Abstract: Systems and techniques relating to fault tolerant data storage in storage devices, such as storage devices that employ Shingled Magnetic Recording (SMR) and/or storage devices that employ solid state memory, include a method, in some implementations, including: receiving, at a storage controller, a data request for a storage device; reading, in response to the data request, data from discrete units of storage in the storage device, the data comprising stored data read from two or more of the discrete units of storage and parity data read from at least one of the discrete units of storage; detecting an error in the stored data from the reading; and recovering stored data for at least one of the discrete units of storage using the parity data and the stored data read from one or more remaining ones of the two or more of the discrete units of storage.

Abstract: Monitors, architectures, systems and methods for determining one or more quality characteristics of a storage channel. The monitor generally includes an iterative decoder configured to decode data from the storage channel and generate information relating to a quality metric of the storage channel and/or the iterative decoder, a memory configured to store a threshold value for the quality metric, and a comparator configured to compare the threshold value with a measured value of the quality metric. The monitor enables accurate determination of storage channel quality without use of conventional Reed-Solomon metrics.

Abstract: Systems and methods are provided for decoding data stored on a storage device. A decoding method is described for retrieving data from the storage device, wherein the retrieved data are encoded using a product code having a first dimension and a second dimension. The decoding method includes processing at least one codeword from the first dimension to form detector soft information, decoding the at least one codeword from the first dimension based on the detector soft information to form a first decoder soft information, and decoding at least one codeword from the second dimension based on the first decoder soft information to form a second decoder soft information.

Abstract: Systems and methods are provided for enhancing the performance and throughput of a low-density parity check (LDPC) decoder. In some embodiments, the enhanced performance and throughput may be achieved by detecting and correcting near-codewords before the decoder iterates up to a predetermined number of iterations. In some embodiments, a corrector runs concurrently with the decoder to correct a near-codeword when the near-codeword is detected. In alternate embodiments, the corrector is active while the decoder is not active. Both embodiments allow for on-the-fly codeword error corrections that improve the performance (e.g., reducing the number of errors) without decreasing the throughput of the decoder.

Abstract: Systems, methods, and other embodiments associated with LDPC decoder architectures are described. According to one embodiment, a method includes decoding codeword bits with a high throughput LDPC decoder and when the decoding of the codeword bits with the high throughput LDPC decoder is unsuccessful, decoding the codeword bits with a low throughput LDPC decoder.

Abstract: In iterative decoding, a data recovery scheme corrects for corrupted or defective data by determining reliability metrics for blocks of decoded data. Block or windowed detectors generate block reliability metrics for data blocks (rather than individual bits) of decoded data using soft information from the regular decoding mode or from new iterative decoding iterations performed during error recovery mode. An error recovery system triggers corrective decoding of selected data blocks based on the block reliability metrics, by for example, comparing the block reliability metrics to a threshold or by selecting an adjustable number of the least reliable data blocks.

Abstract: Systems and methods are provided for encoding data based on an LDPC code using various inversion mechanisms to obtain parity bits. In some embodiments, an LDPC encoder may compute parity bits using a speculative recursion and correction mechanism. In these embodiments, the LDPC encoder may initiate a recursion using at least one speculative value in place of the actual value for a parity component. The speculative values may then be corrected using a correction factor. In other embodiments, an LDPC encoder is provided that can perform a blockwise inversion mechanism. This mechanism may be used on LDPC codes with parity check matrices having a parity portion composed partially of a large triangular matrix. In still other embodiments, a generic LDPC encoder is provided. The generic LDPC encoder can implement a variety of different encoding techniques, such as different inversion mechanisms, and may be processor-based or finite state machine-based.

Abstract: Systems and techniques relating to fault tolerant data storage in storage devices, such as storage devices that employ Shingled Magnetic Recording (SMR) and/or storage devices that employ solid state memory, include a method, in some implementations, including: receiving, at a storage controller, a data request for a storage device; reading, in response to the data request, data from discrete units of storage in the storage device, the data comprising stored data read from two or more of the discrete units of storage and parity data read from at least one of the discrete units of storage; detecting an error in the stored data from the reading; and recovering stored data for at least one of the discrete units of storage using the parity data and the stored data read from one or more remaining ones of the two or more of the discrete units of storage.

Abstract: An error correction system includes an iterative code that employs an interleaved component code and an embedded parity component code. In some embodiments, on the transmission side, input signals received at an input node are encoded based on the interleaved code, which encodes an interleaved version of the input data to produce a first set of codewords. At least a portion of the first set of codewords preferably is divided into a plurality of symbols which are encoded based on the embedded parity code to provide encoded data. Similarly, in some embodiments, on the receiving side, received data are detected to produce detected information and soft outputs. The detected information is decoded based on the embedded parity code to obtain decoded information. The decoded information preferably is used, together with other soft information, by an interleaved decoder to generate reliability metrics for biasing a subsequent decoding iteration.

Abstract: Systems, methods, and other embodiments associated with LDPC decoder architectures are described. According to one embodiment, an apparatus includes a super-parity-check matrix corresponding to at least a portion of a low density parity check (LDPC) code matrix. The super-parity-check-matrix is configured to operate with nx check node processing elements (NPEs) and ny bit NPEs. The super-parity-check matrix includes a plurality of parity check matrices. Each parity check matrix is configured to operate with x check NPEs and y bit NPEs. The numbers n, x, and y, are selected such that ny codeword bits are processed in the single time unit by a high throughput decoder and y codeword bits are processed in the single time unit by a low throughput decoder.

