Abstract: A soft-decision decoding computes a first syndrome polynomial in accordance with a received word, computes a second syndrome polynomial by multiplying the first syndrome polynomial by a locator polynomial based on locations of erasures within the received word, finds a basis and private solution to an affine space of polynomials that solve key equations based on the second syndrome polynomial, determines a weak set of a locations of symbols in the received word with confidence below a certain confidence level, computes a matrix from the basis, the private solution and the weak set, determines sub-matrices in the matrix whose rank is equal to a rank of the matrix, determines error locator polynomial (ELP) candidates from the sub-matrices, the basis, and the private solution, and corrects the received word using a selected one of the ELP candidates.

Abstract: A processing circuit is configured to: construct a first locator polynomial for a Reed-Solomon codeword to identify locations of erasures in the Reed-Solomon codeword; determine a first syndrome of the Reed-Solomon codeword; calculate a first error evaluator polynomial from the first syndrome and the first locator polynomial; and perform error detection based on the first error evaluator polynomial to determine presence of errors in the Reed-Solomon codeword. When presence of errors in the Reed-Solomon codeword is not detected in the error detection, the processing circuit bypasses updating the first locator polynomial and proceeds to completing decoding of the Reed-Solomon codeword, but when presence of errors in the Reed-Solomon codeword is detected in the error detection, the system first updates the first locator polynomial to a second locator polynomial in a process with reduced complexity compared to the common one, before completing decoding of the Reed-Solomon codeword.

Abstract: A method of correcting data stored in a memory device includes: applying an iterative decoder to the data; determining a total number of rows in first data the decoder attempted to correct; estimating first visible error rows among the total number that continue to have an error after the attempt; estimating residual error rows among the total number that no longer have an error after the attempt; determining second visible error rows in second data of the decoder that continue to have an error by permuting indices of the residual error rows according to a permutation; and correcting the first data using the first visible error rows.

Abstract: A method of correcting data stored in a memory device includes: applying an iterative decoder to the data; determining a total number of rows in first data the decoder attempted to correct; estimating first visible error rows among the total number that continue to have an error after the attempt; estimating residual error rows among the total number that no longer have an error after the attempt; determining second visible error rows in second data of the decoder that continue to have an error by permuting indices of the residual error rows according to a permutation; and correcting the first data using the first visible error rows.

Abstract: A method of correcting data stored in a memory device includes: applying an iterative decoder to the data; determining a total number of rows in first data the decoder attempted to correct; estimating first visible error rows among the total number that continue to have an error after the attempt; estimating residual error rows among the total number that no longer have an error after the attempt; determining second visible error rows in second data of the decoder that continue to have an error by permuting indices of the residual error rows according to a permutation; and correcting the first data using the first visible error rows.

Abstract: Systems, devices, and methods for encoding information bits for storage, including encoding information bits and balance bits to obtain a first bit chunk of a first arrangement; permuting the first bit chunk to obtain a second bit chunk of a second arrangement; encoding the second bit chunk to obtain a third bit chunk of the second arrangement; permuting a first portion of the third bit chunk to obtain a fourth bit chunk of the first arrangement, and encoding the fourth bit chunk to obtain a fifth bit chunk of the first arrangement; permuting a second portion of the third bit chunk, and adjusting the balance bits based on the fifth bit chunk and the permutated second portion of the third bit chunk; adjusting the first arrangement based on the adjusted balance bits, and obtaining a codeword based on the adjusted first arrangement; and transmitting the codeword to a storage device.

