Source: http://www.google.de/patents/US8751726
Timestamp: 2017-11-25 11:15:18
Document Index: 7512442

Matched Legal Cases: ['Application No. 61', 'Application No. 60', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 60', 'Application No. 61', 'Application No. 60', 'Application No. 61', 'Application No. 60', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 60', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61']

Patent US8751726 - System and methods employing mock thresholds to generate actual reading ... - Google Patentsuche
A method for reading at least one page within an erase sector of a flash memory device, the method comprising computing at least one mock reading threshold; using the at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within the...http://www.google.de/patents/US8751726?utm_source=gb-gplus-sharePatent US8751726 - System and methods employing mock thresholds to generate actual reading thresholds in flash memory devices
Veröffentlichungsnummer US8751726 B2
Anmeldenummer US 12/596,438
PCT-Nummer PCT/IL2008/001232
Auch veröffentlicht unter US8321625, US8341335, US8453022, US8843698, US9104550, US20100064096, US20100131809, US20100146191, US20100180073, US20130080691, US20130238839, WO2009072100A2, WO2009072100A3, WO2009072101A2, WO2009072101A3, WO2009072102A2, WO2009072102A3, WO2009072104A2, WO2009072104A3, WO2009072104A8
Veröffentlichungsnummer 12596438, 596438, PCT/2008/1232, PCT/IL/2008/001232, PCT/IL/2008/01232, PCT/IL/8/001232, PCT/IL/8/01232, PCT/IL2008/001232, PCT/IL2008/01232, PCT/IL2008001232, PCT/IL200801232, PCT/IL8/001232, PCT/IL8/01232, PCT/IL8001232, PCT/IL801232, US 8751726 B2, US 8751726B2, US-B2-8751726, US8751726 B2, US8751726B2
Patentzitate (322), Nichtpatentzitate (38), Referenziert von (2), Klassifizierungen (6), Juristische Ereignisse (5)
US 8751726 B2
A method for reading at least one page within an erase sector of a flash memory device, the method comprising computing at least one mock reading threshold; using the at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within the erase sector, thereby to generate a plurality of logical values; defining a set of reading thresholds based at least partly on the plurality of logical values; and reading at least one page in the erase sector using the set of reading thresholds.
1. A method for reading at least one page within an erase sector of a flash memory device, the method comprising: computing at least one mock reading threshold; wherein the mock threshold that is far from an adequate conventional reading threshold useful for reconstructing a logical value from a physical value residing in a flash memory cell; using said at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within said erase sector, thereby to generate a plurality of logical values; defining a set of reading thresholds based at least partly on said plurality of logical values; and reading at least one page in said erase sector using said set of reading thresholds.
2. A method according to claim 1 wherein said defining of a set of reading thresholds based at least partly on said plurality of logical values includes estimating a mean and standard deviation of at least one physical level over at least a portion of at least one page belonging to the erase sector of the flash memory device based on said at least one mock reading operation.
3. A method according to claim 2 wherein said estimating is performed for at least a first physical level residing above a second physical level and below a third physical level and wherein estimating the mean and standard deviations of said first physical level comprises interpolating between previously found means and standard deviations of said second and third levels.
4. A method for rapidly assessing functionality of erase sectors in a flash memory, the method comprising: estimating a mean and standard deviation of at least one physical level over at least a portion of at least one page belonging to an erase sector of a flash memory device; wherein said estimating is performed for at least a first physical level residing above a second physical level and below a third physical level and wherein estimating the mean and standard deviations of said first physical level comprises interpolating between previously found means and standard deviations of said second and third levels.
5. A method according to claim 1 wherein said defining of a set of reading thresholds based at least partly on said plurality of logical values includes identifying at least one non-populous region of a predetermined size, within a distribution of physical values of a population of cells belonging to a page within the erase sector.
6. A method according to claim 5 wherein at least one reading threshold in said set of reading thresholds is determined to be a central value within said non-populous region.
7. A method for assessing effects of retention and cycling on individual erase sectors in a flash memory which has undergone retention and cycling, the method comprising: receiving a first centerpoint of a rightmost lobe of a distribution of physical values within the cells of a new flash memory device and a second centerpoint of a rightmost lobe of a distribution of physical values within the cells of an entirely degraded flash memory device; generating a histogram representing distribution of physical values within the cells of an individual erase sector, over a range extending at least between said second and first centerpoints; and computing at least one statistic of a rightmost lobe of the histogram.
8. A method according to claim 7 wherein said at least one statistic comprises at least one of a mean and a standard deviation.
9. A method according to claim 1 wherein said defining comprises seeking a local maximum in a threshold voltage distribution and determining at least one reading threshold based at least partly on said local maximum.
10. A method according to claim 1 wherein said defining comprises seeking a local minimum in a threshold voltage distribution and determining at least one reading threshold based at least partly on said local minimum.
11. A method according to claim 1 wherein said defining comprises: identification of a threshold voltage distribution of a highest program level in a probability distribution of physical values within said erase sector; and preventing misidentification of the threshold voltage distribution of the highest program level by comparing the number of cells whose threshold voltage is larger than the candidate maximizing voltage, to a threshold.
12. A method according to claim 1 and also comprising guaranteeing a similar number of cells in each program level.
13. A method according to claim 1 wherein, each time said computing, using, defining and reading are performed, said reading thresholds as most recently modified are stored in a data base in association with characterization information, said method also comprising, for at least one page in said erase sector: accessing said data base and reviewing at least some of said characterization information to determine whether said database includes reading thresholds suitable for said page; if said database does include suitable thresholds, using said suitable thresholds to read said page; and if said database does not include suitable thresholds, performing said computing, using, defining and reading steps for said page.
14. A method according to claim 13 wherein said characterization information includes:
identification of row neighborhood, number of program/erase cycles which rows in said row neighborhood underwent, and retention period which rows in said row neighborhood endured.
