Biological sequence data-base searching multilayered accelerating method based on flow process

Abstract

The invention discloses a multi-level acceleration method of flow-based biological sequence database search, which is to accelerate the search speed of a biological sequence database on the premise of ensuring search accuracy and relatively low cost. The technical proposal is that a cluster system composed of a plurality of personal computers shall be created firstly, and a master control node machine is assigned; the master control node machine distributes the database sequence and stores into each node machine in the cluster system, so as to fill and rearrange an inquiry sequence, and distribute the inquiry sequence to all the node machines in the cluster system; each node machine executes the search task in parallel, so as to be responsible for the completion of search tasks of the inquiry sequence in a local database sequence; the master control node machine collects, summarizes and outputs the results of parallel search tasks on all the node machines. The invention makes the search tasks be executed in parallel between the n node machines of the cluster, each node machine distributes the comparative calculation task of two sequences to p hardware calculation clusters to be conducted in parallel, thereby realizing the multi-level acceleration objective in parallel of three layers including a cluster node layer, a flow-level calculation layer, as well as a flow inner core command layer.

Description

technical field

[0001] The invention mainly relates to a method for retrieving and comparing massive biological information in life science and information science, especially a method for multi-level acceleration of biological sequence database search. Background technique

[0002] In recent years, with the continuous development and deepening of the genome projects of various species, massive biological sequence data have been generated, which mainly include DNA (deoxyribonucleic acid), RNA (ribonucleic acid) sequence data and protein sequence data. For example, the amount of data in GenBank / EMBL / DDBJ, the three major international nucleic acid databases, doubles approximately every 15 months, and the speed of data growth is still accelerating. According to Moore's Law, the growth rate of biological data is or will soon be The growth rate exceeds the computer processing power, so according to this growth trend, searching and processing these data will take longer (in the c...

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