Micron Technology Incorporated

Vamsi Pavan Rayaprolu

Kishore Kumar Muchherla

Ashutosh Malshe

Sampath K Ratnam

Harish Reddy Singidi

Shane G Nowell

Mustafa Nazmi Kaynak

Sivagnanam Parthasarathy

Gianni Stephen Alsasua

Peter Sean Feeley

Karl David Schuh

Steven Michael Kientz

Michael Sheperek

Renato C Padilla

Christopher M Smitchger

Jiangang Wu

Gary F Besinga

Renato Padilla, Jr

Michael G Miller

Patrick Robert Khayat

Larry Joseph Koudele

Qisong Lin

Xiangang Luo

Jeffrey S McNeil, Jr

Tawalin Opastrakoon

Giuseppina Puzzilli

Bruce A Liikanen

Saeed Sharifi Tehrani

Violante Moschiano

Jianmin Huang

James Fitzpatrick

Niccolo' Righetti

Gil Golov

Aswin Thiruvengadam

Zixiang Loh

Shuhui Chen

Ugo Russo

Walter Di Francesco

Niccolo′ Righetti

Nagendra Prasad Ganesh Rao

Jay Sarkar

Jeffrey Scott McNeil, Jr

Roy Leonard

Hong Lu

Guang Chang Ye

Shao Chun Shi

Thomas Herbert Lentz

Ipsita Ghosh

Zhenming Zhou

Eric N Lee

Murong Lang

Ting Luo

Seungjune Jeon

Dung Viet Nguyen

Todd A Marquart

Suresh Rajgopal

Charles See Yeung Kwong

Tecla Ghilardi

Li-Te Chang

Ling Wang

HyungSeok Kim

Yue Wei

Shyam Sunder Raghunathan

Larry K Koudele

Hyung Seok Kim

A processing device in a memory sub-system detects an occurrence of a data integrity check trigger event and, responsive to the occurrence of the data integrity check trigger event, identifies a memory die of a plurality of memory dies. The processing device further associates each segment of the identified memory die with a respective group of a plurality of groups, each group representing one or more of a plurality of error mechanisms, and determines one or more respective adaptive scan frequencies for the identified memory die based on statistics of the segments associated with each respective group.

Adaptive integrity scan rates in a memory sub-system based on block health metrics

A system includes a memory device and a processing device, operatively coupled with the memory device, to perform operations including: determining whether a program erase cycle count associated with a segment of the memory device satisfies a first threshold criterion for triggering an offset bin update; responsive to determining that the program erase cycle count satisfies the first threshold creation, performing a calibration measurement of a center of a voltage valley for each state of each cell in the segment of the memory device; and updating a threshold voltage offset bin associated with the segment of the memory device based on a result of the calibration measurement.

Adaptive calibration for threshold voltage offset bins

A method includes determining respective valid translation unit counts of a block of non-volatile memory cells over a period of time, determining a rate of change of the respective valid translation unit counts of the block of non-volatile memory cells over the period of time, comparing the rate of change of the valid translation unit counts to a bin transition rate, and based on comparing the rate of change of the valid translation unit counts to the bin transition rate, performing a media management operation on the block of non-volatile memory cells.

Data age and validity-based memory management

Described are systems and methods for validating read level voltage in memory devices. An example memory device comprises: a memory array comprising a plurality of memory cells electrically coupled to a plurality of wordlines; and a controller coupled to the memory array, the controller to perform operations comprising: causing a read level voltage to be applied to a specified wordline of the plurality of wordlines; receiving an actual bit count reflecting a number of memory cells that have their respective threshold voltages below the read level voltage; and responsive to determining that a difference of an expected bit count and the actual bit count exceeds a predetermined threshold value, adjusting the read level voltage.

Validating read level voltage in memory devices

One or more trim values associated with a set of blocks of a memory device are set according to a representative number of program erase cycles (PECs) for the set of blocks. Each block in the set of blocks was programmed within at least one of a specified time window or a specified temperature range. Responsive to executing a program operation on a block of the set of blocks according to the one or more trim values, an indicator is set to reflect the one or more trim values used during the execution of the program operation. Responsive to receiving a request to perform a read operation directed to the block of the set of blocks, a read offset value corresponding to the indicator is determined. The read operation is performed using the read offset value.

Charge loss mitigation throughout memory device lifecycle by proactive window shift

A first host data item and a second host data item are received. The first host data item is stored in a first page of a first logical unit of a memory device, where the first page is one of a plurality of pages associated with redundancy metadata. A second page a second page of a second logical unit of the memory device is identified, where the second page is one of the plurality of pages associated with the redundancy metadata, and the first page and the second page are associated with different wordlines of the memory device. The second host data item is stored in the second page of the second logical unit of the memory device. The first page and the second page can be associated with a fault tolerant stripe that includes the redundancy metadata.