15. A method according to claim 12 wherein said guaranteeing comprises scrambling of bits stored in said erase sector.
16. A system for reading at least one page within an erase sector of a flash memory device, the system comprising: mock threshold computation apparatus operative to compute at least one mock reading threshold; wherein the mock threshold that is far from an adequate conventional reading threshold useful for reconstructing a logical value from a physical value residing in a flash memory cell; a reading threshold set generator operative to define a set of reading thresholds based at least partly on said plurality of logical values; and reading apparatus using said at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within said erase sector, thereby to generate a plurality of logical values and subsequently using said set of reading thresholds based at least partly on said plurality of logical values to read at least one page in said erase sector using said set of reading thresholds.
17. A system for rapidly assessing functionality of erase sectors in a flash memory, the system comprising: flash memory physical level distribution statistic estimation apparatus estimating a mean and standard deviation of at least one physical level over at least a portion of at least one page belonging to an erase sector of a flash memory device and including interpolation apparatus, wherein said apparatus receives and operates upon at least a first physical level residing above a second physical level and below a third physical level by using said interpolation apparatus to interpolate between previously found means and standard deviations of said second and third levels.
18. A system for assessing effects of retention and cycling on individual erase sectors in a flash memory which has undergone retention and cycling, the system comprising: a histogram generator operative to generate a histogram representing distribution of physical values within the cells of an individual erase sector, over a range extending at least between a first centerpoint of a rightmost lobe of a distribution of physical values within the cells of a new flash memory device and a second centerpoint of a rightmost lobe of a distribution of physical values within the cells of an entirely degraded flash memory device; and a rightmost lobe analyzer operative to compute at least one statistic of a rightmost lobe of the histogram.
19. A method according to claim 1 wherein said computing comprises translating the mock reading thresholds along a physical value axis of a probability distribution of physical values within said erase sector, according to at least one characteristic of a highest program level within said probability distribution.
This application is a National Phase of PCT International Application No. PCT/IL2008/001232, entitled “SYSTEM AND METHODS EMPLOYING MOCK THRESHOLDS TO GENERATE ACTUAL READING THRESHOLDS IN FLASH MEMORY DEVICE”, International Filing Date Sep. 17, 2008, published on Jun. 11, 2009 as International Publication No. WO 2009/072102, which in turn claims priority from U.S. Provisional Application No. 61/129,608, filed Jul. 8, 2008, U.S. Provisional Application No. 60/996,782, filed Dec. 5, 2007, U.S. Provisional Application No. 61/064,853, filed Mar. 31, 2008, U.S. Provisional Application No. 61/006,805, filed Jan. 31, 2008, U.S. Provisional Application No. 61/071,465, filed Apr. 30, 2008, all of which are incorporated herein by reference in their entirety.
Other co-pending applications include: U.S. Provisional Application No. 60/960,207, filed Sep. 20, 2007 and entitled “Systems and Methods for Coupling Detection in Flash Memory”, U.S. Provisional Application No. 61/071,467, filed Apr. 30, 2008 and entitled “Improved Systems and Methods for Determining Logical Values of Coupled Flash Memory Cells”, U.S. Provisional Application No. 60/960,943, filed Oct. 22, 2007 and entitled “Systems and methods to reduce errors in Solid State Disks and Large Flash Devices” and U.S. Provisional Application No. 61/071,469, filed Apr. 30, 2008 and entitled “Systems and Methods for Averaging Error Rates in Non-Volatile Devices and Storage Systems”, U.S. Provisional Application No. 60/996,027, filed Oct. 25, 2007 and entitled “Systems and Methods for Coping with Variable Bit Error Rates in Flash Devices”, U.S. Provisional Application No. 61/071,466, filed Apr. 30, 2008 and entitled “Systems and Methods for Multiple Coding Rates in Flash Devices”, U.S. Provisional Application No. 61/006,120, filed Dec. 19, 2007 and entitled “Systems and Methods for Coping with Multi Stage Decoding in Flash Devices”, U.S. Provisional Application No. 61/071,464, filed Apr. 30, 2008 and entitled “A Decoder Operative to Effect A Plurality of Decoding Stages Upon Flash Memory Data and Methods Useful in Conjunction Therewith”, U.S. Provisional Application No. 61/006,385, filed Jan. 10, 2008 and entitled “A System for Error Correction Encoder and Decoder Using the Lee Metric and Adapted to Work on Multi-Level Physical Media”, U.S. Provisional Application No. 61/064,995, filed Apr. 8, 2008 and entitled “Systems and Methods for Error Correction and Decoding on Multi-Level Physical Media”, U.S. Provisional Application No. 60/996,948, filed Dec. 12, 2007 and entitled “Low Power BCH/RS Decoding: a Low Power Chien-Search Implementation”, U.S. Provisional Application No. 61/071,487, filed May 1, 2008 and entitled “Chien-Search System Employing a Clock-Gating Scheme to Save Power for Error Correction Decoder and other Applications”, U.S. Provisional Application No. 61/071,468, filed Apr. 30, 2008 and entitled “A Low Power Chien-Search Based BCH/RS Recoding System for Flash Memory, Mobile Communications Devices and Other Applications”, U.S. Provisional Application No. 61/006,806, filed Jan. 31, 2008 and entitled “Systems and Methods for using a Erasure Coding in Flash memory”, U.S. Provisional Application No. 61/071,486, filed May 1, 2008 and entitled “Systems and Methods for Handling Immediate Data Errors in Flash Memory”, U.S. Provisional Application No. 61/006,078, filed Dec. 18, 2007 and entitled “Systems and Methods for Multi Rate Coding in Multi Level Flash Devices”, U.S. Provisional Application No. 61/064,923, filed Apr. 30, 2008 and entitled “Apparatus For Coding At A Plurality Of Rates In Multi-Level Flash Memory Systems. And Methods Useful In Conjunction Therewith”, U.S. Provisional Application No. 61/064,760, filed Mar. 25, 2008 and entitled “Hardware efficient implementation of rounding in fixed-point arithmetic”, U.S. Provisional Application No. 61/071,404, filed Apr. 28, 2008 and entitled “Apparatus and Methods for Hardware-Efficient Unbiased Rounding”, U.S. Provisional Application No. 61/136,234, filed Aug. 20, 2008 and entitled “A Method Of Reprogramming A Non-Volatile Memory Device Without Performing An Erase Operation”, U.S. Provisional Application No. 61/129,414, filed Jun. 25, 2008 and entitled “Improved Programming Speed in Flash Devices Using Adaptive Programming”, and several other co-pending patent applications being filed concurrently (same day).
