Sandisk Technologies Inc.

Western Digital Technologies, Inc.

Idan Goldenberg

Eran Sharon

Alexander Bazarsky

Ran Zamir

Idan Alrod

Rami Rom

Stella Achtenberg

Ishai Ilani

Ariel Navon

Dudy David Avraham

Karin Inbar

Nian Niles Yang

Omer Fainzilber

Philip David Reusswig

Yan Dumchin

Yuri Ryabinin

Roi Kirshenbaum

Eyal Sobol

Michael Micha Ionin

Mark Fiterman

Eran Banani

Martin Booth

Didi Gur

Igal Mariasin

A storage system generates a low-density parity check (LDPC) code from a plurality of subcodes. The storage system stores each subcode in a different page of a word line in the memory. The subcode can be stored in one plane in the memory or across multiple planes. When the subcodes are stored across multiple planes, they can be stored in a checkboard pattern.

Storage system and method for using subcodes and convolutional-based LDPC interleaved coding schemes with read threshold calibration support

Calibration of soft bit reference levels in a non-volatile memory system is disclosed. A set of memory cells are sensed at a hard bit reference level and test soft bit reference levels. The test soft bit reference levels are grouped around the hard bit reference level. A metric is determined for the test soft bit reference levels. Bins are defined based on the hard bit reference level and the set of test soft bit reference levels. A metric may be determined for each of the bins. The new soft bit reference levels are determined based on the metric. In one aspect, the metric is how many memory cells have a value for a physical parameter within each bin. The soft bit reference levels may be established based on a target percentage for the bins. In one aspect, the metric is how many unsatisfied counters are within each bin.

Soft bit reference level calibration

An error correcting code (ECC) decoder for a non-volatile memory device is configured to decode data stored by the non-volatile memory device using a parity check matrix with columns of different column weights. The ECC decoder is further configured to artificially slow processing of one or more of the columns of the parity check matrix in response to column weights for the one or more columns satisfying a threshold.

Decoder for irregular error correcting codes

A method for punctured bit estimation includes receiving a punctured codeword. The method further includes generating a reconstructed codeword using the punctured codeword and at least one punctured bit having a default logic value. The method further includes generating a syndrome vector for the reconstructed codeword. The method further includes determining, using the syndrome vector, a number of unsatisfied parity-checks for the at least one punctured bit. The method further includes determining, for the at least one punctured bit, a bit value using, at least, the number of unsatisfied parity-checks associated with the at least one punctured bit.

Punctured bit estimation and bit error rate estimation

In an illustrative example, a method includes sensing at least a portion of a representation of a convolutional low-density parity-check (CLDPC) codeword stored at a memory of a data storage device. The method further includes receiving the portion of the representation of the CLDPC codeword at a controller of the data storage device. The method further includes performing one or more management operations associated with the memory based on an estimated number of errors of the portion of the representation of the CLDPC codeword.

Method and data storage device to estimate a number of errors using convolutional low-density parity-check coding

In an illustrative example, an apparatus includes a controller and a memory that is configured to store a codeword of a convolutional low-density parity-check (CLDPC) code. The codeword has a first size and includes multiple portions that are independently decodable and that have a second size. The controller includes a CLDPC encoder configured to encode the codeword and a CLDPC decoder configured to decode the codeword or a portion of the codeword.

Method and data storage device using convolutional low-density parity-check coding with a long page write and a short page read granularity

A black box recorder for an autonomous vehicle includes an interface configured to receive data from an engine control unit (ECU) device. The data includes first data and second data. The black box recorder further includes an error correction code (ECC) engine configured to determine a first parity size associated with the first data based on a characteristic of the first data and a second parity size associated with the second data based on a characteristic of the second data. The first parity size is different than the second parity size. The ECC engine is further configured to generate a convolutional low-density parity-check (CLDPC) codeword that includes the first data, the second data, first redundancy data associated with the first data, and second redundancy data associated with the second data. The first redundancy data has the first parity size, and the second redundancy data has the second parity size.

Variable length CLDPC encoder and method of operation in an autonomous vehicle

In an illustrative example, a method includes receiving data to be processed in accordance with a convolutional low-density parity-check (CLDPC) code. The method also includes processing the data based on a parity check matrix associated with the CLDPC code. The parity check matrix includes a first portion and a second portion. The first portion includes a plurality of copies of a first sub-matrix that is associated with a first sub-code, and the second portion includes a copy of second sub-matrix that is associated with a second sub-code.

Convolutional low-density parity-check coding

A storage device may program data differently for different memory areas of a memory. In some embodiments, the storage device may use different codebooks for different memory areas. In other embodiments, the storage device may modify bit orders differently for different memory areas. What codebook the storage device uses or what bit order modification the storage device performs for a particular memory area may depend on the bad storage locations specific to that memory area. Where different codebooks are used, optimal codebooks may be selected from a library, or codebooks may be modified based on the bad storage locations of the memory areas.

Use of multiple codebooks for programming data in different memory areas of a storage device

Systems and methods are described for compacting operating parameter sets in a data storage device. Data storage device may be configured to maintain multiple operating parameter sets, each of which stores various parameters for interacting with different memory elements within the device. The data storage device may further be limited in the total number of operating parameter sets that can be maintained in the device at any given time. Thus, the data storage device may be required at various times to combine two or more operating parameter sets, to enable creation of a new operating parameter set. Because each operating parameter set can contain a number of parameters, identification of similar sets for combination can be computationally intensive. To identify similar sets in an efficient manner, a device as disclosed herein is enabled to reduce a dimensionality of each set, and locate similar sets under that reduced dimensionality.

Compacting operating parameter groups in solid state memory devices

Systems and methods are described for generating location-based read voltage offsets in a data storage device. Optimal read voltage thresholds vary across memory elements of a device. However, data storage devices are often limited in the number of read voltage thresholds that can be maintained in the device. Thus, it may not be possible to maintain optimal read voltage parameters for each memory element within a device. The systems and methods described herein provide for increased accuracy of read voltage thresholds when applied to memory elements within a specific location in a device, by enabling the use of location-based read voltage offsets, depending on a relative location of the memory element being read from. The read voltage offsets can be determined based on application of a neural network to data regarding optimal read voltage thresholds determined from at least a sample of memory elements in a device.

Operating parameter offsets in solid state memory devices

Bit-order modification for different memory areas of a storage device

Determining codebooks for different memory areas of a storage device

A device includes a low density parity check (LDPC) decoder that configured to receive a representation of a codeword. The LDPC decoder includes a message memory configured to store decoding messages, multiple data processing units (DPUs), a control circuit, and a reording circuit. The control circuit is configured to enable a first number of the DPUs to decode the representation of the codeword in response to a decoding mode indicator indicating a first decoding mode and to enable a second number of the DPUs to decode the representation of the codeword in response to the decoding mode indicator indicating a second decoding mode. The reordering circuit is configured to selectively reorder at least one of the decoding messages based on the decoding mode indicator.

ECC decoder with multiple decoding modes

A device includes a memory and a controller coupled to the memory. The controller is configured to determine a first count of bits of a representation of data that are estimated to be erroneous and a second count of bits of the representation of data that have high estimated reliability and are estimated to be erroneous. The controller is further configured to modify at least one read parameter or at least one decode parameter based on the first count and the second count.

Growing community of inventors

Ramat Hasharon, Israel

Idan Goldenberg