Diagonal page mapping in memory systems

Systems and methods are disclosed including a memory device and a processing device operatively coupled to the memory device. The processing device can perform operations including running sample data through each of a set of error-handling operations performed on data residing in a segment of the memory device in an existing order; and determining an optimized order of the set of error-handling operations based on probability data and latency data, wherein the probability data is associated with a result of running the sample data, and wherein the optimized order comprises an adjustment to an order of one or more error-handling operations of the set of error-handling operations in the existing order.

Management of error-handling flows in memory devices using probability data structure

Systems and methods are disclosed including a memory device and a processing device operatively coupled to the memory device. The processing device can perform operations including determining a value of a data state metric of a memory page, wherein the data state metric value is reflective of a number of bit errors associated with the memory page; upon determining that the data state metric value satisfies a first threshold criterion, obtaining, from a neural network, a value of a voltage distribution metric associated with the page; and upon determining that the voltage distribution metric value satisfies a second threshold criterion, performing a media management operation with respect to a block associated with the page, wherein the media management operation comprises writing data stored at the block to a new block.

Data integrity checks based on voltage distribution metrics

Systems and methods are disclosed including a memory device and a processing device operatively coupled to the memory device. The processing device can perform operations comprising performing a data integrity check on a source set of memory cells, configured to store a first number of bits per memory cell, to obtain a data integrity metric value; responsive to determining that the data integrity metric value satisfies the threshold criterion, performing an error handling operation on the data stored on the source set of memory cells to generate corrected data; and causing the memory device to copy data the corrected data to a destination set of memory cells of the memory device, wherein the destination set of memory cells are configured to store a second number of bits per memory cell, wherein the second number of bits per memory cells is greater than the first number of bits per memory cell.

Memory compaction management in memory devices

An example memory sub-system includes a memory device and a processing device, operatively coupled to the memory device. The processing device is configured to initialize a block family associated with a memory device; initialize a timeout associated with the block family; initializing a low temperature and a high temperature using a reference temperature at the memory device; responsive to programming a block residing on the memory device, associate the block with the block family; and responsive to at least one of: detecting expiration of the timeout or determining that a difference between the high temperature and the low temperature is greater than or equal to a specified threshold temperature value, close the block family.

Block family-based error avoidance for memory devices

A system includes a memory device containing multiple dies that each have multiple pages, and a processing device, operatively coupled with the memory device, to perform various operations including scanning a group of pages residing on a die and determining a value of one data state metric and a corresponding value of another state metric. The operations can also include recording a set of values of the first metric and a corresponding set of values of the second metric, as well as calculating the value of the second metric corresponding to a predetermined value of the first metric associated with a failure condition of the die. Additionally, the operations can include identifying a particular criterion that is satisfied by the calculated value, assigning, to the die, a rating corresponding to the identified criterion, and performing scans on the die at a frequency determined by the assigned rating.

Host data storage scan data retention rating

Systems and methods are disclosed including a memory device and a processing device operatively coupled to the memory device. The processing device can perform operations comprising determining a data validity metric value with respect to a set of memory cells of the memory device; responsive to determining that the data validity metric value satisfies a first threshold criterion, performing a data integrity check on the set of memory cells to obtain a data integrity metric value; and responsive to determining that the data integrity metric value satisfies a second threshold criterion, performing an error handling operation on the data stored on the set of memory cells to generate corrected data.

Performing selective copyback in memory devices

A processing device in a memory sub-system monitors a temperature associated with a block of a memory device, the block comprising a plurality of wordlines. The processing device further determines a first amount of time between when memory cells associated with a first wordline of the plurality of wordlines of the block were written and when memory cells associated with a last wordline of the plurality of wordlines of the block were written. That first amount of time is normalized according to the temperature associated with the block. The processing device further determines, based at last in part on the first amount of time and on an associated scaling factor, an estimate of when the block will reach a uniform charge loss state.

Temperature-compensated time estimate for a block to reach a uniform charge loss state

Methods, systems, and devices for a model for predicting memory system performance are described. A memory system may generate a set of read commands and perform a first set of read operations at a memory device according to the generated read commands. The memory system may generate information indicating a performance of the memory device based on the first set of read operations and may update one or more coefficients of a model that correlates the information with a change in a read window. In some cases, the memory system may model the change in a read window based on the information and update one or more parameters associated with read operations based on the modelled change in the read window. The memory system may perform a second set of read operations at the memory device using the one or more updated parameters.

Model for predicting memory system performance

A processing device in a memory sub-system detects an occurrence of a triggering event, determines respective levels of charge loss associated with a first representative wordline of a block of a memory device and with a second representative wordline of the block of the memory device, and determines whether a difference between the respective levels of charge loss satisfies a threshold criterion. Responsive to determining that the difference between the respective levels of charge loss satisfies the threshold criterion, the processing device further determines that the block is in a uniform charge loss state.

Measurement of representative charge loss in a block to determine charge loss state

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San Jose, CA, United States of America

Vamsi Pavan Rayaprolu