Methods for performing input-output operations in a storage system using artificial intelligence and devices thereof
AssigneeNetApp, Inc.
InventorDouglas Joseph Santry
Life of this patent
Estimating the term…
Abstract
The present technology relates to identifying one of a plurality of artificial intelligence models based on a received key value. The received key value is applied to the identified one of the artificial intelligence models which is trained to output one of a plurality of actual index values. The one of the actual index values is compared to a range within the actual index values to determine when the one of the actual index value points to the data block. A received input-output operation is performed on the data block when the one of the actual index values is determined to point to the data block.
Claims17
A method for servicing input/output (I/O) operations in a data storage network with reduced media access requests, the method implemented by one or more data storage apparatuses and comprising:
- traversing a neural tree based on a key received with a write operation to identify a current data block, wherein the neural tree comprises a plurality of hierarchically arranged nodes comprising interior nodes and leaf nodes, the interior nodes comprise artificial intelligence models, one of the leaf nodes comprises the current data block, and the write operation is received from a client device via a storage network connection;
- determining that a layout of the neural tree requires modification;
- creating a new data block on a data storage device in the data storage network;
- assigning a first index to the new data block;
- executing the write operation via a data fabric based on a storage location on the data storage device associated with the new data block;
- and
- retraining, by the computing device, the one of the artificial intelligence models to output the first index assigned to the new data block instead of a second index pointing to the current data block.
A non-transitory machine readable medium having stored thereon instructions for servicing input/output (I/O) operations in a data storage network with reduced media access requests comprising machine executable code that, when executed by at least one machine, causes the machine to:
- traverse a neural tree based on a key received with a delete operation to identify a data block, wherein the neural tree comprises a plurality of hierarchically arranged nodes comprising interior nodes and leaf nodes, the interior nodes comprise artificial intelligence models, one of the leaf nodes comprises the data block, and the delete operation is received from a client device via a storage network connection;
- execute the delete operation via a data fabric based on a storage location on a data storage device in the data storage network determined from the data block;
- determine that a layout of the neural tree requires modification as a result of the delete operation;
- and
- retrain one of the artificial intelligence models to output a first index that is assigned to another one of the artificial intelligence models instead of a second index pointing to the data block.
A computing device for servicing input/output (I/O) operations in a data storage network with reduced media access requests, the computing device comprising:
- memory containing machine readable media comprising machine executable code having stored thereon instructions;
- and
- one or more processors coupled to the memory and configured to execute the machine executable code to cause the processors to:
- traverse a tree based on a key received with a storage operation to identify a data block, wherein the tree comprises a plurality of hierarchically arranged nodes comprising trained neural networks and the storage operation is received from a client device via a storage network connection;
- execute the storage operation via a data fabric based on a storage location on a data storage device in the data storage network determined from the data block;
- determine that a layout of the tree requires modification as a result of the storage operation;
- and
- retrain one of the trained neural networks to output a first index instead of a second index pointing to the data block.
Dependencies are inferred from the claim text.