[4] “4-Bit-Per-Cell NROM Reliability”. Boaz Eitan, Guy Cohen, Assaf Shappir, Eli Lusky, Amichai Givant, Meir Janai, Ilan Bloom, Yan Polansky, Oleg Dadashev, Avi Lavan, Ran Sahar and Eduardo Maayan. Appears on the website of Saifun.com.
[5] Portal, J. M. et al. “EEPROM Diagnosis Based on Threshold Voltage Embedded Measurement”. Journal of Electronic Testing: Theory and Applications Volume 21, Issue 1 (January 2005)
[6] Himeno, T.; Matsukawa, N.; Hazama, H.; Sakui, K.; Oshikiri, M.; Masuda, K.; Kanda, K.; Itoh, Y.; Miyamoto, J. “A new technique for measuring threshold voltage distribution in flash EEPROM devices.” Microelectronic Test Structures, 1995. ICMTS 1995. Proceedings of the 1995 International Conference on Volume, Issue, 22-25 Mar. 1995 Page(s):283-287 Digital Object Identifier 10.1109/ICMTS.1995.513988
[7] G. Tao, A. Scarpa, J. Dijkstra, W. Stidl and F. Kuper, “Data retention prediction for modern floating gate non-volatile memories”, Microelectronics Reliability, Volume 40, Issues 8-10, August-October 2000, Pages 1561-1566
[8] Esseni, D., “Trading-off programming speed and current absorption in flash memories with the ramped-gate programming technique”, IEEE Transactions on Electron Devices, 47(4), April 2000.
[9] Portal, J. M. “EEPROM Memory: Threshold voltage built in self diagnosis”, ITC International Test Conference, Paper 2.1.
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, n may or may not be an integer. “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.
“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.
Certain embodiments of the present invention seek to provide improved flash memory apparatus.
There is thus provided, in accordance with at least one embodiment of the present invention, a method for reading at least one page within an erase sector of a flash memory device, the method comprising computing at least one mock reading threshold; using the at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within the erase sector, thereby to generate a plurality of logical values; defining a set of reading thresholds based at least partly on the plurality of logical values; and reading at least one page in the erase sector using the set of reading thresholds.
Further in accordance with at least one embodiment of the present invention, the defining of a set of reading thresholds based at least partly on the plurality of logical values includes estimating a mean and standard deviation of at least one physical level over at least a portion of at least one page belonging to the erase sector of the flash memory device based on the at least one mock reading operation.
Still further in accordance with at least one embodiment of the present invention, the estimating is performed for at least a first physical level residing above a second physical level and below a third physical level and wherein estimating the mean and standard deviations of the first physical level comprises interpolating between previously found means and standard deviations of the second and third levels.
An advantage of the embodiment described above is that a significant amount of computation is saved since it is not necessary to generate a histogram for intermediate physical levels if histograms for physical levels on both sides are known. It is appreciated that alternatively or in addition to claim 3, estimating may be performed for a first physical level even if it does not reside above the second physical level and below the third physical level by extrapolating suitably between previously found means and standard deviations of the second and third levels.
Also provided, in accordance with another embodiment of the present invention, is a method for rapidly assessing functionality of erase sectors in a flash memory, the method comprising estimating a mean and standard deviation of at least one physical level over at least a portion of at least one page belonging to an erase sector of a flash memory device; wherein the estimating is performed for at least a first physical level residing above a second physical level and below a third physical level and wherein estimating the mean and standard deviations of the first physical level comprises interpolating between previously found means and standard deviations of the second and third levels.
Further in accordance with at least one embodiment of the present invention, the defining of a set of reading thresholds based at least partly, on the plurality of logical values includes identifying at least one non-populous region of a predetermined size, within a distribution of physical values of a population of cells belonging to a page within the erase sector.
It is appreciated that non-populous does not mean non-populated i.e. the non-populous regions include only a small number of values but not necessarily zero values.
Still further in accordance with at least one embodiment of the present invention, at least one reading threshold in the set of reading thresholds is determined to be a central value within the non-populous region.
Also provided, in accordance with still another embodiment of the present invention, is a method for assessing effects of retention and cycling on individual erase sectors in a flash memory which has undergone retention and cycling, the method comprising receiving a first centerpoint of a rightmost lobe of a distribution of physical values within the cells of a new flash memory device and a second centerpoint of a rightmost lobe of a distribution of physical values within the cells of an entirely degraded flash memory device; generating a histogram representing distribution of physical values within the cells of an individual erase sector, over a range extending at least between the second and first centerpoints; and computing at least one statistic of a rightmost lobe of the histogram. It is appreciated that there may be only one lobe.
Further in accordance with at least one embodiment of the present invention, at least one statistic comprises at least one of a mean and a standard deviation.
Still further in accordance with at least one embodiment of the present invention, the defining comprises seeking a local maximum in a threshold voltage distribution and determining at least one reading threshold based at least partly on the local maximum.
Additionally in accordance with at least one embodiment of the present invention, the defining comprises seeking a local minimum in a threshold voltage distribution and determining at least one reading threshold based at least partly on the local minimum.
Further in accordance with at least one embodiment of the present invention, the defining comprises identification of a threshold voltage distribution of a highest program level in a probability distribution of physical values within the erase sector; and preventing misidentification of the threshold voltage distribution of the highest program level by comparing the number of cells whose threshold voltage is larger than the candidate maximizing voltage, to a threshold.
