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Determine a load balancing mechanism for allocation of shared resources in a storage system using a machine learning module based on number of I/O operations

專利號(hào)
US11175958B2
公開(kāi)日期
2021-11-16
申請(qǐng)人
INTERNATIONAL BUSINESS MACHINES CORPORATION(US NY Armonk)
發(fā)明人
Lokesh M. Gupta; Matthew R. Craig; Beth Ann Peterson; Kevin John Ash
IPC分類
G06F9/50; G06N3/08; G06N20/00
技術(shù)領(lǐng)域
tcbs,learning,storage,in,machine,host,module,adapter,controller,resources
地域: NY NY Armonk

摘要

A plurality of interfaces that share a plurality of resources in a storage controller are maintained. In response to an occurrence of a predetermined number of operations associated with an interface of the plurality of interfaces, an input is provided on a plurality of attributes of the storage controller to a machine learning module. In response to receiving the input, the machine learning module generates an output value corresponding to a number of resources of the plurality of resources to allocate to the interface in the storage controller.

說(shuō)明書

In certain embodiments shown in FIG. 16, the plurality of interfaces comprise a plurality of ports of a host bus adapter that communicatively couples the storage controller to a host computational device. The plurality of resources comprise a plurality of task control blocks for executing a plurality of input/output (I/O) operations that are received by the host bus adapter from the host computational device.

FIG. 17 illustrates a flowchart that shows a determination of load balancing mechanism for shared resource in a storage system by training a machine learning module, in accordance with certain embodiments;

Control starts at block 1702 in which a machine learning module 106 receives inputs comprising attributes of a storage controller 102, wherein the attributes affect allocation of a plurality of resources to a plurality of interfaces in the storage controller. In response to a predetermined number of I/O operations occurring in the storage controller 102, a generation is made (at block 1704) via forward propagation through a plurality of layers of the machine learning module 106 of an output value corresponding to a number of resources to allocate to an interface of the plurality of interfaces in the storage controller 102.

權(quán)利要求

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