High resolution read attempts of a Flash memory device include many read attempts that differ from by their read thresholds, wherein these read thresholds are proximate to each other. These high resolution read attempts are time consuming.
These read attempts include (a) read attempts that are solely dedicated for finding a desired read threshold, and (b) read attempts that solely dedicated for soft decoding.
The finding of the desired read threshold involves operating a Digital Signal Processor (DSP) to set the desired read threshold.
After the finding, additional read attempts are used for generating reliability-metrics for a soft decoding process.
As indicated above—a read attempt for 2 bpc memory page may require reading a MSB page, by using a single MSB read threshold (in case there are not too many errors).
The MSB read threshold in this example for reading the MSB page bits is denoted by Xth,1 18. For reading the LSB page bits, it is required to read using two LSB read thresholds (in case there are not too many errors), which are denoted Xth,0, and Xth,2 17 and 19.
It is noted that the distribution of threshold voltages illustrated in
In
In order to perform soft sampling there is usually a DSP operation for searching the best initial read thresholds, around which the soft sampling takes place. This is required since the initial thresholds, which may be either default thresholds or some estimation based on previous read attempt, can be irrelevant. This is due to aging effects of memory cells, which result in distribution change over time and cycles. After a DSP operation for initial read thresholds estimation, a high resolution read attempt is done for providing inputs for the soft input decoder. A schematic block diagram of the described flow is provided in
There is a need to reduce the soft read penalty.
There may be provided joint digital signal processing (DSP) and error correction code (ECC) operation for reading data from a flash memory device. This may reduce the inherent overhead in producing soft information to a decoder. This overhead usually involves read attempts intended for characterizing the current page/codeword associated flash memory cells statistical distribution. Once the statistical characterization is sufficiently revealed and a desired read threshold (or thresholds) is set it is possible to perform soft sampling, which provides a high resolution read of the memory cells, to be used by the decoder.
It may be suggested to utilize the results of the read attempts which are used for statistical characterization as part of the soft information. If needed, complement the statistical characterization process using the ECC. For example, partial decoding can be employed, and the decoder can provide scores per different input hypotheses (this is described in more detail later). Once the statistical characterization process is complete, additional read attempts may take place to provide a high resolution soft input, which can be, for example, a reliability-metric per input bit for the decoder.
Since the statistical distribution of the threshold voltages changes over the Flash memory device life span, a read attempt may require learning the statistics and only then placing the thresholds for the read attempt which is used as input for the decoder. In case there are not too many errors, a hard input for the decoder may suffice once the statistics is known up to a sufficiently high accuracy. It is mainly required for setting read threshold such that a minimal number of read errors are obtained for the decoder inputs.
When there are relatively many errors, it may not be enough to provide just a single hard decision input, which is obtained by a single read, to the decoder. In such cases, a soft decoder may be applied when soft information, such as reliability information, for each bit is provided to the decoder. This reliability information is achieved by performing multiple read attempts using different read thresholds.
According to an embodiment of the invention a method may be provided and may include performing, by a flash memory controller, multiple read attempts of a group of flash memory cells, using multiple read thresholds, to provide multiple read results; determining, by the flash memory controller and based upon the multiple read results, a reliability metric of each of the multiple read results; and error correction decoding the multiple read results based upon reliability metrics associated with the multiple read results.
The method may include finding, based upon the multiple read results, at least one desired read threshold to be applied during future read attempts.
The method may include evaluating a characteristic of the multiple read results under different assumptions about mapping between the read thresholds and reliability metrics.
The characteristic may be a bit error rate metric associated with an outcome of a soft decoding process or a partial soft decoding process applied on the multiple read results.
The characteristic may be a bit error rate metric associated with an outcome of a hard decoding process or a partial hard decoding process applied on the multiple read results.
The different assumptions about the identity of the desired read threshold may differ from each other by a reliability associated with each of the multiple read results.
The method may include evaluating the characteristic of the multiple read thresholds under each assumption by comparing between (a) a relationship between numbers of first and second read results of different values, and (b) an expected relationship between numbers of first and second read results of different numbers.
The method may include evaluating the characteristic of the multiple read thresholds under each assumption by performing a partial decoding process of the multiple read results.
The partial decoding may be a partial soft decoding.
The partial soft decoding may involve applying iterations of soft decoding of a lowest decoding complexity.
The partial decoding may be a partial hard decoding.
The method may include evaluating the characteristic of the multiple read thresholds by checking a distribution of thresholds voltages of the group of memory cells under the different assumptions.
The selecting of the desired read threshold may be followed by performing at least one additional read attempt to provide additional read results and determining, based upon the at least one additional read result, a reliability of the at least one additional read result.
The method may include soft decoding the multiple read results.
The method may include performing additional read results using additional read thresholds, after finding the desired read threshold, wherein the additional read thresholds are proximate to the desired read threshold.
The additional read thresholds may be selected such that there are at least a predefined number of read thresholds that are proximate to the desired read threshold and are positioned at each side of the desired read threshold, as to provide the decoder with high resolution sampling for soft information.
The first and second read attempts may be executed before a completion of a determination of a desired read threshold.
According to an embodiment of the invention a method may be provided and may include starting a search for near optimum reliability metrics mapping related to multiple read thresholds; computing a histogram that represents a voltage threshold distribution obtained when performing multiple read attempts using the multiple read thresholds; activating a particle hard decoding for at least some of the multiple read thresholds and calculating a hard decoding score for each of the at least some read thresholds; computing a divergence metric for each read threshold; searching for a minimum of the voltage threshold distribution around every read threshold of the multiple read thresholds; calculating a read threshold score based upon a divergence metric of the read threshold, a hard decoding score of the read threshold and a minimum of the voltage threshold distribution around the read threshold; determining if, based upon read threshold scores assigned to the multiple read thresholds, labels to reliability metrics can be determined; if it is determined that labels to reliability metrics can be determined then applying the labels to the reliability metrics and starting soft decoding; if it is determined that labels to reliability metrics can not be determined then activating a partial soft decoding to calculate partial soft decoding scores per read threshold; calculating a new read threshold score for each read threshold based upon a partial soft decoding score of the read threshold and voltage threshold distribution around the read threshold; and applying the labels to the reliability metrics and starting soft decoding.
According to an embodiment of the invention a method may be provided and may include reading a flash memory array using multiple read thresholds that are positioned around one or more initial read thresholds; determining if an optimal hard read threshold can be determined; if it is determined that the optimal hard read threshold can not be determined then performing more read attempts using additional read thresholds; if it is determined that the optimal hard read threshold can be determined then setting additional read thresholds for high resolution read soft decoding; associating every read threshold with a reliability metric; and performing soft error correction decoding.
According to an embodiment of the invention a method may be provided and may include starting a soft decoding process; choosing, based on hard decoding scores, a subset of possible labels to reliability metrics hypotheses; performing partial soft decoding for every hypothesis; selecting a desired read threshold based on likelihood scores obtained during the partial soft decoding; and completing the soft decoding process taking into account the desired read threshold.
Further embodiments of the invention include a computer readable medium that is non-transitory and may store instructions for performing the above-described methods and any steps thereof, including any combinations of same. For example, the computer readable medium may store instructions for performing, by a flash memory controller, multiple read attempts of a group of flash memory cells, using multiple read thresholds, to provide multiple read results;
determining, by the flash memory controller and based upon the multiple read results, a reliability metric of each of the multiple read results; and error correction decoding the multiple read results based upon reliability metrics associated with the multiple read results.
Further embodiments of the invention include a computer readable medium that is non-transitory and may store instructions for performing the above-described methods and any steps thereof, including any combinations of same. For example, the computer readable medium may store instructions for reading a flash memory array using multiple read thresholds that are positioned around one or more initial read thresholds; determining if an optimal hard read threshold can be determined; if it is determined that the optimal hard read threshold can not be determined then performing more read attempts using additional read thresholds; if it is determined that the optimal hard read threshold can be determined then setting additional read thresholds for high resolution read soft decoding; associating every read threshold with a reliability metric; and performing soft error correction decoding.
Further embodiments of the invention include a computer readable medium that is non-transitory and may store instructions for performing the above-described methods and any steps thereof, including any combinations of same. For example, the computer readable medium may store instructions for starting a soft decoding process; choosing, based on hard decoding scores, a subset of possible labels to reliability metrics hypotheses; performing partial soft decoding for every hypothesis; selecting a desired read threshold based on likelihood scores obtained during the partial soft decoding; and completing the soft decoding process taking into account the desired read threshold.