Still further in accordance with at least one embodiment of the present invention, the method also comprises guaranteeing a similar number of cells in each program level.
Additionally in accordance with at least one embodiment of the present invention, each time the computing, using, defining and reading are performed, the reading thresholds as most recently modified are stored in a data base in association with characterization information, and the method also comprises, for at least one page in the erase sector: accessing the data base and reviewing at least some of the characterization information to determine whether the database includes reading thresholds suitable for the page; if the database does include suitable thresholds, using the suitable thresholds to read the page; and if the database does not include suitable thresholds, performing the computing, using, defining and reading steps for the page. The database is termed herein “threshold history data base”.
It typically stores, as time goes on, a set of thresholds for each row or group of adjacent rows, but not for each erase sector but rather for each category of erase sectors. Typically, a category of erase sectors comprises a set of erase sectors which share a common range of cycling indices and a common range of retention durations. For example, the first category may comprise erase sectors which have undergone up to 100 cycles and whose retention duration is up to 1 month. The second category may comprise erase sectors which have undergone from 101 to 200 cycles and whose retention duration is up to 1 month, and so on, up to a 50th category which may comprise erase sectors which have undergone from 4901 up to 5000 cycles and whose retention duration is up to 1 month. The 51st to 100 categories may comprise erase sectors which have undergone 0-100, 101-200 etc. cycles respectively, and whose retention duration is between 1 and 2 months. The 101th to 150th categories may comprise erase sectors which have undergone 0-100, 101-200 etc. cycles respectively, and whose retention duration is between 2 and 3 months, etc. and so forth, with steps of 1 month between categories for the first year. From the first year to the tenth year, the retention duration increment between categories may be 1 year rather than a single month. The cycling index increment between categories may be uniform e.g. 100 cycles as in this example.
Further in accordance with at least one embodiment of the present invention, the characterization information includes: identification of row neighborhood, number of program/erase cycles which rows in the row neighborhood underwent, and retention period which rows in the row neighborhood endured.
Additionally in accordance with at least one embodiment of the present invention, the guaranteeing comprises scrambling of bits stored in the erase sector. Scrambling may be carried out by the scrambler/descrambler described herein.
Also provided, in accordance with yet another embodiment of the present invention, is a system for reading at least one page within an erase sector of a flash memory device, the system comprising mock threshold computation apparatus operative to compute at least one mock reading threshold; a reading threshold set generator operative to define a set of reading thresholds based at least partly on the plurality of logical values; and reading apparatus using the at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within the erase sector, thereby to generate a plurality of logical values and subsequently using the set of reading thresholds based at least partly on the plurality of logical values to read at least one page in the erase sector using the set of reading thresholds.
Still further provided, in accordance with still another embodiment of the present invention, is a system for rapidly assessing functionality of erase sectors in a flash memory, the system comprising flash memory physical level distribution statistic estimation apparatus estimating a mean and standard deviation of at least one physical level over at least a portion of at least one page belonging to an erase sector of a flash memory device and including interpolation apparatus, wherein the apparatus receives and operates upon at least a first physical level residing above a second physical level and below a third physical level by using the interpolation apparatus to interpolate between previously found means and standard deviations of the second and third levels.
Also provided, in accordance with another embodiment of the present invention, is a system for assessing effects of retention and cycling on individual erase sectors in a flash memory which has undergone retention and cycling, the system comprising a histogram generator operative to generate a histogram representing distribution of physical values within the cells of an individual erase sector, over a range extending at least between a first centerpoint of a rightmost lobe of a distribution of physical values within the cells of a new flash memory device and a second centerpoint of a rightmost lobe of a distribution of physical values within the cells of an entirely degraded flash memory device; and a rightmost lobe analyzer operative to compute at least one statistic of a rightmost lobe of the histogram.
Further in accordance with at least one embodiment of the present invention, the computing comprises translating the mock reading thresholds along a physical value axis of a probability distribution of physical values within the erase sector, according to at least one characteristic of a highest program level within the probability distribution.
According to certain embodiments, an average or central value of a highest lobe in a probability density function graph of logical values read from flash memory may be found, by defining mock thresholds between maximal values identified for a new flash memory device and minimal values identified for an extremely run down (high retention, high cycle count) flash memory device. To do this, a new flash memory device may be taken up at a set up stage, and a large number of cells therein, perhaps one erase-sector full, may be programmed to their highest levels. The erase sector is read, using suitable thresholds whose intervals define a suitable resolution, to determine the location of the top edge of the highest (rightmost) lobe. An extremely run-down flash memory device is then taken up, also at the set up stage, and a large number of cells therein, perhaps one erase-sector full, may be programmed to their highest levels.
The erase sector is read, using suitable thresholds whose intervals define a suitable resolution, to determine the location of the bottom edge of the lowest (leftmost) lobe. It can then be assumed to be the case, that any flash memory device's highest lobe falls within the window between the known bottom edge of the lowest lobe of the run-down flash memory, and the known top edge of the highest lobe of the new flash memory. This is helpful, for example, when it is desired to define mock reading thresholds to identify the location of a highest lobe of a probability density function of an individual flash memory device, wherein the mock reading thresholds are to span all possible locations of the highest lobe. This can be done by distributing mock reading thresholds throughout the entire window described above.
Any suitable processor, display and input means may be used to process, display, store and accept information, including computer programs, in accordance with some or all of the teachings of the present invention, such as but not limited to a conventional personal computer processor, workstation or other programmable device or computer or electronic computing device, either general-purpose or specifically constructed, for processing; a display screen and/or printer and/or speaker for displaying; machine-readable memory such as optical disks, CDROMs, magnetic-optical discs or other discs; RAMs, ROMs, EPROMs, EEPROMs, magnetic or optical or other cards, for storing, and keyboard or mouse for accepting. The term “process” as used above is intended to include any type of computation or manipulation or transformation of data represented as physical, e.g. electronic, phenomena which may occur or reside e.g. within registers and for memories of a computer.