Abstract: A method for Bose-Chaudhuri-Hocquenghem (BCH) soft error decoding includes receiving a codeword x, wherein the received codeword x has ?=t+r errors for some r?1; computing a minimal monotone basis {?i(x)}1?i?r+1?F[x] of an affine space V={?(x)?F[x]:?(x)·S(x)=??(x) (mod x2t), ?(0)=1, deg(?(x)?t+r}, wherein ?(x) is an error locator polynomial and S(x) is a syndrome; computing a matrix A?(?j(?i))i?[w],j?[r+1], wherein W={?1, . . . , ?w} is a set of weak bits in x; constructing a submatrix of r+1 rows from sub matrices of r+1 rows of the subsets of A such that the last column is a linear combination of the other columns; forming a candidate error locating polynomial using coefficients of the minimal monotone basis that result from the constructed submatrix; performing a fast Chien search to verify the candidate error locating polynomial; and flipping channel hard decision at error locations found in the candidate error locating polynomial.

Abstract: A method for Bose-Chaudhuri-Hocquenghem (BCH) soft error decoding includes receiving a codeword x, wherein the received codeword x has ?=t+r errors for some r?1; computing a minimal monotone basis {?i(x)}1?i?r+1?F[x] of an affine space V={?(x)?F[x]: ?(x)·S(x)=??(x) (mod x2t), ?(0)=1, deg(?(x)?t+r}, wherein ?(x) is an error locator polynomial and S(x) is a syndrome; computing a matrix A?(?j?i))i?[W],j?[r+1], wherein W={?i, . . . , ?W} is a set of weak bits in x; constructing a submatrix of r+1 rows from sub matrices of r+1 rows of the subsets of A such that the last column is a linear combination of the other columns; forming a candidate error locating polynomial using coefficients of the minimal monotone basis that result from the constructed submatrix; performing a fast Chien search to verify the candidate error locating polynomial; and flipping channel hard decision at error locations found in the candidate error locating polynomial.

Abstract: A hardware architecture for systematic erasure encoding includes first matrix constructor circuit that receives parity-check matrix H for codeword C, and the erased part of codeword C, and outputs matrix H1 of columns of H located on erased coordinates of code C; second matrix constructor circuit that receives matrix H and the erased part of codeword C and outputs matrix H2 of columns of H located on non-erased coordinates of code C; a neural network that calculates matrix J1 that is an approximate inverse of matrix H1. The matrix J1 is used to determine new erasures in the parity matrix H and new erased coordinates. Matrices H1 and H2 are updated, and the updated H1 is provided as feedback to the first matrix constructor circuit. A calculator circuit restores the erased coordinates of codeword C, from the matrix J1, matrix H2, and a non-erased part of codeword C.

Abstract: A method of performing division operations in an error correction code includes the steps of receiving an output ??F†{0} wherein F=GF(2r) is a Galois field of 2r elements, ?=?0?i?r?1?i×?i wherein ? is a fixed primitive element of F, and ?i?GF(2), wherein K=GF(2s) is a subfield of F, and {1, ?} is a basis of F in a linear subspace of K; choosing a primitive element ??K, wherein ?=?1+?×?2, ?1=?0?i?s?1 ?i×?i?K, ?2=?0?i?s?1 ?i+s×?i?K, and ?=[?0, . . . , ?r?1]T?GF(2)r; accessing a first table with ?1 to obtain ?3=?1?1, computing ?2×?3 in field K, accessing a second table with ?2=?3 to obtain (1+?×?2×?3)?1=?4+?×?5, wherein ??1=(?1×(1+?×?2×?3))?1=?3×(?4+?×?5)=?3×?4+?×?3×?5; and computing products ?3×?4 and ?3×?5 to obtain ??1=?0?i?s?1?i×?i+?·?i?i?s?1?i+s=?i where ?i?GF(2).

Abstract: A method of performing division operations in an error correction code includes the steps of receiving an output ??F†{0} wherein F=GF(2r) is a Galois field of 2r elements, ?=?0?i?r?1?i×?i wherein ? is a fixed primitive element of F, and ?i?GF(2), wherein K=GF(2s) is a subfield of F, and {1, ?} is a basis of F in a linear subspace of K; choosing a primitive element ??K, wherein ?=?1+?×?2, ?1=?0?i?s?1?i×?i?K, ?2=?0?i?s?1?i+s×?i?K, and ?=[?0, . . . , ?r?1]T?GF(2)r; accessing a first table with ?1 to obtain ?3=?1?1, computing ?2×?3 in field K, accessing a second table with ?2=?3 to obtain (1+?×?2×?3)?1=?4+?×?5, wherein ??1=(?1×(1+?×?2×?3))?1=?3×(?4+?×?5)=?3×?4+?×?3×?5; and computing products ?3×?4 and ?3×?5 to obtain ??1=?0?i?s?1?i×?i+?·?i?i?s?1?i+s=?i where ?i?GF(2).

Abstract: A method for repairing a single erasure in a Reed Solomon code in a system of a plurality of n storage nodes and a controller, wherein a content of each storage node is a codeword and each node stores a vector v. The method includes identifying a failed storage node; transmitting an index of the failed storage node to each surviving storage node; multiplying the content of each node i by a j-th component of a vector that is a permutation of elements of vector v that correspond to the surviving storage nodes; determining a trace map of the result and converting the result from an m×r bit representation into a reduced representation of r bits; reconstructing the content of the failed storage node from the reduced representation of each surviving node's content; and outputting the reconstructed content of the failed storage node.

Abstract: An application specific integrated circuit (ASIC) tangibly encodes a program of instructions executable by the integrated circuit to perform a method for fast Chase decoding of generalized Reed-Solomon (GRS) codes. The method includes using outputs of a syndrome-based hard-decision (HD) algorithm to find an initial Groebner basis G for a solution module of a key equation, upon failure of HD decoding of a GRS codeword received by the ASIC from a communication channel; traversing a tree of error patterns on a plurality of unreliable coordinates to adjoin a next weak coordinate, where vertices of the tree of error patterns correspond to error patterns, and edges connect a parent error pattern to a child error pattern having exactly one additional non-zero value, to find a Groebner basis for each adjoining error location; and outputting an estimated transmitted codeword when a correct error vector has been found.

Abstract: An application specific integrated circuit (ASIC) tangibly encodes a method for fast polynomial updates in fast Chase decoding of binary Bose-Chaudhuri-Hocquenghem (BCH) codes. The method includes the steps of using outputs of a syndrome-based hard-decision (HD) algorithm to find a Groebner basis for a solution module of a modified key equation, upon failure of HD decoding of a BCH codeword received by the ASIC from a communication channel; evaluating polynomials obtained from said Groebner basis at inverses of specified weak-bit locations; and transforming a Groebner basis for a set of flipped weak-bit locations (?1, . . . , ?r?1) to a Groebner basis for (?1, . . . , ?r), wherein ?r is a next weak-bit location, wherein r is a difference between a number of errors and a HD correction radius of the BCH codeword.

Abstract: A method of encoding generalized concatenated error-correcting codes includes providing a parity matrix {tilde over (H)}j of a j-th layer code and predefined syndrome {tilde over (s)} of length n?{tilde over (k)}j, where the first n-kl coordinates are zero, n is a length of a codeword c of a first layer BCH code Cl of dimension {tilde over (k)}j, codeword c satisfies {tilde over (H)}jc={tilde over (s)}, a first layer code includes only a BCH code, and each subsequent layer includes a Reed-Solomon (RS) stage followed by a BCH code; finding a square matrix R, of dimension (n?{tilde over (k)}j)(n?{tilde over (k)}j) such that Rj{tilde over (H)}j=(A|I), where A is an arbitrary matrix, Rj=(Qj|Tj), where Q has n?kl columns Tj and has k1?{tilde over (k)}j columns; finding a vector c?(a b) where a is a vector of length {tilde over (k)}j and b is a vector of length n?{tilde over (k)}j; and solving ( A | I ) ? ( a b ) = ( Q j | T j ) ? s ~ = T j ? s ? ? where ? ? a = 0 ?