Further embodiments of the invention include a computer readable medium that is non-transitory and may store instructions for performing the above-described methods and any steps thereof, including any combinations of same. For example, the computer readable medium may store instructions for starting a search for near optimum reliability metrics mapping related to multiple read thresholds; computing a histogram that represents a voltage threshold distribution obtained when performing multiple read attempts using the multiple read thresholds; activating a particle hard decoding for at least some of the multiple read thresholds and calculating a hard decoding score for each of the at least some read thresholds; computing a divergence metric for each read threshold; searching for a minimum of the voltage threshold distribution around every read threshold of the multiple read thresholds; calculating a read threshold score based upon a divergence metric of the read threshold, a hard decoding score of the read threshold and a minimum of the voltage threshold distribution around the read threshold; determining if, based upon read threshold scores assigned to the multiple read thresholds, labels to reliability metrics can be determined; if it is determined that labels to reliability metrics can be determined then applying the labels to the reliability metrics and starting soft decoding; if it is determined that labels to reliability metrics can not be determined then activating a partial soft decoding to calculate partial soft decoding scores per read threshold; calculating a new read threshold score for each read threshold based upon a partial soft decoding score of the read threshold and voltage threshold distribution around the read threshold; and applying the labels to the reliability metrics and starting soft decoding.
Additional embodiments of the invention include a system arranged to execute any or all of the methods described above, including any stages—and any combinations of same. For example, the system may include a flash memory controller that may include a read circuit that me be arranged to perform multiple read attempts of a group of flash memory cells, using multiple read thresholds, to provide multiple read results; a reliability circuit that may be arranged to determine, based upon the multiple read results, a reliability metric of each of the multiple read results; and an error correction decoding circuit that may be arranged to perform error correction decoding of the multiple read results based upon reliability metrics associated with the multiple read results.
The flash memory controller may include a read threshold circuit that may be arranged to find, based upon the multiple read results, at least one desired read threshold to be applied during future read attempts.
Additional embodiments of the invention include a system arranged to execute any or all of the methods described above, including any stages—and any combinations of same. For example, the system may include a flash memory controller that may include a read circuit that may be arranged to read a flash memory array using multiple read thresholds that are positioned around one or more initial read thresholds; a read threshold circuit that may be arranged to determine if an optimal hard read threshold can be determined; if it is determined that the optimal hard read threshold can not be determined then the read circuit that may be arranged to perform more read attempts using additional read thresholds; if it is determined that the optimal hard read threshold can be determined then the flash memory controller that may be arranged to set additional read thresholds for high resolution read soft decoding; associate every read threshold with a reliability metric; and perform soft error correction decoding.
Additional embodiments of the invention include a system arranged to execute any or all of the methods described above, including any stages—and any combinations of same. For example, the system may include a flash memory controller that may include a error correction decoding circuit, a reliability circuit and a read threshold circuit; wherein the error correction decoding circuit that may be arranged to start a soft decoding process; the reliability circuit that may be arranged to choose, based on hard decoding scores, a subset of possible labels to reliability metrics hypotheses; the error correction decoding circuit is further that may be arranged to perform partial soft decoding for every hypothesis; the read threshold circuit that may be arranged to select a desired read threshold based on likelihood scores obtained during the partial soft decoding; and the error correction decoding circuit that may be arranged to complete the soft decoding process taking into account the desired read threshold.
Additional embodiments of the invention include a system arranged to execute any or all of the methods described above, including any stages—and any combinations of same. For example, the system may include a flash memory controller that may include a read circuit, a reliability circuit, a read threshold circuit and an error correction decoding circuit; wherein the flash memory controller that may be arranged to compute a histogram that represents a voltage threshold distribution obtained when performing multiple read attempts using the multiple read thresholds; activate a particle hard decoding for at least some of the multiple read thresholds and calculate a hard decoding score for each of the at least some read thresholds; compute a divergence metric for each read threshold; search for a minimum of the voltage threshold distribution around every read threshold of the multiple read thresholds; calculate a read threshold score based upon a divergence metric of the read threshold, a hard decoding score of the read threshold and a minimum of the voltage threshold distribution around the read threshold; determine if, based upon read threshold scores assigned to the multiple read thresholds, labels to reliability metrics can be determined; if it is determined that labels to reliability metrics can be determined then apply the labels to the reliability metrics and starting soft decoding; if it is determined that labels to reliability metrics can not be determined then activate a partial soft decoding to calculate partial soft decoding scores per read threshold; calculate a new read threshold score for each read threshold based upon a partial soft decoding score of the read threshold and voltage threshold distribution around the read threshold; and apply the labels to the reliability metrics and starting soft decoding.
The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference to the following detailed description when read with the accompanying drawings in which:
It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.
In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present invention.
The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference to the following detailed description when read with the accompanying drawings.
It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.
Because the illustrated embodiments of the present invention may for the most part, be implemented using electronic components and circuits known to those skilled in the art, details will not be explained in any greater extent than that considered necessary as illustrated above, for the understanding and appreciation of the underlying concepts of the present invention and in order not to obfuscate or distract from the teachings of the present invention.
The following terms may be construed either in accordance with any definition thereof appearing in the prior art literature or in accordance with the specification, or as follows:
Bit error rate (BER): a proportion of incorrectly read bits. The BER may be measured right after reading at the input to the ECC decoder, or at the output of the decoder.
Undecodable Bit error rate (UBER): a parameter that a flash memory device manufacturer commits to vis a vis its customers, expressing the maximum proportion of wrongly read bits (wrongly read bits/total number of bits) that users of the flash memory device need to expect at any time during the stipulated lifetime of the flash memory device, e.g. UBER<1E-15 after maximal P/E cycles and 10 years.
Block: a set of flash memory device cells which must, due to physical limitations of the flash memory device, be erased together. Also termed erase sector, erase block.
Cell: A component of flash memory that stores one bit of information (in single-level cell devices) or n bits of information (in a multi-level device having 2 exp n levels). Typically, each cell comprises a floating-gate transistor. “Multi-level” means that the physical levels in the cell are, to an acceptable level of certainty, statistically partitionable into multiple distinguishable regions, plus a region corresponding to zero, such that digital values each comprising multiple bits can be represented by the cell. In contrast, in single-level cells, the physical levels in the cell are assumed to be statistically partitionable into only two regions, one corresponding to zero and one other, non-zero region, such that only one bit can be represented by a single-level cell.
Charge level: the measured voltage of a cell which reflects its electric charge.
Cycling: Repeatedly programming new data into flash memory cells and repeatedly erasing the cells between each two writing operations.
Digital value or “logical value”: n-tuple of bits represented by a cell in flash memory capable of generating 2 exp n distinguishable levels of a typically continuous physical value such as charge, where n may or may not be an integer.
Decoding: may refer to error correction decoding.
Erase cycle: The relatively slow process of erasing a block of cells (erase sector), each block typically comprising more than one page, or, in certain non-flash memory devices, of erasing a single cell or the duration of so doing. An advantage of erasing cells collectively in blocks as in flash memory, rather than individually, is enhanced programming speed: Many cells and typically even many pages of cells are erased in a single erase cycle.
Program erase (P/E) cycle: The process of erasing a block of cells (erase sector), each block typically comprising a plurality of pages, and subsequently writing new data into at least some of them. The terms “program” and “write” are used herein generally interchangeably.
Flash memory: Non-volatile computer memory including cells that are erased block by block, each block typically comprising more than one page, but are written into and read from, page by page. Includes NOR-type flash memory, NAND-type flash memory, and PRAM, e.g. Samsung PRAM, inter alia, and flash memory devices with any suitable number of levels per cell, such as but not limited to 2, 4, or 8.
Logical page: a portion of typically sequential data, whose amount is typically less than or equal to a predetermined amount of data defined to be a page full of data, which has typically been defined by a host (data source/destination) or user thereof, as a page, and which is sent by the host to a flash memory device for storage and is subsequently read by the host from the flash memory device.
Physical Page: A portion, typically 512 or 2048, 4096, 8192 or 16384 bytes in size, of a flash memory e.g. a NAND or NOR flash memory device. Writing and reading is typically performed physical page by physical page, as opposed to erasing which can be performed only at a granularity of an erase sector. A few bytes, typically 16-32 for every 512 data bytes are associated with each page (typically 16, 64 or 128 per page), for storage of error correction information. A typical block may include 32 512-byte pages, 64 2048-byte, 128 8192-bytes or 256 8192-bytes pages.
Alternatively, a physical page is an ordered set (e.g. sequence or array) of flash memory cells which are all written in simultaneously by each write operation, the set typically comprising a predetermined number of typically physically adjacent flash memory cells containing actual data written by and subsequently read by the host, as well as, typical error correction information and back pointers used for recognizing the true address of a page.
Program: same as “write”.
Program level (programmed level, programming level): amount of charge originally induced in a cell to represent a given logical value, as opposed to “present level”.
Retention: Retention of original physical levels induced in the flash memory cells despite time which has elapsed and despite previous erase/write cycles; retention is typically below 100% resulting in deterioration of original physical levels into present levels.