FIG. 1A is a simplified flowchart illustration of a generalized method for reading at least one page within an erase sector of a flash memory device, the method being operative in accordance with certain embodiments of the present invention;
FIG. 1B is a simplified block diagram of a flash memory system constructed and operative in accordance with certain embodiments of the present invention;
FIGS. 2A-2B, taken together, form a simplified flowchart illustration of an example method implementing the generalized method of FIG. 1A, the method of FIGS. 2A-2B being operative in accordance with certain embodiments of the present invention;
FIG. 3 is a simplified flowchart illustration of a method for performing step 210 of FIG. 2A, the method being operative in accordance with certain embodiments of the present invention;
FIG. 4 is a simplified flowchart illustration of a method for performing step 220 of FIG. 2A, the method being operative in accordance with certain embodiments of the present invention;
FIG. 5 is a simplified flowchart illustration of a method for performing step 240 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 6 is a simplified flowchart illustration of a method for performing step 500 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention;
FIG. 7 is a simplified flowchart illustration of a method for performing step 510 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention;
FIG. 8 is a simplified flowchart illustration of a method for performing step 520 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention;
FIG. 9 is a simplified flowchart illustration of a method for performing step 530 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention;
FIG. 10A-10B, taken together, form a simplified flowchart illustration of a method for performing step 260 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 11 is a simplified flowchart illustration of a method for performing step 270 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 12 is a simplified flowchart illustration of a method for performing step 280 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 13A-13B, taken together, form a simplified flowchart illustration of a method for performing step 290 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 14 is a simplified flowchart illustration of a method for performing step 1350 of FIG. 13B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 15 is a simplified flowchart illustration of a method for performing step 300 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention;
FIG. 16 is a simplified flowchart illustration of a method for performing step 202 of FIG. 2A, the method being operative in accordance with certain embodiments of the present invention;
FIG. 17 is a simplified flowchart illustration of a method for performing step 1620 of FIG. 16, the method being operative in accordance with certain embodiments of the present invention;
FIG. 18 is a simplified electronic diagram of a linear feedback shift register suitable for implementing a scrambler/descrambler as described herein with reference also to FIG. 27;
FIG. 19 (prior art) is a simplified theoretical probability density function v, voltage graph showing voltage distributions of program levels, in which the vertical axis represents theoretical physical values conditional on programmed levels;
FIG. 20 is a graph of a threshold voltage distribution of a highest program level which is useful in understanding the highest program level mean and standard deviation fine estimation methods shown and described herein;
FIG. 21 is a graph of a threshold voltage distribution of an intermediate program level which is useful in understanding the intermediate program level mean and standard deviation fine estimation methods shown and described herein;
FIG. 22 is a graph of adaptive voltage intervals for estimation of means and standard deviations of intermediate program levels as shown and described herein;
FIG. 23 is an example of a data structure for a Threshold history table which may be searched using the method of FIG. 4 and maintained using the method of FIG. 15;
FIG. 24 is a simplified diagram of Detection thresholds sets useful in accordance with certain embodiments of the present invention;
FIG. 25 is a simplified flowchart illustration of a method for rapidly assessing functionality of erase sectors in a flash memory operative in accordance with certain embodiments of the present invention;
FIG. 26 is a simplified flowchart illustration of a method for assessing effects of retention and cycling on individual erase sectors in a flash memory which has undergone retention and cycling, operative in accordance with certain embodiments of the present invention; and
FIG. 27 is a simplified functional block diagram of the external controller of FIG. 1B, according to certain embodiments of the present invention.
Reference is now made to FIG. 1A which is a simplified generally self-explanatory flowchart illustration of a generalized method for reading at least one page within an erase sector of a flash memory device, the method being operative in accordance with certain embodiments of the present invention. The method of FIG. 1A typically includes some or all of the following steps, suitably ordered, e.g. as shown:
Step 100: computing at least one mock reading threshold. A mock threshold is a threshold which is far from being an adequate conventional reading threshold useful for reconstructing a logical value from a physical value residing in a flash memory cell. While the mock threshold is used as an input to a reading process, as though it were a true reading threshold, its utility differs. For example, mock thresholds may be used to ascertain the state of health of an erase sector at a certain point in time. Mock thresholds may be used as a reflection of the current locations and shapes of the various lobes of the probability density functions, as shown in FIG. 19, of a particular erase sector or entire flash memory device.
Step 110: using the at least one mock reading threshold to perform at least one mock read operation of at least a portion of at least one page within the erase sector, thereby to generate a plurality of logical values.
Step 120: defining a set of reading thresholds based at least partly on the plurality of logical values.
Step 130: reading at least one page in the erase sector using the set of reading thresholds.
Reference is now made to FIG. 1B which is a simplified block diagram of a flash memory system constructed and operative in accordance with certain embodiments of the present invention. As shown, the flash memory system of FIG. 1B includes a host or outside application 100 which interfaces, via an interface controller 102 operative to generate “genuine” reading thresholds from “mock” reading threshold indicative of flash memory health. The controller 102 is typically operative to perform some or all of the methods shown and described herein such as the methods of FIGS. 1A and 2A-2B, with a flash memory device 105. FIG. 27 is a simplified functional block diagram of the controller 102 according to certain embodiments of the present invention.
An internal microcontroller 110 typically manages the functional units of the flash memory device 105. The storage portion of the flash memory device includes one or more typically many erase sectors 120 each storing one or more typically many physical pages 130 each including one or more typically many cells 140 having more than one possible state such that logical values may be stored therein. Erasing circuitry 150 is provided to erase data from cells, writing circuitry 160 writes data into cells, and reading circuitry 170 reads data from cells.
FIGS. 2A-2B, taken together, form a simplified generally self-explanatory flowchart illustration of an example method implementing the generalized method of FIG. 1A, the method of FIGS. 2A-2B being operative in accordance with certain embodiments of the present invention.
FIG. 3 is a simplified generally self-explanatory flowchart illustration of a method for performing step 210 of FIG. 2A, the method being operative in accordance with certain embodiments of the present invention.
FIG. 4 is a simplified generally self-explanatory flowchart illustration of a method for performing step 220 of FIG. 2A, the method being operative in accordance with certain embodiments of the present invention. FIG. 2B provides detail of step 235 in FIG. 2A. It is appreciated that a decision as to whether or not a tail effect is present, which impacts on appropriate action which may be taken in each case, occurs in step 280. A “tail effect” is defined herein as a situation in which the right tail of the probability density function of the physical value of a cell decays much slower than the Gaussian probability density. Such a situation can be detected empirically by generating a histogram with a fine grid over the entire voltage range, thereby effectively “taking a picture” of the probability function of the physical values. By examining this distribution it is possible to identify program levels which may exhibit excessive tails in their distribution.
FIG. 5 is a simplified generally self-explanatory flowchart illustration of a method for performing step 240 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention.
FIG. 6 is a simplified generally self-explanatory flowchart illustration of a method for performing step 500 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention.
FIG. 7 is a simplified generally self-explanatory flowchart illustration of a method for performing step 510 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention.
FIG. 8 is a simplified generally self-explanatory flowchart illustration of a method for performing step 520 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention.
FIG. 9 is a simplified generally self-explanatory flowchart illustration of a method for performing step 530 of FIG. 5, the method being operative in accordance with certain embodiments of the present invention.
FIG. 10A-10B, taken together, form a simplified generally self-explanatory flowchart illustration of a method for performing step 260 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention.
FIG. 11 is a simplified generally self-explanatory flowchart illustration of a method for performing step 270 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention.
FIG. 12 is a simplified generally self-explanatory flowchart illustration of a method for performing step 280 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention.
FIG. 13A-13B, taken together, form a simplified generally self-explanatory flowchart illustration of a method for performing step 290 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention.
FIG. 14 is a simplified generally self-explanatory flowchart illustration of a method for performing step 1350 of FIG. 13B, the method being operative in accordance with certain embodiments of the present invention.
FIG. 15 is a simplified generally self-explanatory flowchart illustration of a method for performing step 300 of FIG. 2B, the method being operative in accordance with certain embodiments of the present invention. In step 1560, T1 may be stored in MSB thresholds (T1) of thresholds (1 BPC) of RowEntry (r, c, t). In step 1570, T2 may be stored in MSB thresholds (T2) of thresholds (2 BPC) of RowEntry (r, c, t). T1 and T3 may be stored in CSB thresholds (T1, T3) of thresholds (2 BPC) of RowEntry (r, c, t). In step 1580, T4 may be stored in MSB thresholds (T4) of thresholds (3 BPC) of RowEntry (r, c, t). T2 and T6 may be stored in CSB thresholds (T2, T6) of thresholds (3 BPC) of RowEntry (r, c, t). T1, T3, T5 and T7 may be stored in LSB thresholds (T1, T3, T5, T7) of thresholds (3 BPC) of RowEntry (r, c, t).
The acronyms MSB, LSB and CSB are used herein to denote most significant, least significant, and intermediately significant (e.g. in 3-bit-per-cell applications) bits respectively.
FIG. 16 is a simplified generally self-explanatory flowchart illustration of a method for performing step 202 of FIG. 2A, the method being operative in accordance with certain embodiments of the present invention.
FIG. 17 is a simplified generally self-explanatory flowchart illustration of a method for performing step 1610 of FIG. 16, the method being operative in accordance with certain embodiments of the present invention.
FIG. 18 is a simplified generally self-explanatory electronic diagram of a linear feedback shift register suitable for implementing the scrambler/descrambler of FIG. 27.
Design considerations may take into account the following: Conventional flash memory devices store information as charge in “cells”, each made of either a floating gate transistor or an NROM transistor. In single-level cell (SLC) devices, each cell stores only one bit of information. Multi-level cell (MLC) devices can store more than one bit per cell by choosing between multiple levels of electrical charge to apply to the floating gates of their cells. The amount of charge (also known as charge level) is then measured by a detector, by comparing the voltage of the transistor gate (also known as charge level and denoted VT) to a decision threshold voltage (also known as charge level boundary point and denoted VD). The amount of charge is then used to determine the programmed level (logical value) of the cell. Due to inaccuracies during the programming procedure and charge loss due to time and temperature (also known as retention), the measured levels suffer from a random distortion.
FIG. 19 illustrates an example of the eight (8) separate probability distributions of a cell which can be programmed with one of eight (8) corresponding program levels (111, 110, 100, 101, 001, 000, 010, and 011, respectively). For each distribution curve, the Y-axis represents the probability that the cell is programmed to the corresponding level, given the value of the charge level VT (represented by the x-axis).
The cell's programmed level may be determined using several methods. One method is to apply a voltage to the cell's gate and measure if the cell conducts current. The cell has a certain threshold voltage such that if voltage above that threshold is applied to the gate, the gate will conduct. Bellow that threshold voltage the gate will not conduct current (or will conduct a small amount of current, below a certain demarcation level). As the amount of charge in the cell changes this threshold voltage, the charge may be inferred by determining at which voltage the cell starts to conduct current. Thus, the programmed level is determined by iteratively applying different voltages to the gate and measuring whether the cells conduct or not. Another method is based on the fact that when applying a voltage above the threshold voltage, the cell conducts current and the amount of current depends on the difference between the applied voltage and the threshold voltage. As the threshold voltage changes as a function of the amount of charge in the cell, the programmed level may be inferred by measuring the current going through the cell.
Thus, the programmed level may be obtained by simultaneously comparing the conducted current with a given set of fixed currents distinguishing between all programmed levels. In other words, each cell's programmed level is determined by simultaneously comparing the VT level against several decision threshold levels (reading thresholds). For example, if there are eight (8) possible programmed levels, the cell's VT is simultaneously compared against seven decision threshold levels which divide the voltage axis into eight (8) regions, as shown in FIG. 19.
