View source for 17838481. Storage System and Method for Inference of Read Thresholds Based on Memory Parameters and Conditions simplified abstract (Western Digital Technologies, Inc.)

=Storage System and Method for Inference of Read Thresholds Based on Memory Parameters and Conditions=


==Organization Name==

[[:Category:Western Digital Technologies, Inc.|Western Digital Technologies, Inc.]]


[[Category:Western Digital Technologies, Inc.]]

==Inventor(s)==

[[:Category:Eran Sharon of Rishon Lezion (IL)|Eran Sharon of Rishon Lezion (IL)]][[Category:Eran Sharon of Rishon Lezion (IL)]]

[[:Category:Ariel Navon of Revava (IL)|Ariel Navon of Revava (IL)]][[Category:Ariel Navon of Revava (IL)]]

[[:Category:Alexander Bazarsky of Holon (IL)|Alexander Bazarsky of Holon (IL)]][[Category:Alexander Bazarsky of Holon (IL)]]

[[:Category:David Avraham of San Jose CA (US)|David Avraham of San Jose CA (US)]][[Category:David Avraham of San Jose CA (US)]]

[[:Category:Nika Yanuka of Hadera (IL)|Nika Yanuka of Hadera (IL)]][[Category:Nika Yanuka of Hadera (IL)]]

[[:Category:Idan Alrod of Herzeliya (IL)|Idan Alrod of Herzeliya (IL)]][[Category:Idan Alrod of Herzeliya (IL)]]

[[:Category:Tsiko Shohat Rozenfeld of Los Altos CA (US)|Tsiko Shohat Rozenfeld of Los Altos CA (US)]][[Category:Tsiko Shohat Rozenfeld of Los Altos CA (US)]]

[[:Category:Ran Zamir of Ramat Gan (IL)|Ran Zamir of Ramat Gan (IL)]][[Category:Ran Zamir of Ramat Gan (IL)]]

==Storage System and Method for Inference of Read Thresholds Based on Memory Parameters and Conditions - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17838481 titled 'Storage System and Method for Inference of Read Thresholds Based on Memory Parameters and Conditions

==Simplified Explanation==

'''Abstract:'''
A storage system has an inference engine that can infer a read threshold based on various parameters of the memory. This read threshold can be used during regular read operations or as part of error handling processes. By using machine learning, the accuracy of the read threshold can be significantly improved, leading to reduced bit error rate, improved latency, throughput, power consumption, and quality of service.

'''Patent/Innovation Explanation:'''
* The storage system includes an inference engine that can determine a read threshold for reading a wordline in the memory.
* The read threshold is inferred based on multiple parameters of the memory.
* This machine-learning-based approach improves the accuracy of the read threshold.
* The read threshold can be used in regular read operations or error handling processes.
* By accurately determining the read threshold, the system can reduce bit error rate and improve various performance metrics such as latency, throughput, power consumption, and quality of service.

'''Potential Applications:'''
* Data storage systems in various industries such as cloud computing, data centers, and enterprise storage.
* Solid-state drives (SSDs) and flash memory devices.
* Embedded systems and IoT devices that require efficient and reliable storage.

'''Problems Solved:'''
* Inaccurate read thresholds in storage systems can lead to higher bit error rates and reduced performance.
* Traditional methods of determining read thresholds may not account for various parameters of the memory, resulting in suboptimal performance.
* Error handling processes may not have accurate read thresholds, leading to inefficient error recovery.

'''Benefits:'''
* Improved accuracy of read thresholds leads to reduced bit error rate.
* Enhanced performance metrics such as latency, throughput, power consumption, and quality of service.
* More efficient error handling processes with accurate read thresholds.
* Increased reliability and data integrity in storage systems.


==Original Abstract Submitted==

A storage system has an inference engine that can infer a read threshold based on a plurality of parameters of the memory. The read threshold can be used in reading a wordline in the memory during a regular read operation or as part of an error handling process. Using this machine-learning-based approach to infer a read threshold can provide significant improvement in read threshold accuracy, which can reduce bit error rate and improve latency, throughput, power consumption, and quality of service.



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