Dell Products Inc.

Emc IP Holding Company LLC

Arunava Das Gupta

Niladri Bhattacharya

Chandrashekar Nelogal

Vaideeswaran Ganesan

A storage usage management system includes a storage usage management subsystem coupled to first and second storage devices. The storage usage management subsystem collects first write usage data from use of the first storage device by a host mapped to the first storage device, determines that second write usage data from use of the first storage device by the host exceeds first metric(s) associated with the first write usage data by a first threshold, and collects the second write usage data and third write usage data from immediately subsequent use of the first storage device by the host. If the storage usage management subsystem determines that the second and third write usage data exceed second metric(s) associated with the first write usage data by a second threshold, it uses the second and third write usage data to determine whether to remap the host to the second storage device.

Storage-usage-based host/storage mapping management system

An information handling system may have a long short term memory (LSTM) that receives Input/Output (I/O) parameters, and produces a prediction output by operation of a recursive neural network (RNN). An I/O optimizer provides the I/O parameters to the LSTM and receives the prediction output from the LSTM. The I/O optimizer may include a manager module configured to provide control signals to control gates for controlling application of the I/O parameters and the prediction output, and a collector module configured to collect the I/O parameters.

System and method for Input/Output (I/O) pattern prediction using recursive neural network and proaction for read/write optimization for sequential and random I/O

Systems and methods for tiering data in distributed data networks. A global model is developed based on federated learning where edge servers are able to train a model. The learning from the edge servers are collectively applied to the global model. This process can be repeated until the global model is ready for deployment. The global model allows data to be tiered. This may include pushing data from a datacenter to edge servers or cleaning edge servers of data that does not satisfy the global model. The model can be retrained and can be used to proactively push new content out to the edge servers.

Data tiering for edge computers, hubs and central systems

A linguistic semantic analysis application integration system includes an application and one or more linguistic semantic analysis databases that include application-specific programming language information that identifies application-specific programming language terms utilized in providing the application. A linguistic semantic analysis engine is provided a module to be utilized by the application, and operates to analyze the module to determine methods and properties included in the module. The methods and properties are then parsed to identify library programming language terms included in the methods and properties, and those library programming language terms are matched with the application-specific programming language terms included in the application-specific programming language information. Based on that matching, intent for the methods and properties is determined, and that intent is used to automatically generate integration code for integrating the module with the application.

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Arunava Das Gupta