In general, if there are L possible program levels, then L-1 decision threshold levels are employed. As the probability distributions extend beyond the decision threshold levels, there is a probability of detection error, i.e. detecting the wrong program level. In order to minimize the detection error, one wishes to set the decision threshold levels optimally. The optimal placement of the decision thresholds levels in terms of minimizing the detection error probability generally depends on the probability distribution associated with the VT level of the cells. The statistical behavior of the cells' VT level can be approximated by Gaussian distributions. The optimal placement of the reading threshold for the Gaussian case is a known function, as described e.g. in the above-referenced publication by Proakis, of the means and standard deviations (STDs) of the Gaussian distributions. In other words, knowledge of good decision thresholds (assuming the Gaussian assumption is correct) is possible if the means and standard deviations of the cells' VT distributions are known.
Since the means and standard deviations of the probability distributions change as a result of cycling and retention, it is not clear how to set the decision thresholds when attempting to read a given page storing information. Setting the decision thresholds to the optimal position corresponding to a fresh flash device might show acceptable performance only if the page was recently programmed and not retained for a significant amount of time. Similarly, setting the decision thresholds to fit a device which was cycled 1000 times and retained for 10 years might not work, i.e. cause too many detection errors, if the page in question was recently written to a non-cycled flash device.
This situation calls for a training stage in which the flash device's controller learns the “state” of the page/block and determines a set of decision thresholds which will yield preferably as little detection errors as possible when used to read the page. One method for performing training involves estimating the state of the flash device from the data bearing cells themselves in order to deduce appropriate reading thresholds without any a-priori knowledge of the data stored in these cells.
The training procedures mentioned above could be performed prior to the reading of every page. In some applications, this approach might turn out expensive in terms of a system's resources. It is therefore important to find ways in which the training procedure comes into play less frequently. One such way, which utilizes a data base of previously obtained training information is described herein.
Certain embodiments of the present invention allow generation of reading threshold values for use when reading data from cells of a flash memory device, without incurring any penalty in terms of a reduction in the number of available cells used for storing data (e.g., without using a “training-sequence”). This is done by employing a “blind” training method in which the probability distributions of the cells' VT level is estimated based on the actual data bearing cells, whose actual content is in general unknown to the controller. Estimation of the probability distribution of each program level is done by successive read operations which are carried out over the entire page (or a large part thereof) in an appropriate voltage interval. The results of the read operations are translated into an approximate histogram of VT levels corresponding to a specific program level, and the probability distribution is estimated based on this histogram. Certain embodiments of this invention also include some refinements which allow to trade-off complexity vs. performance, as well as to improve performance in the presence of certain types of non-Gaussian statistics.
Other embodiments of this invention include the usage of a threshold history data base which keeps a list of previously obtained reading thresholds. The data base is organized and used based on the assumption that distinct erase blocks with a similar degradation state, i.e. with a similar cycling counter and similar duration of retention, behave statistically the same. This implies that thresholds which exist in the data base and which were obtained from a certain block with certain degradation characteristics can be used to successfully read another page within another erase block which has undergone similar degradation.
According to certain embodiments, a method for evaluating the unknown degradation state of a first erase block based on certain characteristics indicative of degradation, such as but not limited to cycling index and retention duration, is provided. The first erase block is matched with a second erase block sharing the same characteristics, whose degradation state is known. If the two erase blocks share the same characteristics, the known degradation state of the second is taken to be the degradation state of the first.
For clarity, the specification and drawings at times relate specifically to a flash memory device where each cell has eight (8) possible charge levels (or program levels), thus storing 3 bits per cell. It is appreciated however that certain embodiments of this invention are also applicable to flash devices with less or more charge levels. The page to be read has typically been written to a flash device after an unknown number of program/erase cycles, and the data in the page has been retained for an unknown period of time. Denote the number of cells in the page by Nc. Denote the means of the cells' VT level distributions by μ1, μ2 . . . , μ8, where the index 1 corresponds to the erase level, index 2 corresponds to the program level closest to the erased state, and so on. Furthermore, denote by σ1, σ2, . . . , σ8, the standard deviations (STDs) of these distributions, respectively. Finally, denote by T1, T2 . . . , T7, the reading thresholds which are to be used for reading the page. An approximation to the optimal reading thresholds is given by the following formulae, e.g. as described herein in FIG. 2B, step 280 and in FIG. 12:
Fine Estimation of the Mean and standard deviation of the Highest Program Level, according to certain embodiments of the present invention, is now described in detail.
In one embodiment of the present invention, the mean and standard deviation of the probability distribution of the VT level of the cells programmed to the highest program level are estimated e.g. as illustrated herein in FIG. 2B at step 240 and in FIG. 5. An example of the threshold voltage distribution of the two (2) highest program levels is shown in FIG. 20. The solid line corresponds to a fresh cell which underwent little (if any) program-erase cycles and whose data was retained for a very short period of time. The (Gaussian) probability distribution of the threshold voltage of these cells is determined by their means μ7, μ8 and standard deviations σ7, σ8. The dashed line corresponds to used cells which were subjected to 1000 program-erase cycles and whose data was retained for 10 years. The (Gaussian) probability distribution of these cells is designated by the means μ′7, μ′8 and standard deviations σ′7, σ′8.
The flash device typically supports a read operation in which the threshold levels of all the cells in a given page are compared simultaneously against some fixed voltage. Specifically, if the read operation is given a voltage V0, then each cell which conducts current after applying this voltage to its gate is read as 1, and each cell which does not conduct current is read as 0.
Several such read operations can be performed successively with a sequence of voltages which span the interval [VL, VR] e.g. as shown in FIGS. 2A-2B. In particular, assume that for a prescribed value dV, the sequence of read voltages is given by
VL, VL+dV, VL+2dV, VL+3dV, . . . , VR
e.g. as shown in FIG. 5 at step 500 and in FIG. 6.
