Abstract: The present disclosure relates to a system for executing a plurality of service requests (SRs) from corresponding plurality of user computing devices, the system comprising a distributed compute (DC) that forms part of a distributed network, the DC having at least one processor that executes one or more routines stored in an operatively coupled memory to enable receipt of the plurality of service requests in a heterogeneous interaction pool, wherein the DC further comprises a system state manager (SSM) that, based on at least one common attribute of each SR in the interaction pool, identifies an appropriate node (N) from one or more available nodes that has an ability and the attribute-based interest configuration to execute the respective SR, and transmits the respective SR to the identified node (N) for execution.

Abstract: A method includes obtaining, by a processing device, first data indicative of substrate generation parameters of a first substrate. The processing device further obtains second data indicative of properties of the first substrate. The processing device further obtains third data indicative of substrate generation parameters of a second substrate. The processing device further receives fourth data indicative of properties of the second substrate. The method further includes providing a user interface (UI). The UI includes a first UI element for presenting a visual depiction of the second data and a second UI element for presenting a visual depiction of the fourth data. The method further includes receiving user input of a classification of the first substrate and the second substrate. The method further includes performing analysis relating the first data and the third data to the user classifications. The method further includes performing a corrective action based on the analysis.

Abstract: A method includes receiving profile data of a plurality of features of a substrate. The method further includes generating a typical profile based on the profile data of the plurality of features. The method further includes generating a first array of features. Each of the first array of features is based on the typical profile. The method further includes providing the first array of features to a process model. The method further includes obtaining first output from the process model based on the first array of features. The method further includes causing performance of a corrective action in view of the first output from the process model.

Abstract: A method includes receiving, by a processing device, data indicative of a plurality of measurements of a profile of a substrate. The method further includes separating the data into a plurality of sets of data, a first set of the plurality of sets associated with a first region of the profile, and a second set of the plurality of sets associated with a second region of the profile. The method further includes fitting data of the first set to a first function to generate a first fit function. The first function is selected from a library of functions. The method further includes fitting data of the second set to a second function to generate a second fit function. The method further includes generating a piecewise functional fit of the profile of the substrate. The piecewise functional fit includes the first fit function and the second fit function.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. Bit patterns provided by multiple reads of reference memory locations can be counted and used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: The present disclosure relates to a system for executing a plurality of service requests (SRs) from corresponding plurality of user computing devices, the system comprising a distributed compute (DC) that forms part of a distributed network, the DC having at least one processor that executes one or more routines stored in an operatively coupled memory to enable receipt of the plurality of service requests in a heterogeneous interaction pool, wherein the DC further comprises a system state manager (SSM) that, based on at least one common attribute of each SR in the interaction pool, identifies an appropriate node (N) from one or more available nodes that has an ability and the attribute-based interest configuration to execute the respective SR, and transmits the respective SR to the identified node (N) for execution.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. Bit patterns provided by multiple reads of reference memory locations can be counted and used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. Bit patterns provided by multiple reads of reference memory locations can be counted and used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: A decoder is configured to perform, for a unit of data received by the decoder, a plurality of decoding iterations in which a plurality of messages are passed between a plurality of check nodes and a plurality of variable nodes, each message indicating a degree of reliability in an observed outcome of data. The decoder determines, for each of the plurality of decoding iterations, whether a trigger condition is satisfied based on an internal state of the decoder and, when a trigger condition is determined to be satisfied during a respective decoding iteration, scales one or more respective messages of the plurality of messages during a subsequent decoding iteration. The unit of data is decoded based on the plurality of decoding iterations and at least one scaled message resulting from the trigger condition being satisfied during the respective decoding iteration.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. Bit patterns provided by multiple reads of reference memory locations can be counted and used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. Bit patterns provided by multiple reads of reference memory locations can be counted and used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: A data storage device is disclosed comprising a storage medium. Input data is encoded according to at least one channel code constraint to generate first data and second data. The first data is encoded into a first codeword, and the second data is encoded into a second codeword, wherein a first code rate of the first codeword is less than a second code rate of the second codeword. The first codeword and the second codeword are interleaved to generate an interleaved codeword, and the interleaved codeword is written to the storage medium.