Retention time: The amount of time that data has been stored in a flash device, typically without, or substantially without, voltage having been supplied to the flash device i.e. the time which elapses between programming of a page and reading of the same page.
Threshold level or “decision level”: the voltage (e.g.) against which the charge level of a cell is measured. For example, a cell may be said to store a particular digital n-tuple D if the charge level or other physical level of the cell falls between two threshold values T.
In the present specification, the terms “row” and “column” refer to rows of cells and columns of cells, respectively and are not references to sub-divisions of a logical page.
The term “MSB” is used herein to denote the bit which is programmed into a multi-level cell, storing several bits, first. The term “LSB” is used herein to denote the bit which is programmed into the multi-level cell, last. The term “CSB” is used herein to denote the bit which is programmed into a 3-level cell, storing 3 bits, second, i.e. after the MSB and before the LSB. It is appreciated that more generally, e.g. if the multi-level cell stores 4 or more levels, there are more than one CSB and use of the term “CSB” herein, which implies that the cell is a 3-level cell, is merely by way of example and is not intended to be limiting.
“Page read Bit errors” are those errors found in the physical page corresponding to a logical page, which typically are corrected using ECC (error correction code) such that the page is successfully reconstructed despite these errors.
The term “reading threshold” and “detection threshold” are used generally interchangeably.
The terms “sampling” and “reading” are used generally interchangeably.
The terms “read attempt” and “read attempt” are used generally interchangeably.
The term “high resolution” sampling refers to samplings using read thresholds that are proximate to each other—so that a difference between adjacent read thresholds may be smaller (and even much smaller) that a width of a threshold voltage distribution lobe. The distance can be 1/x of the width of the threshold voltage distribution lobe, wherein x may exceed 2. Typical values of x may range between 4 and 20.
The terms “cell” and “flash memory cell” are used generally interchangeably.
In the context of the present application, the term “programming” comprises the following operations: Take as input a sequence of bits to be stored in memory, transform respectively into “programmed values” which are physical values which are taken to represent these bits and induce the programmed values in cells of flash memory, resulting in physical values which cluster around the programmed values respectively. The term “program” in this application does not necessarily include the process of coding e.g. error correction coding in which redundancy bits are added. Typically, programming is a final procedure which transforms a sequence of binary logical values which have previously undergone processes such as scrambling, addition of CRC, and coding.
A programming process is a method for inducing given programmed values in flash memory cells. Typically, the programming process involves a sequence of voltage pulses applied to a flash memory cell, each pulse increasing the voltage level of the cell. After each such pulse, the process may determine whether or not to continue, depending on whether the programmed value has been achieved.
One or more read attempts can be included in a read operation. The outcome of a read attempt can be used for generating reliability metrics or for providing a decoding result.
Any reference to a method should be interpreted as referring to a device that may execute the method.
There may be provided methods, computer readable media and systems for joint DSP and ECC decoding operation with minimal sampling overhead. The overhead is mainly measured in read attempts, which are considerably reduced by the disclosed methods.
There may be provided methods, computer readable media and systems for joint memory sampling and reliability metrics mapping calculation using ECC.
The method may include multiple sampling (read attempts) and refinement of one or more read thresholds using: (a) minimum search (without decoder) from computation of the voltage threshold distribution (histogram) from the available samples—finding the read threshold that will provide the lowest number of errors; (b) divergence estimation from the histogram—for example by comparing the ratio of “1” cells and “0” cells and comprising to a desired ratio (such as 1:1 ratio); (c) Hard decoder activation for optimal threshold search and reliability metrics assignment—using partial hard decoding—activating the ECC decoder to perform a partial ECC decoding on results of the read attempts; and (d) Soft decoder activation for optimal threshold search and reliability metrics assignment—using partial soft decoding.
Partial soft decoding may be defined as a low complexity soft decoding process which does not necessarily decode all errors. Such partial decoding provides BER metrics which can be used to adjust the labels to reliability metrics mapping.
It is noted that the results of reading a flash memory array with each of the read thresholds can be stored and used for both threshold selection and soft decoding.
Referring to
Yet according to another embodiment of the invention the histogram or any other manner for providing soft information can take into account the number of cells between read thresholds—such as the number of cells that their voltage threshold lies in range 321 between read thresholds 201 and 202.
The method may include low resolution sampling to be used for assigning preliminary labels to reliability metrics mapping (performing few read attempts using different read thresholds and then trying to map reliability metrics to the results of these read attempts), followed by a refined high resolution sampling based on earlier processing. Recalculation of mapping, and soft decoding using all available samples where every read threshold combination is associated with a reliability metric.
The mapping can take into account the distance of each read threshold from the optimal read threshold and a probability that is related to the distance. Such a distribution is illustrated by curve 1200 of
Curve 1200 that illustrates a symmetrical and non-linear relationship of a difference (dv) between a reference voltage provided to a flash memory cell and a desired (optimal or sub-optimal) threshold voltage of the flash memory cell and the probability to read “1” from a flash memory cell that was programmed to store “1”.
If, for example a flash memory is read by providing to its gate a reference voltage (Vref) that equals its optimal threshold voltage (Vopt=Vref) then there is a ˜50% probability to read “1” and about 50% probability to read “0”. If, for example, Vref exceeds Vopt by at least 200 mVolts then there is about 100% to read “1”. If, for example, Vref is lower from Vopt by at least 200 mV then there is about 100% to read “0”. It is noted that the relationship may change from die to die and also over time—but can be measured, provided by the manufacturer or otherwise estimated or calculated.
The system 30 includes a flash memory array 21, a flash memory controller 33 and an ECC decoder 34. The flash memory controller 33 can include a read circuit 31, a reliability circuit 32 and a read threshold circuit 34. The flash memory controller 33 may be arranged to perform a joint DSP and high resolution sampling.
The flash memory controller 33 can jointly perform read threshold estimation and high resolution sampling. Thus, near optimum read thresholds are estimated jointly with the soft read attempts, while possibly receiving soft scores from the decoder during the sampling as to assess the further recommended sampling thresholds.
This approach may reduce up to 50% in the number of read attempts required for obtaining decoder inputs at high resolution metrics.
The system 30 of
The system 30 may minimize the inherent overhead in producing decoder soft information input. This overhead usually involves read attempts solely intended for characterizing the current page/codeword associated memory cells' statistical distribution. Once the statistical characterization is sufficiently revealed, it is possible to perform soft sampling, which provides a high resolution from the memory cells, to be used by the decoder.
The system 30 may use results of the read attempts which are used for statistical characterization as part of the soft information. If needed, complement the statistical characterization process using the ECC. For example, partial decoding can be employed, and the ECC decoder 34 can provide scores per different input hypotheses (this is described in more detail later). Once the statistical characterization process is complete, additional read attempts may take place to provide a high resolution soft input, which can be, for example, a reliability-metric per input bit for the decoder.
These three stages can be initiated by a reception of a read command or by any other event such as errors found in previous read attempts, a lapse of a predefined period from the last update of read thresholds, arriving to a certain P/E count and the like.
The first stage (illustrated by the single read threshold of the upper part of
The second stage (illustrated by read thresholds 41-45) may include providing to an ECC decoder with high resolution input samples around the initial read threshold. This may include performing five read attempts with five different read thresholds 41-45 that are centered on the initial read threshold 41—two read thresholds at each side of the initial read threshold 41.
According to an embodiment of the invention every read result can also be labeled, such that the read results of thirty one read attempts can be represented by 5 bits per sampled cell—by a label.
The third stage (illustrated by the nine read thresholds of the lowest part of
For example—assuming that the optimal threshold is read threshold 45 and there is a need to provide four read thresholds from each side of read threshold 45—then additional thresholds such as 40 (leftmost) and 47-49 are added—they are used to provide additional read results.
If, for another example, the optimal threshold is read threshold 41 and only two thresholds per side are required—then the third stage will not require additional read attempts with additional read thresholds.
Referring to FIG. 6—the initial read threshold 61 is not the optimal read threshold and additional read thresholds are defined to include read thresholds 61-69.
The results of the multiple read attempts (using each read threshold out of read thresholds 61-69)—or at least some of the results (for example those obtained while using read thresholds 41-45) can be used to find a desired read threshold—and this finding may use an initial mapping from label values to reliability metrics. This initial mapping can be converted to a desired mapping from labels to reliability metrics—based on the read results. The method may follow by using the desired mapping for soft decoding of the codewords stored in the flash memory device.
Method 50 includes the following stages:
Method 70 may starts by stage 72 of performing multiple read attempts of a group of flash memory cells, using multiple read thresholds, to provide multiple read results. The group of the flash memory cells can be a page, a block, a portion of a page, a portion of a block or any other portion of a flash memory module.
The different read attempts differ from each other by threshold. If a single read threshold is looked for (for example—in SLC flash memory cells) the different read thresholds can be proximate to each other and proximate to (or include) an initial read threshold that is set without performing a dedicate DSP executed read threshold locating stage.
If MLC cells are read and there is a need to find multiple desired thresholds then the method can be repeated for each desired read threshold to be found. The multiple thresholds in this case can include multiple groups of read thresholds—a group of read thresholds per desired read threshold to be found. In x bit per cell flash memory cells there are 2^x groups of such read thresholds.
Stage 72 may be followed by stages 74 and 75.
Stage 74 may include determining, by the flash memory controller and based upon the multiple read results, a reliability metric of each of the multiple read results. The multiple read results and their associated reliability metrics can be fed to a soft decoder that may then perform a soft decoding process to provide decoded output—as illustrated by stage 79. Stage 79 may include error correction decoding the multiple read results based upon reliability metrics associated with the multiple read results.
Stage 75 may include finding, based upon the multiple read results, at least one desired read threshold to be applied during future read attempts.
Stage 75 may include stage 751 of evaluating a characteristic of the multiple read results under different assumptions about mappings between the read thresholds and reliability metrics. These assumptions can be equivalent to assumptions to an identity of the desired read threshold out multiple read thresholds that were used during stage 72. This evaluation can be much faster than a read attempt and thus multiple assumptions can be evaluated without inducing a substantial timing penalty.
The read threshold that is associated with the most reliable read results, or those which amount to a minimal amount of errors (after an execution of an error correction decoding process) can be selected to be the desired read threshold.
It is noted that the desired read threshold can be selected out of the multiple read threshold or can differ from each of these read thresholds. For example—a desired read threshold can have a value that is between two read thresholds or can be near one of the minimal or maxima read threshold of the multiple read thresholds.
Stage 75 may include stage 752 of evaluating the characteristic of the multiple read results under each assumption by comparing between (a) a relationship between numbers of read results of different values, and (b) an expected relationship between numbers of read results of different numbers.
Stage 75 may include stage 753 of evaluating the characteristic of the multiple read results under each assumption by performing a partial decoding process of the first and second read results. The partial decoding process may be a partial soft decoding, a partial hard decoding or a combination thereof.
Stage 75 may include stage 754 of evaluating the reliability of the multiple read results by checking a distribution of thresholds voltages of the group of memory cells under the different assumptions.
Stage 75 may be followed by stage 76 of performing, after the selection of the one or more desired read threshold, at least one additional read attempt to provide additional read results and determining, based upon the at least one additional read result, a reliability of the at least one additional read result.
Stage 75 may be followed by stage 77 of performing additional read attempts using additional read thresholds, after finding the one or more desired read threshold, wherein each additional read threshold is proximate to a desired read threshold. The additional read thresholds can be selected such that there are at least a predefined number of read thresholds that are proximate to each desired read threshold and are positioned at each side of the desired read threshold.
Soft Decoding Overview
For soft decoding of a codeword (also termed as packet) soft information per bit is required. This may be obtained by performing multiple read attempts of a flash memory device, where each read attempt uses different read thresholds. The read thresholds may be configured such that soft metrics, called log-likelihood ratio (LLR), can be computed per bit of the read results.
The definition of an LLR is LLR(bi)=LOG {(P(bi=1|y)/P(bi=1|y)}, where y is the channel output and bi is the i'th bit of some flash memory page.
The LLR expression can be substantially simplified, for an additive white Gaussian noise (AWGN) channel model. The AWGN is also a good approximation in many cases for the Flash lobes' distribution. By assuming an AWGN channel,
where y is the AWGN channel output.
It is straightforward to show that the LLR(bi) becomes
where the LLR per bit is created during the multiple read attempts, as a quantized version of an AWGN channel.
The quantization level per threshold is directly determined by the number of reads, as the base-two logarithm of the read counter. Once the multiple read attempts have been conducted, and LLRs are available for all codeword bits, the decoding process begins.
There are many possible approximations for LLR values mapping for implementation efficiency, such as mapping to fixed point integer values.
Iterative soft decoding includes the process of performing soft decoding on some of the code components, while repeating the process iteratively, and applying the most likely corrections every iteration (under different conditions, as will be elaborated here). On some code components it may be desired to perform only hard decoding. An example for such code can be a 3D code where the outer components are BCH codes which correct t>4 errors, for which soft decoding complexity may be too high to consider, and thus only hard decoding is done for outer code components. If this code has inner-1 and inner-2 BCH components with decoding capability of t≦4, then soft decoding may be efficiently implemented here (in terms of computational complexity, or hardware implementation).
The soft decoding for a component code may include a notation of Sphere decoding. In particular, when using a BCH component code, this can include creating a list of candidates of the most likely error hypotheses. Perform BCH decoding for every candidate in the list, and compute a soft score for every decoding result by
where C is the set of error bits, and bm is a location of an error bit.
Usually, the selected error hypothesis of a soft component decoder has the smallest SLLR score.
Sampling and Score Mapping
The sampling and score mapping can include calculating multiple reliability metrics to multiple read thresholds and using these metrics for soft decoding.
A method may be provided and may include calculating a probability density function (pdf) from the read results. Using the pdf, it is possible to determine the minimum of histograms that map the number of read results having different values, which may be associated with the optimal hard read threshold. This is usually the case when all lobes have identical symmetric distributions. However, when this is not so, the minimum of the pdf is not always the optimal hard read threshold. Therefore this stage can be provided for assigning a score per label. This is denoted in the figure by Spdf(i), where i is a threshold index. Spdf(i) can be computed is by the pdf values associated with a threshold from the computed histogram: Spdf(i)=f(i), where f(i) is the number of measured cells within a bin normalized by the total number of bits, defining an empirical pdf.
A method can be provided for finding the optimal label to soft metric mapping. It may include (a) obtaining multiple samples around initial read thresholds, (b) computing a probability density function (pdf) from the available input, (c) using the pdf to determine the minimum points of the histograms, which may be associated with the optimal hard read threshold. This is usually the case when all lobes have identical symmetric distributions. However, when this is not so, the minimum of the pdf may not be always the optimal hard read threshold. Therefore this stage may provide a score output per label.
Another score that can be computed from the pdf is the divergence score. The divergence aims to find how far is the distribution around a threshold from the expected distribution.
The divergence score may be defined, for example, as follows Sd(i)=2^(−ND(p∥q), where N is the number of bits in a codeword, the phrase a^b is a by the power of b, q is the probability measured by the histogram, and p is the expected probability on the optimal threshold. The measure D(p∥q) can be computed according to the Kullback-Leibler divergence.
The divergence score SD(i) can be responsive to a distance between a read threshold used during a certain read attempt and a desired threshold. An approximate computation can be carried out by counting the number of one-valued read results (‘1’) relative to the total number of bits in a codeword or relative to the number of zero-valued (‘0’) read results. For equally likely codeword distributions, i.e. p=0.5, it is expected that the empirical probability measure would be nearly 0.5. If the divergence is too far from p, the read threshold may be ignored.
Using the pdf scores Spdf(i) and the divergence scores SD(i), it is possible to perform a partial hard decoding. A partial hard decoding may include an efficient operation which uses some inner component codes for decoding. In case of BCH inner components, the partial decoding scores may be the actual number of corrected bits per inner BCH component (or some max value if the component cannot be corrected).
The sum of scores of all inner components may be denoted as SHard(i), where again i is associated with a read threshold. These scores may reflect a coarse estimation of the number of errors associated with the read threshold. Then, the decision on optimum hard threshold may be done by combining the hard score SHard(i), SD(i) and Spdf(i).
In general the combination may be defined via a function mapping SpdfHard(i)=f(Spdf(i), SD(i), SHard(i)).
Another exemplary weighed combining of the scores can be SpdfHard(i)=Spdf(i)+Ai*SD(i)+Bi*SHard(i), where Ai and Bi are threshold dependent weights for combining the scores of the three stages described.
The method may follow by mapping the labels using the input scores SpdfHard(i) into reliability metric. The mapping may be done using the distribution of the associated voltage threshold lobes, which may be known in advance, or may be estimated.
According to the expected distribution, the estimation may be done separately, or directly from the weighted scores SpdfHard(i). If this mapping is successful (e.g. the scores correspond to a reference distribution), then the mapping can be provided from the soft decoder, where each label is directly mapped to a reliability metric, which the decoder uses for soft decoding.
The method may follow by soft decoder activation. If the soft decoder fails, or if the labels to reliability metrics mapping is not successful using SpdfHard(i), then the mapping can be done using partial soft decoding.
There is provided a method for performing partial soft decoding, the method may include: (A) Choosing, based on the hard/pdf scores SpdfHard(i), a subset of possible labels to reliability metrics hypotheses, (B) For every hypothesis performing partial soft decoding. When using, for example, BCH component code the partial decoding may include performing soft decoding per component on a small list of candidates, where the lowest sum-LLR of every component soft decoding can be saved in SLLR(k), where k is the code component index. If the code has a multi-dimensional structure, the partial soft decoding may include activating only a single soft decoding iteration per mapping hypothesis. (C) Combining the scores per hypothesis, which may be done as follows Ssoft(i)=SUM{SLLR(k)}, for each k value. (D) Choosing the suitable label to reliability metrics mapping, which may provide the most likely soft decoder reliability metrics input, and (E) Activating the soft decoder.
A method may be provided and may include: (A) performing a low resolution sampling, for which the statistical characterization is computed, for example computing scores SpdfHard(i) and Ssoft(i), (B) From these scores it may be determined if further sampling is required. (C) If it is determined that no more sampling is required, then soft decoding may be issued based on the optimum selected mapping of labels to reliability metrics. (D) If it is determined that further sampling is needed, then the additional read attempts may be done according to last step results. Accordingly, SpdfHard(i) and Ssoft(i) may provide a score estimation per threshold obtained during the low resolution read.
This step may reveal the dynamic range available for the reliability metrics per lobe. Wherever the reliability metrics dynamic range is too small, further sampling might be required. Thus the selection of high resolution sampling can be done accurately.
According to the expected distribution, the estimation may be done separately, or directly from the weighted scores SpdfHard(i). If this mapping is successful (e.g. the scores correspond to a reference distribution), then the mapping can be provided from the soft decoder, where now every label is directly mapped to a reliability metric, which the decoder uses for soft decoding. Next stage clearly is a soft decoder activation. If the decoder fails, or if the labels to reliability metrics mapping is not successful using SpdfHard(i), then the mapping can be done using partial soft decoding.
Partial soft decoding may be done, like described in
Method 90 includes:
According to an embodiment of the invention a method is provided and may include performing a first step of low resolution sampling, for which the statistical characterization is computed. Statistical characterization may be done according to steps disclosed earlier.
During these steps the scores SpdfHard(i) and Ssoft(i) can be computed. From these scores it may be determined if further sampling is required. If no more sampling is required, then soft decoding may be issued based on the near optimum selected mapping of labels to reliability metrics.
If further sampling is needed, then the additional read attempts may be done according to last step results. That is, SpdfHard(i) and Ssoft(i) provide a score estimation per threshold obtained during the low resolution read. This step may reveal the dynamic range available for the reliability metrics per lobe. Wherever the reliability metrics dynamic range is too small, further sampling might be required. Thus the selection of high resolution sampling can be done accurately.
An example for multi-stage sampling as described above is given in
In this case a total of additional eight read attempts are performed.
The results are labeled, and a DSP processing like described above is done. The result of this processing is a list of additional read thresholds for which sampling is required. Once all samples are available, the near optimum labels to reliability metrics mapping can be done, according to disclosed methods.
For many reads this provides a two-fold read attempts reduction. For an LSB page of a 3 bpc device there can be nearly four-fold less read attempts. The read results of low resolution sampling are labeled, and a DSP processing like described above is done. The result of this processing is a list of additional read thresholds for which sampling (by LSB page reads) is required.
Once all samples are available, the near optimum labels to reliability metrics mapping can be done, according to disclosed methods.
The extension to any multi-level Flash device with 3-bpc or 4-bpc for example is straightforward, and this invention, although demonstrated for 2 bpc Flash devices, covers any N-bpc Flash device.
The invention may also be implemented in a computer program for running on a computer system, at least including code portions for performing steps of a method according to the invention when run on a programmable apparatus, such as a computer system or enabling a programmable apparatus to perform functions of a device or system according to the invention.
A computer program is a list of instructions such as a particular application program and/or an operating system. The computer program may for instance include one or more of: a subroutine, a function, a procedure, an object method, an object implementation, an executable application, an applet, a servlet, a source code, an object code, a shared library/dynamic load library and/or other sequence of instructions designed for execution on a computer system.
The computer program may be stored internally on a non-transitory computer readable medium. All or some of the computer program may be provided on computer readable media permanently, removably or remotely coupled to an information processing system. The computer readable media may include, for example and without limitation, any number of the following: magnetic storage media including disk and tape storage media; optical storage media such as compact disk media (e.g., CD-ROM, CD-R, etc.) and digital video disk storage media; nonvolatile memory storage media including semiconductor-based memory units such as FLASH memory, EEPROM, EPROM, ROM; ferromagnetic digital memories; MRAM; volatile storage media including registers, buffers or caches, main memory, RAM, etc.
A computer process typically includes an executing (running) program or portion of a program, current program values and state information, and the resources used by the operating system to manage the execution of the process. An operating system (OS) is the software that manages the sharing of the resources of a computer and provides programmers with an interface used to access those resource's. An operating system processes system data and user input, and responds by allocating and managing tasks and internal system resources as a service to users and programs of the system.
The computer system may for instance include at least one processing unit, associated memory and a number of input/output (I/O) devices. When executing the computer program, the computer system processes information according to the computer program and produces resultant output information via I/O devices.
In the foregoing specification, the invention has been described with reference to specific examples of embodiments of the invention. It will, however, be evident that various modifications and changes may be made therein without departing from the broader spirit and scope of the invention as set forth in the appended claims.
Moreover, the terms “front,” “back,” “top,” “bottom,” “over,” “under” and the like in the description and in the claims, if any, are used for descriptive purposes and not necessarily for describing permanent relative positions. It is understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in other orientations than those illustrated or otherwise described herein.
The connections as discussed herein may be any type of connection suitable to transfer signals from or to the respective nodes, units or devices, for example via intermediate devices. Accordingly, unless implied or stated otherwise, the connections may for example be direct connections or indirect connections. The connections may be illustrated or described in reference to being a single connection, a plurality of connections, unidirectional connections, or bidirectional connections. However, different embodiments may vary the implementation of the connections. For example, separate unidirectional connections may be used rather than bidirectional connections and vice versa. Also, plurality of connections may be replaced with a single connections that transfers multiple signals serially or in a time multiplexed manner. Likewise, single connections carrying multiple signals may be separated out into various different connections carrying subsets of these signals. Therefore, many options exist for transferring signals.
Although specific conductivity types or polarity of potentials have been described in the examples, it will appreciated that conductivity types and polarities of potentials may be reversed.
Each signal described herein may be designed as positive or negative logic. In the case of a negative logic signal, the signal is active low where the logically true state corresponds to a logic level zero. In the case of a positive logic signal, the signal is active high where the logically true state corresponds to a logic level one. Note that any of the signals described herein can be designed as either negative or positive logic signals. Therefore, in alternate embodiments, those signals described as positive logic signals may be implemented as negative logic signals, and those signals described as negative logic signals may be implemented as positive logic signals.
Furthermore, the terms “assert” or “set” and “negate” (or “deassert” or “clear”) are used herein when referring to the rendering of a signal, status bit, or similar apparatus into its logically true or logically false state, respectively. If the logically true state is a logic level one, the logically false state is a logic level zero. And if the logically true state is a logic level zero, the logically false state is a logic level one.
Those skilled in the art will recognize that the boundaries between logic blocks are merely illustrative and that alternative embodiments may merge logic blocks or circuit elements or impose an alternate decomposition of functionality upon various logic blocks or circuit elements. Thus, it is to be understood that the architectures depicted herein are merely exemplary, and that in fact many other architectures can be implemented which achieve the same functionality.
Any arrangement of components to achieve the same functionality is effectively “associated” such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as “associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being “operably connected,” or “operably coupled,” to each other to achieve the desired functionality.
Furthermore, those skilled in the art will recognize that boundaries between the above described operations merely illustrative. The multiple operations may be combined into a single operation, a single operation may be distributed in additional operations and operations may be executed at least partially overlapping in time. Moreover, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be altered in various other embodiments.
Also for example, in one embodiment, the illustrated examples may be implemented as circuitry located on a single integrated circuit or within a same device. Alternatively, the examples may be implemented as any number of separate integrated circuits or separate devices interconnected with each other in a suitable manner.
Also for example, the examples, or portions thereof, may implemented as soft or code representations of physical circuitry or of logical representations convertible into physical circuitry, such as in a hardware description language of any appropriate type.
Also, the invention is not limited to physical devices or units implemented in non-programmable hardware but can also be applied in programmable devices or units able to perform the desired device functions by operating in accordance with suitable program code, such as mainframes, minicomputers, servers, workstations, personal computers, notepads, personal digital assistants, electronic games, automotive and other embedded systems, cell phones and various other wireless devices, commonly denoted in this application as ‘computer systems’.
However, other modifications, variations and alternatives are also possible. The specifications and drawings are, accordingly, to be regarded in an illustrative rather than in a restrictive sense.
In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word ‘comprising’ does not exclude the presence of other elements or steps then those listed in a claim. Furthermore, the terms “a” or “an,” as used herein, are defined as one or more than one. Also, the use of introductory phrases such as “at least one” and “one or more” in the claims should not be construed to imply that the introduction of another claim element by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim element to inventions containing only one such element, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an.” The same holds true for the use of definite articles. Unless stated otherwise, terms such as “first” and “second” are used to arbitrarily distinguish between the elements such terms describe. Thus, these terms are not necessarily intended to indicate temporal or other prioritization of such elements The mere fact that certain measures are recited in mutually different claims does not indicate that a combination of these measures cannot be used to advantage.
While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those of ordinary skill in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.
This application is a NONPROVISIONAL of, claims priority to and incorporates by reference U.S. provisional patent application No. 61/472,557, filing date 6 Apr. 2011.
Number | Name | Date | Kind |
---|---|---|---|
4430701 | Christian et al. | Feb 1984 | A |
4463375 | Macovski | Jul 1984 | A |
4584686 | Fritze | Apr 1986 | A |
4589084 | Fling et al. | May 1986 | A |
4777589 | Boettner et al. | Oct 1988 | A |
4866716 | Weng | Sep 1989 | A |
5003597 | Merkle | Mar 1991 | A |
5077737 | Leger et al. | Dec 1991 | A |
5297153 | Baggen et al. | Mar 1994 | A |
5305276 | Uenoyama | Apr 1994 | A |
5592641 | Doyle et al. | Jan 1997 | A |
5623620 | Doyle et al. | Apr 1997 | A |
5640529 | Hasbun | Jun 1997 | A |
5657332 | Auclair et al. | Aug 1997 | A |
5663901 | Harari et al. | Sep 1997 | A |
5724538 | Morris et al. | Mar 1998 | A |
5729490 | Calligaro et al. | Mar 1998 | A |
5740395 | Wells et al. | Apr 1998 | A |
5745418 | Hu et al. | Apr 1998 | A |
5778430 | Ish et al. | Jul 1998 | A |
5793774 | Usui et al. | Aug 1998 | A |
5920578 | Zook et al. | Jul 1999 | A |
5926409 | Engh et al. | Jul 1999 | A |
5933368 | Hu et al. | Aug 1999 | A |
5956268 | Lee | Sep 1999 | A |
5956473 | Hu et al. | Sep 1999 | A |
5968198 | Balachandran | Oct 1999 | A |
5982659 | Irrinki et al. | Nov 1999 | A |
6011741 | Harari et al. | Jan 2000 | A |
6016275 | Han | Jan 2000 | A |
6038634 | Ji et al. | Mar 2000 | A |
6081878 | Estakhri et al. | Jun 2000 | A |
6094465 | Stein et al. | Jul 2000 | A |
6119245 | Hiratsuka | Sep 2000 | A |
6182261 | Haller et al. | Jan 2001 | B1 |
6192497 | Yang et al. | Feb 2001 | B1 |
6195287 | Hirano | Feb 2001 | B1 |
6199188 | Shen et al. | Mar 2001 | B1 |
6209114 | Wolf et al. | Mar 2001 | B1 |
6259627 | Wong | Jul 2001 | B1 |
6272052 | Miyauchi | Aug 2001 | B1 |
6278633 | Wong et al. | Aug 2001 | B1 |
6279133 | Vafai et al. | Aug 2001 | B1 |
6301151 | Engh et al. | Oct 2001 | B1 |
6370061 | Yachareni et al. | Apr 2002 | B1 |
6374383 | Weng | Apr 2002 | B1 |
6504891 | Chevallier | Jan 2003 | B1 |
6532169 | Mann et al. | Mar 2003 | B1 |
6532556 | Wong et al. | Mar 2003 | B1 |
6553533 | Demura et al. | Apr 2003 | B2 |
6560747 | Weng | May 2003 | B1 |
6637002 | Weng et al. | Oct 2003 | B1 |
6639865 | Kwon | Oct 2003 | B2 |
6674665 | Mann et al. | Jan 2004 | B1 |
6675281 | Oh et al. | Jan 2004 | B1 |
6704902 | Shinbashi et al. | Mar 2004 | B1 |
6751766 | Guterman et al. | Jun 2004 | B2 |
6772274 | Estakhri | Aug 2004 | B1 |
6781910 | Smith | Aug 2004 | B2 |
6792569 | Cox et al. | Sep 2004 | B2 |
6873543 | Smith et al. | Mar 2005 | B2 |
6891768 | Smith et al. | May 2005 | B2 |
6914809 | Hilton et al. | Jul 2005 | B2 |
6915477 | Gollamudi et al. | Jul 2005 | B2 |
6952365 | Gonzalez et al. | Oct 2005 | B2 |
6961890 | Smith | Nov 2005 | B2 |
6968421 | Conley | Nov 2005 | B2 |
6990012 | Smith et al. | Jan 2006 | B2 |
6996004 | Fastow et al. | Feb 2006 | B1 |
6999854 | Roth | Feb 2006 | B2 |
7010739 | Feng et al. | Mar 2006 | B1 |
7012835 | Gonzalez et al. | Mar 2006 | B2 |
7038950 | Hamilton et al. | May 2006 | B1 |
7068539 | Guterman et al. | Jun 2006 | B2 |
7079436 | Perner et al. | Jul 2006 | B2 |
7149950 | Spencer et al. | Dec 2006 | B2 |
7177977 | Chen et al. | Feb 2007 | B2 |
7188228 | Chang et al. | Mar 2007 | B1 |
7191379 | Adelmann et al. | Mar 2007 | B2 |
7196946 | Chen et al. | Mar 2007 | B2 |
7203874 | Roohparvar | Apr 2007 | B2 |
7212426 | Park et al | May 2007 | B2 |
7290203 | Emma et al. | Oct 2007 | B2 |
7292365 | Knox | Nov 2007 | B2 |
7301928 | Nakabayashi et al. | Nov 2007 | B2 |
7315916 | Bennett et al. | Jan 2008 | B2 |
7388781 | Litsyn et al. | Jun 2008 | B2 |
7395404 | Gorobets et al. | Jul 2008 | B2 |
7441067 | Gorobets et al. | Oct 2008 | B2 |
7443729 | Li et al. | Oct 2008 | B2 |
7450425 | Aritome | Nov 2008 | B2 |
7454670 | Kim et al. | Nov 2008 | B2 |
7466575 | Shalvi et al. | Dec 2008 | B2 |
7533328 | Alrod et al. | May 2009 | B2 |
7558109 | Brandman et al. | Jul 2009 | B2 |
7593263 | Sokolov et al. | Sep 2009 | B2 |
7610433 | Randell et al. | Oct 2009 | B2 |
7613043 | Cornwell et al. | Nov 2009 | B2 |
7619922 | Li et al. | Nov 2009 | B2 |
7697326 | Sommer et al. | Apr 2010 | B2 |
7706182 | Shalvi et al. | Apr 2010 | B2 |
7716538 | Gonzalez et al. | May 2010 | B2 |
7804718 | Kim | Sep 2010 | B2 |
7805663 | Brandman et al. | Sep 2010 | B2 |
7805664 | Yang et al. | Sep 2010 | B1 |
7844877 | Litsyn et al. | Nov 2010 | B2 |
7911848 | Eun et al. | Mar 2011 | B2 |
7961797 | Yang et al. | Jun 2011 | B1 |
7975192 | Sommer et al. | Jul 2011 | B2 |
8020073 | Emma et al. | Sep 2011 | B2 |
8108590 | Chow et al. | Jan 2012 | B2 |
8122328 | Liu et al. | Feb 2012 | B2 |
8159881 | Yang | Apr 2012 | B2 |
8190961 | Yang et al. | May 2012 | B1 |
8225181 | Perlmutter et al. | Jul 2012 | B2 |
8250324 | Haas et al. | Aug 2012 | B2 |
8300823 | Bojinov et al. | Oct 2012 | B2 |
8305812 | Levy et al. | Nov 2012 | B2 |
8327246 | Weingarten et al. | Dec 2012 | B2 |
8407560 | Ordentlich et al. | Mar 2013 | B2 |
8417893 | Khmelnitsky et al. | Apr 2013 | B2 |
8693258 | Weingarten et al. | Apr 2014 | B2 |
20010034815 | Dugan et al. | Oct 2001 | A1 |
20020063774 | Hillis et al. | May 2002 | A1 |
20020085419 | Kwon et al. | Jul 2002 | A1 |
20020154769 | Petersen et al. | Oct 2002 | A1 |
20020156988 | Toyama et al. | Oct 2002 | A1 |
20020174156 | Birru et al. | Nov 2002 | A1 |
