Abstract: Disclosed herein are memory devices, systems, and methods of encoding and decoding data. In one aspect, an encoded data chunk is received and segmented into data segments with similar features. Each segment can be decoded based on its features. Data can also be rearranged and partitioned so as to minimize an entropy score that is based on the size and entropy of the data partitions. The approach is capable of enhancing performance, reducing decoding latency, and reducing power consumption.

Abstract: A method and apparatus for obtaining data from a memory, estimating a probability of data values of the obtained data based on at least one of a source log-likelihood ratio and a channel log-likelihood ratio, wherein each bit in the obtained data has an associated log-likelihood ratio, determining at least one data pattern parameter for the data and performing a decoding process using the at least one data pattern parameters to determine a decoded data set.

Abstract: A method and apparatus for obtaining data from a memory, estimating a probability of data values of the obtained data based on at least one of a source log-likelihood ratio and a channel log-likelihood ratio, wherein each bit in the obtained data has an associated log-likelihood ratio, determining at least one data pattern parameter for the data and performing a decoding process using the at least one data pattern parameters to determine a decoded data set.

Abstract: A method and apparatus for obtaining data from a memory, estimating a probability of data values of the obtained data based on at least one of a source log-likelihood ratio and a channel log-likelihood ratio, wherein each bit in the obtained data has an associated log-likelihood ratio, determining at least one data pattern parameter for the data and performing a decoding process using the at least one data pattern parameters to determine a decoded data set.

Abstract: Disclosed herein are memory devices, systems, and methods of content-aware decoding of encoded data. In one aspect, an encoded data chunk is received and one or more characteristics, such as source statistics, are determined. A similar data chunk (that may, e.g., contain data of a similar type) with comparable statistics may be sought. The similar data chunk may, for example, have source statistics that are positively correlated to the source statistics of the encoded data chunk to be decoded. Decoder parameters for the encoded data may be set to correspond with decoder parameters suited to the similar data chunk. The encoded data chunk is decoded using the new decoder parameters. Decoding encoded data based on content can enhance performance, reducing decoding latency and/or power consumption.

Abstract: A data storage device includes a non-volatile memory and a controller coupled to the non-volatile memory. The controller is operable to measure a first threshold voltage (Vt) of a memory cell under a first parameter at a read temperature and measure a second Vt of the memory cell under a second parameter at the read temperature in which the first parameter is different from the second parameter. A Vt correction term for the memory cell is determined based upon the first Vt measurement and the second Vt measurement. A read Vt of the memory cell is adjusted by using the Vt correction term.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for seed generation. An apparatus includes a memory element. An apparatus includes a scrambler component. A scrambler component includes a random seed generation circuit that generates a random seed. A scrambler component includes a deterministic seed generation circuit that generates a deterministic seed based on a physical address of a memory element for storing data. A scrambler component includes a computation circuit that forms a computed seed based on a random seed and a deterministic seed. Data is scrambled using a computed seed before data is stored.

Abstract: A method and apparatus for obtaining data from a memory, estimating a probability of data values of the obtained data based on at least one of a source log-likelihood ratio and a channel log-likelihood ratio, wherein each bit in the obtained data has an associated log-likelihood ratio, determining at least one data pattern parameter for the data and performing a decoding process using the at least one data pattern parameters to determine a decoded data set.

Abstract: A storage device may include a decoder configured to connect bits to a content node based on content-aware decoding process. The content-aware decoding process may be dynamic and determine connection structures of bits and content nodes based on patterns in data. In some cases, the decoder may connect non-adjacent bits to a content node based on a content-aware decoding process. In other cases, the decoder may connect a first number of bits to a first content node and a second number of bits to a second content node. In such cases, the first number of bits and the second number of bits are a different number.

Abstract: A data storage device includes a non-volatile memory and a controller coupled to the non-volatile memory. The controller is operable to measure a first threshold voltage (Vt) of a memory cell under a first parameter at a read temperature and measure a second Vt of the memory cell under a second parameter at the read temperature in which the first parameter is different from the second parameter. A Vt correction term for the memory cell is determined based upon the first Vt measurement and the second Vt measurement. A read Vt of the memory cell is adjusted by using the Vt correction term.

Abstract: A device includes a memory and a controller coupled to the memory. The controller is configured to determine a temperature-based value of a search parameter in response to detecting that an error rate of a codeword read from the memory exceeds a threshold error rate. The controller is further configured to iteratively modify one or more memory access parameters associated with reducing temperature-dependent threshold voltage variation and to re-read the codeword using the modified one or more memory access parameters.

Abstract: A non-volatile storage apparatus includes a set of non-volatile memory cells, one or more control circuits in communication with the set of non-volatile memory cells, the one or more control circuits are configured to encode data with a code rate prior to storage in the set of non-volatile memory cells, the code rate selected from two or more code rates according to one or more predictive indicators received with the data, the one or more predictive indicators relating to expected conditions for storage of the data in the set of non-volatile memory cells.

Abstract: Systems and methods are described for reducing error rates on data storage devices by applying data shaping to data written to such devices in order to avoid error-prone states on cells within the devices. Different states of individual cells (such as those representing different bit patterns) may have different propensities for error, and these propensities may vary during operation of a device. Thus, a device as disclosed herein may determine error-prone states for a cell or group of cells, and apply data shaping to data written to such cells to reduce the likelihood that writing the data places the cell or cells into an error-prone state. Data shaping may be used, for example, to increase the occurrence of “0” bits within input data, thus avoiding error-prone low voltage states that may be used to represent a series of “1” bits.

Abstract: 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.

Abstract: Technology is described herein for learning parameters for a parameterized iterative message passing decoder, and to a corresponding parameterized iterative message passing decoder. Learning the parameters may adapt the decoder to statistical dependencies introduced by the specific code's graph. Taking into account the statistical dependencies may allow the code to be shorter and/or denser. Note that the statistical dependencies in the graph may be extremely complex. Machine learning may be used to learn the parameters. The parameters may be learned when decoding data stored in the memory device. Learning the parameters may adapt the decoder to properties of data stored in the memory device, physical properties of the memory device, and/or patterns in host data.

Abstract: A method of operation of a data storage device includes inputting data to a decoder of the data storage device. The method further includes sending a command to a memory of the data storage device in response to an indication of a pipeline delay associated with a decoding process to decode the data. The command indicates an operation to be performed at the memory to in response to the pipeline delay.

Abstract: 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.

Abstract: 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.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for seed generation. An apparatus includes a memory element. An apparatus includes a scrambler component. A scrambler component includes a random seed generation circuit that generates a random seed. A scrambler component includes a deterministic seed generation circuit that generates a deterministic seed based on a physical address of a memory element for storing data. A scrambler component includes a computation circuit that forms a computed seed based on a random seed and a deterministic seed. Data is scrambled using a computed seed before data is stored.

Abstract: A device includes a non-volatile memory, a traffic analyzer, and a parameter adjuster. The traffic analyzer is configured to generate a traffic type indicator based on one or more read requests from an access device to access data at the non-volatile memory. The traffic type indicator has a first value responsive to the one or more read requests corresponding to a first traffic type and has a second value responsive to the one or more read requests corresponding to a second traffic type. The parameter adjuster is configured to designate one or more decode parameter values based on the traffic type indicator.