Job scheduling method based on bioinformation cloud platform

Abstract

The invention discloses a job scheduling method based on a bioinformation cloud platform, and relates to the technical field of construction of cloud platforms. The job scheduling method comprises the following steps of: S1: transferring a parameter character stream to a service layer by utilizing an expression layer; S2: generating a parameter file named by a program according to parametric variables in the parameter character stream and a program name at the head part of the parameter character stream; S3: finally, assembling into a job submission script with a uniform format and submittingthe job to a resource layer according to an appointed path, the job type and a file name of a parameter file, wherein the job submission script also comprises a job submission command corresponding to the job type; and S4: leading the resource layer to analyze the job submission script, and executing the job submission command so as to call a program required to call a job. The job scheduling method provided by the invention has the advantages of implementing software quick integration of the platform, improving expandability and allocation of the platform, lowering development cost, and shortening development cycle.

Description

technical field [0001] The invention relates to the technical field of cloud platform construction, in particular to a job scheduling method based on a biological information cloud platform. Background technique [0002] With the popularization of second-generation sequencing technology in the field of genomics, more and more biological researchers seek to use high-performance computer clusters to process large amounts of data generated by high-throughput sequencing. However, due to the continuous emergence of new bioinformatics data analysis software around the world, and the continuous acceleration of algorithm updates, researchers not only need to know how to use and manage the hardware system, but also must be proficient in the deployment and debugging of various analysis software. Track cutting-edge software and its new releases. [0003] In order to free researchers from the work of complex computer systems and focus more on the work of biology itself, many research i...

AI Technical Summary

Problems solved by technology

Faced with thousands of analysis software, such a workload is too large, and a large number of developers must be used to maintain the update of background analysis software, resulting in poor scalability and deployability;

[0008] 2. The integration of each new software requires a variety of developers to coordinate their work, including JAVA, PERL and other engineers. The time period is long and the cost is high

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