Abstract: A method for generating a binary GTP codeword, comprised of N structure stages and each stage comprises at least one BCH codeword with error correction capability greater than a prior stage and smaller than a next stage, includes: receiving a syndrome vector s of a new stage 0 binary BCH codeword y over a field GF(2m) that comprises ?t syndromes of length m bits, wherein the syndrome vector s comprises l-th Reed-Solomon (RS) symbols of ?t RS codewords whose information symbols are delta syndromes of all BCH codewords from stage 0 until stage n?1; and multiplying s by a right submatrix ? of a matrix U, wherein U is an inverse of a parity matrix of an BCH code defined by tn, wherein the new binary BCH codeword is y=?·s.

Abstract: A method for repairing a single erasure in a Reed Solomon code in a system of a plurality of n storage nodes and a controller, wherein a content of each storage node is a codeword and each node stores a vector v. The method includes identifying a failed storage node; transmitting an index of the failed storage node to each surviving storage node; multiplying the content of each node i by a j-th component of a vector that is a permutation of elements of vector v that correspond to the surviving storage nodes; determining a trace map of the result and converting the result from an m×r bit representation into a reduced representation of r bits; reconstructing the content of the failed storage node from the reduced representation of each surviving node's content; and outputting the reconstructed content of the failed storage node.

Abstract: A method of encoding generalized concatenated error-correcting codes includes providing a parity Matrix {tilde over (H)}j of a j-th layer code and predefined syndrome {tilde over (s)} of length n?{tilde over (k)}j, where the first n?kl coordinates are zero, n is a length of a codeword c of a first layer BCH code Cl of dimension {tilde over (k)}j, codeword c satisfies {tilde over (H)}jc={tilde over (s)}, a first layer code includes only a BCH code, and each subsequent layer includes a Reed-Solomon (RS) stage followed by a BCH code; finding a square matrix Rj of dimension (n?{tilde over (k)}j)(n?{tilde over (k)}j) such that Rj{tilde over (H)}j=(A|I), where A is an arbitrary matrix, Rj=(Qj|Tj), where Q has n?kl columns and Tj has k1?{tilde over (k)} columns; finding a vector c=(a b) where a is a vector of length {tilde over (k)}j and b is a vector of length n?{tilde over (k)}j; and solving ( A | I ) ? ( a b ) = ( Q j | T j ) ? s ~ = T j ? s where a=0 and b=Tjs, and cod

Abstract: An application specific integrated circuit (ASIC) tangibly encodes a program of instructions executable by the integrated circuit to perform a method for fast Chase decoding of generalized Reed-Solomon (GRS) codes. The method includes using outputs of a syndrome-based hard-decision (HD) algorithm to find an initial Groebner basis G for a solution module of a key equation, upon failure of HD decoding of a GRS codeword received by the ASIC from a communication channel; traversing a tree of error patterns on a plurality of unreliable coordinates to adjoin a next weak coordinate, where vertices of the tree of error patterns correspond to error patterns, and edges connect a parent error pattern to a child error pattern having exactly one additional non-zero value, to find a Groebner basis for each adjoining error location; and outputting an estimated transmitted codeword when a correct error vector has been found.

Abstract: A method for generating a binary GTP codeword, comprised of N structure stages and each stage comprises at least one BCH codeword with error correction capability greater than a prior stage and smaller than a next stage, includes: receiving a syndrome vector s of a new stage 0 binary BCH codeword y over a field GF(2m) that comprises ?t syndromes of length m bits, wherein the syndrome vector s comprises l-th Reed-Solomon (RS) symbols of ?t RS codewords whose information symbols are delta syndromes of all BCH codewords from stage 0 until stage n?1; and multiplying s by a right submatrix ? of a matrix U, wherein U is an inverse of a parity matrix of an BCH code defined by tn, wherein the new binary BCH codeword is y=?·s.