20030014582 | Nakanishi | Jan 2003 | A1 |
20030065876 | Lasser | Apr 2003 | A1 |
20030101404 | Zhao et al. | May 2003 | A1 |
20030105620 | Bowen | Jun 2003 | A1 |
20030177300 | Lee et al. | Sep 2003 | A1 |
20030192007 | Miller et al. | Oct 2003 | A1 |
20040015771 | Lasser et al. | Jan 2004 | A1 |
20040030971 | Tanaka et al. | Feb 2004 | A1 |
20040059768 | Denk et al. | Mar 2004 | A1 |
20040080985 | Chang et al. | Apr 2004 | A1 |
20040153722 | Lee | Aug 2004 | A1 |
20040153817 | Norman et al. | Aug 2004 | A1 |
20040181735 | Xin | Sep 2004 | A1 |
20040203591 | Lee | Oct 2004 | A1 |
20040210706 | In et al. | Oct 2004 | A1 |
20050013165 | Ban | Jan 2005 | A1 |
20050018482 | Cemea et al. | Jan 2005 | A1 |
20050083735 | Chen et al. | Apr 2005 | A1 |
20050117401 | Chen et al. | Jun 2005 | A1 |
20050120265 | Pline et al. | Jun 2005 | A1 |
20050128811 | Kato et al. | Jun 2005 | A1 |
20050138533 | Le Bars et al. | Jun 2005 | A1 |
20050144213 | Simkins et al. | Jun 2005 | A1 |
20050144368 | Chung et al. | Jun 2005 | A1 |
20050169057 | Shibata et al. | Aug 2005 | A1 |
20050172179 | Brandenberger et al. | Aug 2005 | A1 |
20050213393 | Lasser | Sep 2005 | A1 |
20050243626 | Ronen | Nov 2005 | A1 |
20060059406 | Micheloni et al. | Mar 2006 | A1 |
20060059409 | Lee | Mar 2006 | A1 |
20060064537 | Oshima et al. | Mar 2006 | A1 |
20060101193 | Murin | May 2006 | A1 |
20060195651 | Estakhri et al. | Aug 2006 | A1 |
20060203587 | Li et al. | Sep 2006 | A1 |
20060221692 | Chen | Oct 2006 | A1 |
20060248434 | Radke et al. | Nov 2006 | A1 |
20060268608 | Noguchi et al. | Nov 2006 | A1 |
20060282411 | Fagin et al. | Dec 2006 | A1 |
20060284244 | Forbes et al. | Dec 2006 | A1 |
20060294312 | Walmsley | Dec 2006 | A1 |
20070025157 | Wan et al. | Feb 2007 | A1 |
20070063180 | Asano et al. | Mar 2007 | A1 |
20070081388 | Joo | Apr 2007 | A1 |
20070098069 | Gordon | May 2007 | A1 |
20070103992 | Sakui et al. | May 2007 | A1 |
20070104004 | So et al. | May 2007 | A1 |
20070109858 | Conley et al. | May 2007 | A1 |
20070124652 | Litsyn et al. | May 2007 | A1 |
20070140006 | Chen et al. | Jun 2007 | A1 |
20070143561 | Gorobets | Jun 2007 | A1 |
20070150694 | Chang et al. | Jun 2007 | A1 |
20070168625 | Cornwell et al. | Jul 2007 | A1 |
20070171714 | Wu et al. | Jul 2007 | A1 |
20070171730 | Ramamoorthy et al. | Jul 2007 | A1 |
20070180346 | Murin | Aug 2007 | A1 |
20070223277 | Tanaka et al. | Sep 2007 | A1 |
20070226582 | Tang et al. | Sep 2007 | A1 |
20070226592 | Radke | Sep 2007 | A1 |
20070228449 | Takano et al. | Oct 2007 | A1 |
20070253249 | Kang et al. | Nov 2007 | A1 |
20070253250 | Shibata et al. | Nov 2007 | A1 |
20070263439 | Cornwell et al. | Nov 2007 | A1 |
20070266291 | Toda et al. | Nov 2007 | A1 |
20070271494 | Gorobets | Nov 2007 | A1 |
20070297226 | Mokhlesi | Dec 2007 | A1 |
20080010581 | Alrod et al. | Jan 2008 | A1 |
20080028014 | Hilt et al. | Jan 2008 | A1 |
20080049497 | Mo | Feb 2008 | A1 |
20080055989 | Lee et al. | Mar 2008 | A1 |
20080082897 | Brandman et al. | Apr 2008 | A1 |
20080092026 | Brandman et al. | Apr 2008 | A1 |
20080104309 | Cheon et al. | May 2008 | A1 |
20080112238 | Kim et al. | May 2008 | A1 |
20080116509 | Harari et al. | May 2008 | A1 |
20080126686 | Sokolov et al. | May 2008 | A1 |
20080127104 | Li et al. | May 2008 | A1 |
20080128790 | Jung | Jun 2008 | A1 |
20080130341 | Shalvi et al. | Jun 2008 | A1 |
20080137413 | Kong et al. | Jun 2008 | A1 |
20080137414 | Park et al. | Jun 2008 | A1 |
20080141043 | Flynn et al. | Jun 2008 | A1 |
20080148115 | Sokolov et al. | Jun 2008 | A1 |
20080158958 | Shalvi et al. | Jul 2008 | A1 |
20080159059 | Moyer | Jul 2008 | A1 |
20080162079 | Astigarraga et al. | Jul 2008 | A1 |
20080168216 | Lee | Jul 2008 | A1 |
20080168320 | Cassuto et al. | Jul 2008 | A1 |
20080181001 | Shalvi | Jul 2008 | A1 |
20080198650 | Shalvi et al. | Aug 2008 | A1 |
20080198652 | Shalvi et al. | Aug 2008 | A1 |
20080201620 | Gollub | Aug 2008 | A1 |
20080209114 | Chow et al. | Aug 2008 | A1 |
20080219050 | Shalvi et al. | Sep 2008 | A1 |
20080225599 | Chae | Sep 2008 | A1 |
20080250195 | Chow et al. | Oct 2008 | A1 |
20080263262 | Sokolov et al. | Oct 2008 | A1 |
20080282106 | Shalvi et al. | Nov 2008 | A1 |
20080285351 | Shlick et al. | Nov 2008 | A1 |
20080301532 | Uchikawa et al. | Dec 2008 | A1 |
20090024905 | Shalvi et al. | Jan 2009 | A1 |
20090027961 | Park et al. | Jan 2009 | A1 |
20090043951 | Shalvi et al. | Feb 2009 | A1 |
20090046507 | Aritome | Feb 2009 | A1 |
20090072303 | Prall et al. | Mar 2009 | A9 |
20090091979 | Shalvi | Apr 2009 | A1 |
20090103358 | Sommer et al. | Apr 2009 | A1 |
20090106485 | Anholt | Apr 2009 | A1 |
20090113275 | Chen et al. | Apr 2009 | A1 |
20090125671 | Flynn et al. | May 2009 | A1 |
20090132755 | Radke | May 2009 | A1 |
20090144598 | Yoon et al. | Jun 2009 | A1 |
20090144600 | Perlmutter et al. | Jun 2009 | A1 |
20090150599 | Bennett | Jun 2009 | A1 |
20090150748 | Egner et al. | Jun 2009 | A1 |
20090157964 | Kasorla et al. | Jun 2009 | A1 |
20090158126 | Perlmutter et al. | Jun 2009 | A1 |
20090168524 | Golov et al. | Jul 2009 | A1 |
20090187803 | Anholt et al. | Jul 2009 | A1 |
20090199074 | Sommer | Aug 2009 | A1 |
20090213653 | Perlmutter et al. | Aug 2009 | A1 |
20090213654 | Perlmutter et al. | Aug 2009 | A1 |
20090228761 | Perlmutter et al. | Sep 2009 | A1 |
20090240872 | Perlmutter et al. | Sep 2009 | A1 |
20090282185 | Van Cauwenbergh | Nov 2009 | A1 |
20090282186 | Mokhlesi et al. | Nov 2009 | A1 |
20090287930 | Nagaraja | Nov 2009 | A1 |
20090300269 | Radke et al. | Dec 2009 | A1 |
20090323942 | Sharon et al. | Dec 2009 | A1 |
20100005270 | Jiang | Jan 2010 | A1 |
20100025811 | Bronner et al. | Feb 2010 | A1 |
20100030944 | Hinz | Feb 2010 | A1 |
20100058146 | Weingarten et al. | Mar 2010 | A1 |
20100064096 | Weingarten et al. | Mar 2010 | A1 |
20100088557 | Weingarten et al. | Apr 2010 | A1 |
20100091535 | Sommer et al. | Apr 2010 | A1 |
20100095186 | Weingarten | Apr 2010 | A1 |
20100110787 | Shalvi et al. | May 2010 | A1 |
20100115376 | Shalvi et al. | May 2010 | A1 |
20100122113 | Weingarten et al. | May 2010 | A1 |
20100124088 | Shalvi et al. | May 2010 | A1 |
20100131580 | Kanter et al. | May 2010 | A1 |
20100131806 | Weingarten et al. | May 2010 | A1 |
20100131809 | Katz | May 2010 | A1 |
20100131826 | Shalvi et al. | May 2010 | A1 |
20100131827 | Sokolov et al. | May 2010 | A1 |
20100131831 | Weingarten et al. | May 2010 | A1 |
20100146191 | Katz | Jun 2010 | A1 |
20100146192 | Weingarten et al. | Jun 2010 | A1 |
20100149881 | Lee et al. | Jun 2010 | A1 |
20100172179 | Gorobets et al. | Jul 2010 | A1 |
20100174853 | Lee et al. | Jul 2010 | A1 |
20100180073 | Weingarten et al. | Jul 2010 | A1 |
20100199149 | Weingarten et al. | Aug 2010 | A1 |
20100211724 | Weingarten | Aug 2010 | A1 |
20100211833 | Weingarten | Aug 2010 | A1 |
20100211856 | Weingarten | Aug 2010 | A1 |
20100241793 | Sugimoto et al. | Sep 2010 | A1 |
20100246265 | Moschiano et al. | Sep 2010 | A1 |
20100251066 | Radke | Sep 2010 | A1 |
20100253555 | Weingarten et al. | Oct 2010 | A1 |
20100257309 | Barsky et al. | Oct 2010 | A1 |
20100269008 | Leggette et al. | Oct 2010 | A1 |
20100293321 | Weingarten | Nov 2010 | A1 |
20100318724 | Yeh | Dec 2010 | A1 |
20110051521 | Levy et al. | Mar 2011 | A1 |
20110055461 | Steiner et al. | Mar 2011 | A1 |
20110093650 | Kwon et al. | Apr 2011 | A1 |
20110096612 | Steiner et al. | Apr 2011 | A1 |
20110099460 | Dusija et al. | Apr 2011 | A1 |
20110119562 | Steiner et al. | May 2011 | A1 |
20110153919 | Sabbag | Jun 2011 | A1 |
20110161775 | Weingarten | Jun 2011 | A1 |
20110194353 | Hwang et al. | Aug 2011 | A1 |
20110209028 | Post et al. | Aug 2011 | A1 |
20110214029 | Steiner et al. | Sep 2011 | A1 |
20110214039 | Steiner et al. | Sep 2011 | A1 |
20110246792 | Weingarten | Oct 2011 | A1 |
20110246852 | Sabbag | Oct 2011 | A1 |
20110252187 | Segal et al. | Oct 2011 | A1 |
20110252188 | Weingarten | Oct 2011 | A1 |
20110271043 | Segal et al. | Nov 2011 | A1 |
20110302428 | Weingarten | Dec 2011 | A1 |
20120001778 | Steiner et al. | Jan 2012 | A1 |
20120005554 | Steiner et al. | Jan 2012 | A1 |
20120005558 | Steiner et al. | Jan 2012 | A1 |
20120005560 | Steiner et al. | Jan 2012 | A1 |
20120008401 | Katz et al. | Jan 2012 | A1 |
20120008414 | Katz et al. | Jan 2012 | A1 |
20120017136 | Ordentlich et al. | Jan 2012 | A1 |
20120051144 | Weingarten et al. | Mar 2012 | A1 |
20120063227 | Weingarten et al. | Mar 2012 | A1 |
20120066441 | Weingarten | Mar 2012 | A1 |
20120110250 | Sabbag et al. | May 2012 | A1 |
20120124273 | Goss et al. | May 2012 | A1 |
20120246391 | Meir et al. | Sep 2012 | A1 |
Number | Date | Country |
---|---|---|
WO 2008053472 | May 2008 | WO |
Entry |
---|
Search Report of PCT Patent Application WO 2009/118720 A3. |
Search Report of PCT Patent Application WO 2009/095902 A3. |
Search Report of PCT Patent Application WO 2009/078006 A3. |
Search Report of PCT Patent Application WO 2009/074979 A3. |
Search Report of PCT Patent Application WO 2009/074978 A3. |
Search Report of PCT Patent Application WO 2009/072105 A3. |
Search Report of PCT Patent Application WO 2009/072104 A3. |
Search Report of PCT Patent Application WO 2009/072103 A3. |
Search Report of PCT Patent Application WO 2009/072102 A3. |
Search Report of PCT Patent Application WO 2009/072101 A3. |
Search Report of PCT Patent Application WO 2009/072100 A3. |
Search Report of PCT Patent Application WO 2009/053963 A3. |
Search Report of PCT Patent Application WO 2009/053962 A3. |
Search Report of PCT Patent Application WO 2009/053961 A3. |
Search Report of PCT Patent Application WO 2009/037697 A3. |
Yani Chen, Kcshab K. Parhi, “Small Area Parallel Chien Search Architectures for Long BCH Codes”, Ieee Transactions on Very Large Scale Integration(VLSI) Systems, vol. 12, No. 5, May 2004. |
Yuejian Wu, “Low Power Decoding of BCH Codes”, Nortel Networks, Ottawa, Ont., Canada, in Circuits and systems, 2004. ISCAS '04. Proceeding of the 2004 International Symposium on Circuits and Systems, published May 23-26, 2004, vol. 2, pp. II-369-72 vol. 2. |
Michael Purser, “Introduction to Error Correcting Codes”, Artech House Inc., 1995. |
Ron M. Roth, “Introduction to Coding Theory”, Cambridge University Press, 2006. |
Akash Kumar, Sergei Sawitzki, “High-Throughput and Low Power Architectures for Reed Solomon Decoder”, (a.kumar at tue.nl, Eindhoven University of Technology and sergei.sawitzki at philips.com). |
Todd K.Moon, “Error Correction Coding Mathematical Methods and Algorithms”, A John Wiley & Sons, Inc., 2005. |
Richard E. Blahut, “Algebraic Codes for Data Transmission”, Cambridge University Press, 2003. |
David Esseni, Bruno Ricco, “Trading-Off Programming Speed and Current Absorption in Flash Memories with the Ramped-Gate Programming Technique”, Ieee Transactions on Electron Devices, vol. 47, No. 4, Apr. 2000. |
Giovanni Campardo, Rino Micheloni, David Novosel, “VLSI-Design of Non-Volatile Memories”, Springer Berlin Heidelberg New York, 2005. |
John G. Proakis, “Digital Communications”, 3rd ed., New York: McGraw-Hill, 1995. |
J.M. Portal, H. Aziza, D. Nee, “EEPROM Memory: Threshold Voltage Built in Self Diagnosis”, ITC International Test Conference, Paper 2.1. |
J.M. Portal, H. Aziza, D. Nee, “EEPROM Diagnosis Based on Threshold Voltage Embedded Measurement”, Journal of Electronic Testing: Theory and Applications 21, 33-42, 2005. |
G. Tao, A. Scarpa, J. Dijkstra, W. Stidl, F. Kuper, “Data retention prediction for modern floating gate non volatile memories”, Microelectronics Reliability 40 (2000), 1561-1566. |
T. Hirncno, N. Matsukawa, H. Hazama, K. Sakui, M. Oshikiri, K. Masuda, K. Kanda, Y. Itoh, J. Miyamoto, “A New Technique for Measuring Threshold Voltage Distribution in Flash EEPROM Devices”, Proc. IEEE 1995 Int. Conference on Microelectronics Test Structures, vol. 8, Mar. 1995. |
Boaz Eitan, Guy Cohen, Assaf Shappir, Eli Lusky, Amichai Givant, Meir Janai, Ilan Bloom, Yan Polansky, Oleg Dadashev, Avi Lavan, Ran Sahar, Eduardo Maayan, “4-bit per Cell NROM Reliability”, Appears on the website of Saifun.com. |
Paulo Cappelletti, Clara Golla, Piero Olivo, Enrico Zanoni, “Flash Memories”, Kluwer Academic Publishers, 1999. |
Dempster, et al., “Maximum Likelihood from Incomplete Data via the EM Algorithm”, Journal of the Royal Statistical Society. Series B (Methodological), vol. 39, No. 1 (1997), pp. 1-38. |
Mielke, et al., “Flash EEPROM Threshold Instabilities due to Charge Trapping During Program/Erase Cycling”, IEEE Transactions on Device and Materials Reliability, vol. 4, No. 3, Sep. 2004, pp. 335-344. |
Daneshbeh, “Bit Serial Systolic Architectures for Multiplicative Inversion and Division over GF (2)”, A thesis presented to the University of Waterloo, Ontario, Canada, 2005, pp. 1-118. |
Chen, Formulas for the solutions of Quadratic Equations over GF (2), IEEE Trans. Inform. Theory, vol. IT-28, No. 5, Sep. 1982, pp. 792-794. |
Berlekamp et al., “On the Solution of Algebraic Equations over Finite Fields”, Inform. Cont. 10, Oct. 1967, pp. 553-564. |
Number | Date | Country | |
---|---|---|---|
61472557 | Apr 2011 | US |