Abstract: Systems and methods are provided for decoding data. A decoder includes a syndrome memory, a state memory, and decoding circuitry communicatively coupled to the syndrome memory and the state memory. The decoding circuitry retrieves data related to a symbol from the syndrome memory. The decoding circuitry also retrieves data related to the symbol from the state memory. The decoding circuitry processes the data retrieved from the syndrome memory and the data retrieved from the state memory to determine whether to toggle a value of the symbol. The determination is based at least in part on whether the symbol of the data being decoded was previously toggled from an original state.

Abstract: This disclosure relates generally to low power data decoding, and more particularly to low power iterative decoders for data encoded with a low-density parity check (LDPC) encoder. Systems and methods are disclosed in which a low-power syndrome check may be performed in the first iteration or part of the first iteration during the process of decoding a LDPC code in an LDPC decoder. Systems and methods are also disclosed in which a control over the precision of messages sent or received and/or a change in the scaling of these messages may be implemented in the LDPC decoder. The low-power techniques described herein may reduce power consumption without a substantial decrease in performance of the applications that make use of LDPC codes or the devices that make use of low-power LDPC decoders.

Abstract: Systems and methods for power efficient iterative equalization on a channel are provided. An iterative decoder decodes received data from a channel detector using a decoding process. The decoder computes a decision metric based on the decoded data and adjusts the number of iterations of the decoding process based on the decision metric. The adjustment occurs prior to a reliability criterion for the decoded data being satisfied. The decoder may pass control back to the channel detector if the adjusted number of iterations has occurred or if the reliability criterion is satisfied. Adjusting the number of iterations of the decoding process may include increasing the number of iterations from a predetermined number of iterations. The decision metric may be based on syndrome weight or hard decisions. The decision metric may be chosen to reduce average power consumption of the detector, the decoder, or circuitry including the detector and the decoder.

Abstract: Systems and techniques relating to storage devices, such as storage devices that employ Shingled Magnetic Recording (SMR), can include a device, which includes: circuitry configured to write stored data and parity data to discrete portions of a Shingled Magnetic Recording (SMR) track in a SMR storage device; and circuitry configured to recover stored data for one of the discrete portions of the SMR track using the parity data and the stored data read from remaining ones of the discrete portions of the SMR track.

Abstract: Systems and methods are provided for decoding data using hard decisions and soft information. In particular, the systems and methods described herein are directed to decoders having variable nodes and check nodes, each with multiple states. The systems and methods include receiving, at a decoder during a first iteration, values for each of a plurality of variable nodes, and determining, during a second iteration, one or more indications for each of a plurality of check nodes based on the one or more values of the variable nodes received during the first iteration. The methods further include updating, at the decoder during the second iteration, the values for each of the variable nodes based on the values of the respective variable node received during the first iteration, and the indications for each of the plurality connected check nodes during the first iteration.

Abstract: Systems and methods are provided for improved designs and performance for iterative decoder systems. In some embodiments, the iterative decoder may be decoupled from FIR samples through an FIR RAM, thus resulting in a less complex design and shorter processing times. In some embodiments, an intermediate memory may be used when passing information between the SOVA and LDPC of the iterative decoder. In some embodiments, the SOVA-required information may be continuously serialized from information received from the LDPC during each LDPC iteration. In some embodiments, the 1/(1+D2) precoder of the HR RLL encoder may be split into two serial, 1/(1+D) precoders. One 1/(1+D) precoder may be pulled outside of the HR RLL encoder and used in conjunction with the iterative decoder. A 1/(1+D) precoder may be used with the iterative decoder while maintaining the RLL constraints imposed upon the encoded information by the HR RLL encoder.

Abstract: Systems and methods are provided for decoding data using hard decisions and erasures. Circuitry receives data from each of a plurality of variable nodes which correspond to bits of data being decoded. Each variable node stores one of at least three values. The circuitry determines processes the values received from the plurality of variable nodes according to a set of processing rules. The processing rules are used to determine a condition related to the values stored by the plurality of variable nodes. The circuitry stores an indication of the stored condition at a check node.

Abstract: Methods and apparatuses are provided for decoding a codeword using an iterative decoder. The iterative decoder, in a first decoding mode, performs a number of channel iterations on the codeword, determines a first syndrome weight after a first time period, and determines a second syndrome weight after a second time period. Each channel iteration includes an iteration of the channel detector and at least one iteration of the inner iterative decoder. The iterative decoder, in a second decoding mode, determines a true syndrome of the codeword, and processes the codeword based on the true syndrome of the codeword. The codeword is processed using the second decoding mode in response to determining that the first and second determined syndrome weights are less than a syndrome weight threshold.

Abstract: Systems and methods for storing data on a storage device are disclosed. Data for storage to one of a plurality of tracks of the storage device is received. Each of the plurality of tracks includes a plurality of sectors. The received data is encoded using a track level code. The track level code encodes multiple of the plurality of sectors of the one of the plurality of tracks. The encoded data is stored to the one of the plurality of tracks of the storage device.

Abstract: In one embodiment a data decoding apparatus includes first and second decoding blocks configured to decode codeword bits in a first mode determined by a first probability of non-standard errors and a second mode determined by a second probability of non-standard errors. The apparatus also includes a mode modification logic configured to cause at least one of the first and second decoding blocks to operate in the second mode when the first and second decoding blocks fail to decode the codeword bits in the first mode. In another embodiment, a method includes decoding codeword bits in a first mode determined by a first probability of non-standard errors. When decoding the codeword bits in the first mode fails to decode the codeword bits, the codeword bits are decoded in a second mode determined by a second probability of non-standard errors.