parallel computer, caused by the traditional circulating scheduling method. The method comprises the steps of: initiating parameters in a process of starting an MPI system, creating Cm<2> Q tables according to a multiple Q table combined method for a computing environment matched with m networks; continuously receiving an MPI information sending request sent by application in a process of starting the MPI system, determining a current information segment, then obtaining a current environment state, scheduling the current information segment to an optimal network according to the state information of historical empirical values stored in the Q tables; and finally, computing an instant reward value obtained by the scheduling and updating Q values in the Q tables. By adopting the invention, the problems that communication loads are distributed unequally, can not adapt to the network state dynamic change and have poor adaptability on the computing environment can be solved, and the practical application performance of the high-performance parallel computer is improved.

Description

technical field [0001] The invention relates to a message scheduling method in an MPI system under a multi-set communication network environment. Background technique [0002] In the field of high-performance computing, the inter-process communication of parallel applications mostly adopts the method of message passing, and a standard message passing interface (Message Passing Interface, MPI) is provided for the design of parallel programs. The specific component that implements the standard message passing interface is called the MPI system. In the high-performance parallel computer system, the MPI system is responsible for the execution of parallel applications. interprocess communication . When the computing power of a single computing node is not high, the high-performance parallel computer only needs to configure a communication network for communication between computing nodes. At this time, there is no problem of scheduling MPI messages on multiple sets of networks. ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F9/54
Inventor 蒋艳凰卢宇彤赵强利谢旻周恩强曹宏嘉陈海涛董勇所光
Owner NAT UNIV OF DEFENSE TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap