A method, a system, and a computer program product for decompressing data. One or more compressed blocks in a set of stored compressed blocks responsive to a request to access data in the set of stored compressed blocks are identified. String prefixes inside the identified compressed blocks are decompressed using front coding. String suffixes inside the identified compressed blocks are decompressed using a re-pair decompression. Uncompressed data is generated.

A method for adjustable error correction in a storage cluster is provided. The method includes determining health of a non-volatile memory of a non-volatile solid-state storage unit of each of a plurality of storage nodes in a storage cluster on a basis of per flash package, per flash die, per flash plane, per flash block, or per flash page. The determining is performed by the storage cluster. The plurality of storage nodes is housed within a chassis that couples the storage nodes as the storage cluster. The method includes adjusting erasure coding across the plurality of storage nodes based on the health of the non-volatile memory and distributing user data throughout the plurality of storage nodes through the erasure coding. The user data is accessible via the erasure coding from a remainder of the plurality of storage nodes if any of the plurality of storage nodes are unreachable.

A subspace pursuit apparatus for compressive sensing reconstruction includes: a first inner product unit configured to calculate a correlation between a residual vector and column vectors of a sensing matrix by calculating an inner product of them; a first sorting unit coupled to the first inner product unit and configured to select K column vector indices having highest correlations, where K is a sparsity level; a second inner product unit configured to calculate a matrix for calculating a pseudo-inverse matrix required for solving a least-squares from the sensing matrix to store in the Gram matrix buffer; a Cholesky inversion unit configured to perform a Cholesky decomposition of the matrix stored in the Gram matrix buffer and calculate an inverse of a decomposed matrix; and a sparse solution estimator configured to estimate the sparse solution from a matrix value of the matrix based on the inverse of the decomposed matrix.

A data processing system includes a storage medium, and a controller including a data processing block, configured to receive data from a host, transmit the received data to the storage medium, read data from the storage medium in response to a read request from the host, and decode the read data by the data processing block according to multiple decoding modes. The data processing block includes a first decoder and a second decoder, and is configured to manage the first decoder and the second decoder to run the decoding for the read data, and activate a fast decoding having shorter latency than a normal decoding after a fast decoding condition is satisfied.

A method includes writing sets of encoded data slices to storage units of a storage network in accordance with error encoding parameters, where for a set of encoded data slices, the error encoding parameters include an error coding number and a decode threshold number, the error coding number indicates a number of encoded data slices that results when a data segment is encoded using an error encoding function and the decode threshold number indicates a minimum number needed to recover the data segment. The method further includes monitoring processing of the writing the sets of encoded data slices to produce write processing performance information. When the write processing performance information compares unfavorably to a desired write performance range, the method further includes adjusting at least one of the error coding number and the decode threshold number to produce adjusted error encoding parameters for writing subsequent encoded data slices.

A method, a system, and a computer program product for decompressing data. One or more compressed blocks in a set of stored compressed blocks responsive to a request to access data in the set of stored compressed blocks are identified. String prefixes inside the identified compressed blocks are decompressed using front coding. String suffixes inside the identified compressed blocks are decompressed using a re-pair decompression. Uncompressed data is generated.

Embodiments provide a transfer method for wirelessly transferring data in a communication system (e.g. a sensor network or telemetry system). The data includes core data and extension data, wherein the core data is encoded and distributed in an interleaved manner to a plurality of core sub-data packets, wherein the extension data is encoded and distributed in an interleaved manner to a plurality of extension sub-data packets, wherein at least a part of the core data contained in the core sub-data packets is needed for receiving the extension data or extension data packets.

A memory system includes an encoder and a decoder. The encoder is configured to generate multi-dimensionally-coded data to be written into the non-volatile memory. Data bits of the multi-dimensionally-coded data are grouped into first and second dimensional codes with respect to first and second dimensions, respectively. The decoder is configured to, with respect to each of the first and second dimensional codes included in read multi-dimensionally-coded data, generate a syndrome value of the dimensional code, generate low-reliability location information, generate a soft-input value based on the syndrome value and the low-reliability location information, decode the dimensional code through correction of the dimensional code using the soft-input value, and store modification information indicating a bit of the dimensional code corrected through the correction and reliability information indicating reliability of the correction. The decoder generates the soft-input value also based on the modification information and the reliability information in the memory.

Methods and systems for decoding raw data may include determining a sequence of a plurality of read-level voltages based on previous decoding data and executing a multi-stage decoding operation to decode raw data read from the plurality of memory cells using the determined sequence of the plurality of read-level voltages. Decoded data is returned from the multi-stage decoding operation upon completion of the multi-stage decoding operation and the previous decoding data is updated based on results of the multi-stage decoding operation.

A method includes acquiring, by a managing unit of a dispersed storage network (DSN), storage unit status information and data object storage status information from a plurality of storage units of DSN memory of the DSN. The method further includes determining, by the managing unit, DSN status information of the DSN memory based on the storage unit status information and the data object storage status information. The method further includes identifying, by the managing unit, DSN memory issues within the DSN memory. The method further includes prioritizing, by the managing unit, corrective remedies for the DSN memory issues based on the status information of the DSN memory. The method further includes facilitating, by the managing unit, the execution of the prioritized corrective remedies to correct the DSN memory issues.