Abstract: A system to improve error code decoding using historical information may include storage partitioned into memory ranks, and a table to record symbols having failures for each memory rank. The system may also generate a memory rank score for each memory rank. The system may also include an error control decoder that may use the memory rank score when each memory rank is accessed in order to determine whether an error should be corrected or not.

Abstract: A system to improve memory reliability in computer systems that may include memory chips, and may rely on a error control encoder to send codeword symbols for storage in each of the memory chips. At least two symbols from a codeword are assigned to each memory chip and therefore failure of any of the memory chips could affect two symbols or more. The system may also include a table to record failures and partial failures of the codeword symbols for each of the memory chips so the error control encoder can correct subsequent partial failures based upon the previous partial failures. The error control coder is capable of correcting and/or detecting more errors if only a fraction of a chip is noted in the table as having a failure as opposed to a full chip noted as having a failure.

Abstract: The invention includes a method for longitudinal position (LPOS) detection in a magnetic tape storage system for storing data upon linear tape open (LTO) magnetic storage tape, which data includes odd and even 36-bit LPOS words with error correcting ability.

Abstract: A method and system are disclosed for detecting memory chip failure in a computer memory system. The method comprises the steps of accessing user data from a set of user data chips, and testing the user data for errors using data from a set of system data chips. This testing is done by generating a sequence of check symbols from the user data, grouping the user data into a sequence of data symbols, and computing a specified sequence of syndromes. If all the syndromes are zero, the user data has no errors. If one of the syndromes is non-zero, then a set of discriminator expressions are computed, and used to determine whether a single or double symbol error has occurred. In the preferred embodiment, less than two full system data chips are used for testing and correcting the user data.

Abstract: Error correcting codes of any distance (including codes of distance greater than four) use only exclusive OR (XOR) operations. Any code over a finite field of characteristic two are converted into a code whose encoding and correcting algorithms involve only XORs of words (and loading and storing of the data). Thus, the implementation of the encoding and correcting algorithms is more efficient, since it uses only XORs of words—an operation which is available on almost all microprocessors. An important code, the (3, 3) code of distance four, is also described.

Abstract: A data storage subsystem that includes three data storage units, three check storage units, and an array controller coupled to the three data and three check storage units can tolerate failure of any three data and check storage units failures can be occur before data stored on the data storage subsystem is lost. Information is stored on the data storage subsystem as a symmetric Maximum Distance Separation code, such as a Winograd code, a Reed Solomon code, an EVENODD code or a derivative of an EVENODD code. The array controller determines the contents of the check storage units so that any three erasures of the data storage units and the check storage units can be corrected by the array controller. The array controller updates a block of data contained in any one of the data storage units and the check storage units using only six IO operations.

Abstract: A data storage subsystem that includes three data storage units, three check storage units, and an array controller coupled to the three data and three check storage units can tolerate failure of any three data and check storage units failures can be occur before data stored on the data storage subsystem is lost. Information is stored on the data storage subsystem as a symmetric Maximum Distance Separation code, such as a Winograd code, a Reed Solomon code, an EVENODD code or a derivative of an EVENODD code. The array controller determines the contents of the check storage units so that any three erasures of the data storage units and the check storage units can be corrected by the array controller. The array controller updates a block of data contained in any one of the data storage units and the check storage units using only six IO operations.

Abstract: The Hamming distance of an array of storage devices is increased by generating a parity check matrix based on column equations that are formed using an orthogonal parity code and includes a higher-order multiplier that changes each column. The higher order multiplier is selected to generate a finite basic field of a predetermined number of elements. The array has M rows and N columns, such that M is greater than or equal to three and N is greater than or equal to three. Row 1 through row M?2 of the array each have n–p data storage devices and p parity storage devices. Row M?1 of the array has n?(p+1) data storage devices and (p+1) parity storage devices. Lastly, row M of the array has N parity storage devices.

Abstract: An error correction algebraic decoder and an associated method correct a combination of a B-byte burst of errors and t-byte random errors in a failed sector, by iteratively adding and removing an erasure (N?B) times until the entire failed sector has been scanned, provided the following inequality is satisfied: (B+2t)?(R?1), where N denotes the number of bytes, B denotes the length of the burst of errors, t denotes the total number of random errors, and R denotes the number of check bytes in the failed sector. This results in a corrected sector at a decoding latency that is a generally linear function of the number of the check bytes R, as follows: Decoding Latency=5R(N?B).

Abstract: The Hamming distance of an array of storage devices is increased by generating a parity check matrix based on column equations that are formed using an orthogonal parity code and includes a higher-order multiplier that changes each column. The higher order multiplier is selected to generate a finite basic field of a predetermined number of elements. The array has M rows and N columns, such that M is greater than or equal to three and N is greater than or equal to three. Row 1 through row M-2 of the array each have n-p data storage devices and p parity storage devices. Row M-1 of the array has n-(p+1) data storage devices and (p+1) parity storage devices. Lastly, row M of the array has N parity storage devices.

Abstract: A data storage subsystem that includes three data storage units, three check storage units, and an array controller coupled to the three data and three check storage units can tolerate failure of any three data and check storage units failures can be occur before data stored on the data storage subsystem is lost. Information is stored on the data storage subsystem as a symmetric Maximum Distance Separation code, such as a Winograd code, a Reed Solomon code, an EVENODD code or a derivative of an EVENODD code. The array controller determines the contents of the check storage units so that any three erasures of the data storage units and the check storage units can be corrected by the array controller. The array controller updates a block of data contained in any one of the data storage units and the check storage units using only six IO operations.

Abstract: Error correcting codes of any distance (including codes of distance greater than four) use only exclusive OR (XOR) operations. Any code over a finite field of characteristic two are converted into a code whose encoding and correcting algorithms involve only XORs of words (and loading and storing of the data). Thus, the implementation of the encoding and correcting algorithms is more efficient, since it uses only XORs of words—an operation which is available on almost all microprocessors. An important code, the (3, 3) code of distance four, is also described.

Abstract: An efficient method for finding all the possible corrections of a bust of length b and e random errors consists of finding a polynomial whose roots are the candidate location for l— the location of the beginning of the burst—thus avoiding the search over all possible values of l (it is assumed that the burst is non-trivial, i.e., at least one of its errors has a non-zero value). In order to reduce the number of spurious solutions, it is assumed that the number of syndromes is t=2e+b+s, where s is at least 2. The larger the value of s the less likely it is that the algorithm will generate “spurious” solutions. Once the location of the burst is known, standard procedures are used to determine the magnitudes of the burst errors and the location and magnitude of the random errors.

Abstract: An error correction algebraic decoder uses a key equation solver for calculating the roots of finite field polynomial equations of degree up to six, and lends itself to efficient hardware implementation and low latency direction calculation. The decoder generally uses a two-step process. The first step is the conversion of quintic equations into sextic equations, and the second step is the adoption of an invertible Tschirnhausen transformation to reduce the sextic equations by eliminating the degree 5 term. The application of the Tschirnhausen transformation considerably decreases the complexity of the operations required in the transformation of the polynomial equation into a matrix. The second step defines a specific Gaussian elimination that separates the problem of solving quintic and sextic polynomial equations into a simpler problem of finding roots of a quadratic equation and a quartic equation.

Abstract: An error correction algebraic decoder and an associated method correct a combination of a B-byte burst of errors and t-byte random errors in a failed sector, by iteratively adding and removing an erasure (N−B) times until the entire failed sector has been scanned, provided the following inequality is satisfied: (B+2t)≦(R−1), where N denotes the number of bytes, B denotes the length of the burst of errors, t denotes the total number of random errors, and R denotes the number of check bytes in the failed sector. This results in a corrected sector at a decoding latency that is a generally linear function of the number of the check bytes R, as follows: Decoding Latency=5R(N−B).

Abstract: An on-the-fly algebraic error correction system and corresponding method for reducing error location search are presented. The method transforms an error locator polynomial into two transformed polynomials whose roots are elements in a smaller subfield, in order to significantly simplify the complexity, and to reduce the latency of the error correcting system hardware implementation. More specifically, if the error locator polynomial is over a finite field of (22n) elements, the transformed polynomial is over a finite subfield of (2n) elements. Thus, the problem of locating the roots of the error locator polynomial is reduced to locating the roots of the transformed polynomials. Assuming the error locator polynomial is of degree m, the present method requires at most (m2/2) evaluations of polynomials over the Galois field GF(22n) and (2n+1) evaluations over the subfield GF(2n) or root finding of two polynomials of at most a degree m over the subfield GF(2n).

Abstract: An error correction algebraic decoder uses a key equation solver for calculating the roots of finite field polynomial equations of degree up to six, and lends itself to efficient hardware implementation and low latency direction calculation. The decoder generally uses a two-step process. The first step is the conversion of quintic equations into sextic equations, and the second step is the adoption of an invertible Tschirnhausen transformation to reduce the sextic equations by eliminating the degree 5 term. The application of the Tschirnhausen transformation considerably decreases the complexity of the operations required in the transformation of the polynomial equation into a matrix. The second step defines a specific Gaussian elimination that separates the problem of solving quintic and sextic polynomial equations into a simpler problem of finding roots of a quadratic equation and a quartic equation.

Abstract: A computationally efficient, machine-implementable method and means for detecting and correcting errors in received codewords on-the-fly within the capacity of a linear cyclic code using ultra-fast error location processing. Each error locator polynomial of degree t over a finite Galois field derived from a codeword syndrome is mapped into a matrix representative of a system of linear simultaneous equations related to the polynomial coefficients. Roots indicative of error locations within the codeword are extracted from the matrix by a modified Gaussian Elimination process for all the roots where t≦5 and at least one root plus a subset of candidate roots from the finite field for iterative substitution where t>5. Corrected values are separately determined and correction is secured by logically combining the corrected values with the codeword values in error at the error locations represented by the roots.

Abstract: A computationally efficient, machine-implementable method and means for detecting and correcting errors in received codewords on-the-fly within the capacity of a linear cyclic code using ultra-fast error location processing. Each error locator polynomial of degree t over a finite Galois field derived from a codeword syndrome is mapped into a matrix representative of a system of linear simultaneous equations related to the polynomial coefficients. Roots indicative of error locations within the codeword are extracted from the matrix by a modified Gaussian Elimination process for all the roots where t.ltoreq.5 and at least one root plus a subset of candidate roots from the finite field for iterative substitution where t>5. Corrected values are separately determined and correction is secured by logically combining the corrected values with the codeword values in error at the error locations represented by the roots.

Abstract: The invention relates to an arithmetic unit (AU) in combination with an algebraic block ECC decoder for controlling errors in an electronically recorded digital data message by performing at least one of a plurality of predetermined arithmetic operations on the data message in one or more of a plurality of subfields of a first GF(2.sup.12) or a second GF(2.sup.8) finite field. The arithmetic operations are selected either from a first group of operations associated with a first subfield GF(2.sup.4) as cubically extended to the first finite field GF(2.sup.12) or as quadratically extended to the second finite field GF(2.sup.8), or selected from a second group of operations associated with a second subfield GF(2.sup.6) as quadratically extended to the first finite field GF(2.sup.12).