Abstract: A decoder is configured to perform, for a unit of data received by the decoder, a plurality of decoding iterations in which a plurality of messages are passed between a plurality of check nodes and a plurality of variable nodes, each message indicating a degree of reliability in an observed outcome of data. The decoder determines, for each of the plurality of decoding iterations, whether a trigger condition is satisfied based on an internal state of the decoder and, when a trigger condition is determined to be satisfied during a respective decoding iteration, scales one or more respective messages of the plurality of messages during a subsequent decoding iteration. The unit of data is decoded based on the plurality of decoding iterations and at least one scaled message resulting from the trigger condition being satisfied during the respective decoding iteration.

Abstract: A decoder is configured to perform, for a unit of data received by the decoder, a plurality of decoding iterations in which a plurality of messages are passed between a plurality of check nodes and a plurality of variable nodes, each message indicating a degree of reliability in an observed outcome of data. The decoder determines, for each of the plurality of decoding iterations, whether a trigger condition is satisfied based on an internal state of the decoder and, when a trigger condition is determined to be satisfied during a respective decoding iteration, scales one or more respective messages of the plurality of messages during a subsequent decoding iteration. The unit of data is decoded based on the plurality of decoding iterations and at least one scaled message resulting from the trigger condition being satisfied during the respective decoding iteration.

Abstract: A data storage device is disclosed comprising a storage medium. Input data is encoded according to at least one channel code constraint to generate first data and second data. The first data is encoded into a first codeword, and the second data is encoded into a second codeword, wherein a first code rate of the first codeword is less than a second code rate of the second codeword. The first codeword and the second codeword are interleaved to generate an interleaved codeword, and the interleaved codeword is written to the storage medium.

Abstract: A decoder is configured to perform, for a unit of data received by the decoder, a plurality of decoding iterations in which a plurality of messages are passed between a plurality of check nodes and a plurality of variable nodes, each message indicating a degree of reliability in an observed outcome of data. The decoder determines, for each of the plurality of decoding iterations, whether a trigger condition is satisfied based on an internal state of the decoder and, when a trigger condition is determined to be satisfied during a respective decoding iteration, scales one or more respective messages of the plurality of messages during a subsequent decoding iteration. The unit of data is decoded based on the plurality of decoding iterations and at least one scaled message resulting from the trigger condition being satisfied during the respective decoding iteration.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. Bit patterns provided by multiple reads of reference memory locations can be counted and used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: A data storage device is disclosed comprising a storage medium. Input data is encoded according to at least one channel code constraint to generate first data and second data. The first data is encoded into a first codeword, and the second data is encoded into a second codeword, wherein a first code rate of the first codeword is less than a second code rate of the second codeword. The first codeword and the second codeword are interleaved to generate an interleaved codeword, and the interleaved codeword is written to the storage medium.

Abstract: In some embodiments of the present invention, a data storage device includes a controller and a memory. The data storage device further includes an LDPC encoder and decoder, with the decoder implementing a dynamic precision-rescaling technique for improving performance. In one embodiment, the technique works by rescaling the binary representations of the input log-likelihood ratios (LLRs) and messages upon activation of decoder-state-based triggers. Various triggering functions are introduced, e.g., checking if the number of output LLRs smaller than a certain limit crosses a threshold, checking if the weight of a syndrome crosses a threshold, etc. This technique offers an improvement in the performance of the decoder.

Abstract: In one embodiment, an electronic system includes a decoder configured to decode an encoded data unit using multiple variable nodes and multiple check nodes to perform a low-density parity check (LDPC) decoding process. The encoded data unit can be received from a solid-state memory array. As part of performing the LDPC decoding process, the decoder can (i) convert reliability information representing first non-binary values to reliability information representing first binary values, (ii) determine reliability information representing second binary values using the reliability information representing first binary values, and (iii) convert the reliability information representing the second binary values to reliability information representing second non-binary values.