Once these read operations are done, it is possible to obtain a sampled histogram of the threshold voltages in the voltage range. Assume that VR−VL=M*dV, where M is an integer, and let H(m), m=1, 2, . . . , M, be the sampled histogram of the threshold voltage, i.e. H(1) holds the number of cells whose threshold voltage lies in the interval [VL, VL+dV], H(2) holds the number of cells whose threshold voltage lies in the interval [VL+dV, VL+2*dV) and so on. Finally, H(M) holds the number of cells whose threshold voltage lies in the interval [VL+(M−1)*dV, VR]. Also, for future reference, denote by A(m), m=1, 2, . . . , M, the sequence of center points of the histogram's intervals, i.e., A (m)=VL+(m−½)*dV, e.g. as shown in FIG. 5 at step 510 and in FIG. 7.
Next, if the page in question belongs to a fresh block, it is expected that the sequence H(m) will exhibit two local maxima corresponding to the two highest program levels (see solid curve in FIG. 20. At the other extreme, if the page was cycled and its data retained, it is expected that only one maximum will be noticed, close to the left end of the voltage interval [VL, VR].
In order to estimate the mean and standard deviation of the highest program level, a subset of histogram values is identified, which corresponds to the highest program level. This is done by searching for the first bin from the right at which a local maximum is attained. Regardless of the state of the flash device in question, the first significant maximum from the right will always correspond to the highest program level, e.g. as shown in FIG. 5 at step 520 and in FIG. 8.
Once the maximizing bin is identified, several bins may be taken from either side of that bin and accounted for as belonging to cells in the highest program level. Denote by m* the first bin index from the right at which the histogram posses a local maximum. Then, e.g. as shown in FIG. 5 at step 530 and in FIG. 9, the mean and standard deviation of the highest program level can be estimated as follows:
μ = ∑ k = m * - N B m * + N B H ( k ) A ( k ) ∑ k = m * - N B m * + N B H ( k ) σ = max ( ∑ k = m * - N B m * + N B H ( k ) ( A ( k ) - μ ) 2 ∑ k = m * - N B m * + N B H ( k ) - dV 2 12 , 0 ) ,
dV 2 12
Fine Estimation of the Mean and standard deviation of the Intermediate program Levels according to certain embodiments of the present invention, is now described in detail.
In one embodiment of the present invention, the means and standard deviations of the remaining program levels can be estimated as described hereinabove. To this end, one can define appropriate intervals [VL (i)), VR (i)], i=1, 2, . . . for each program level and repeat the procedure described herein.
As opposed to the case of the highest program level, it is not always clear that such intervals exist which prevent ambiguity in identifying the part of the histogram which relates to the desired program level. This situation is illustrated in FIG. 21. As shown, the threshold voltage distributions of program levels 3, 4, and 5 are depicted. The solid curves correspond to fresh devices, while the dashed curves correspond to devices which underwent substantial cycling and retention. If it is desired to estimate the mean and standard deviation of program level 4, then in order to allow estimation of the mean and standard deviation in fresh flash devices as well as in cycled and retained flash arrays, the voltage window depicted in FIG. 21 may be selected. In particular, the right edge of the interval typically contains the lobe of program level 4 in a fresh device, and the left edge of the interval typically ensures that program level 4 is captured in cycled and/or retained devices. However, given the histogram of a device whose cycle count and retention are unknown, it is not clear which local maximum corresponds to program level 4. In a fresh device, it will be the maximum on the right side of the voltage interval, and in cycled and retained devices the maximum on the left side of the voltage interval corresponds to this program level. In order to circumvent this problem, adaptive voltage windows may be defined which are determined according to the mean of the highest program level.
FIG. 22 depicts this procedure for the case of estimating the mean and standard deviation of program level 4. For convenience, only the lobes of program levels four (4) and eight (8) are plotted. A default search voltage interval is defined, which corresponds to the case of a fresh device (see VL, VR in FIG. 22). Then, after estimating the mean of the highest program level as described herein, the difference, denoted as Δ, is computed, between the estimated mean of the highest program level and the mean of the highest program level for a non-cycled and non-retained device. With this difference the endpoints of the search interval for program level 4 are shifted to a pair of new endpoints, namely V′L, V′R as shown in FIG. 22, such that the new search interval coincides with the histogram mass of program level 4 as it behaves in the flash device. This ensures that within the voltage interval only a single maximum will be present, and it will be the one corresponding to the desired program level, e.g. as shown in FIG. 2B at steps 250 and 260, and in FIG. 10. The estimation procedure then continues in the same way as described herein.
Coarse Estimation of the Mean and standard deviation of the Intermediate Program Levels according to certain embodiments of the present invention, is now described in detail.
In some applications, fine estimation of the means and standard deviations of all the program levels with the procedure described hereinabove is prohibitively expensive in terms of the number of flash read operations employed to obtain the histograms. One way to alleviate the complexity is by using the fine estimation procedure only for a subset of the program levels.
In one embodiment, the means and standard deviations of program levels 2, 4, 6, and 8 are estimated finely as described hereinabove, and the remaining means and standard deviations are interpolated from the former. The means and standard deviations can be linearly interpolated by:
μ k = μ k - 1 + μ k + 1 2 , k = 3 , 5 , 7 σ k = σ k - 1 + σ k + 1 2 , k = 3 , 5 , 7 ,
e.g. as shown in FIG. 2B at step 270 and in FIG. 11.
Methods for coping with certain types of non-Gaussian statistics according to certain embodiments of the present invention, are now described in detail.
In some situations, the Gaussian assumption regarding the probability distribution of the threshold voltage of the cells is not valid. In such cases, the formulae used to compute the decision thresholds is no longer close to optimal. It is known, as described e.g. in the above-referenced publication by Proakis, that the optimal reading thresholds should be placed precisely at the intersection point of the probability distributions corresponding to adjacent program levels. Alternatively, decision thresholds are computed, in which the intersection points are approximated by the voltage at which the histogram attains its minimal value. This can be achieved by defining new search intervals and obtaining the histogram as described hereinabove. The histogram can then be searched for the minimum, e.g. as shown in FIG. 2B at step 290 and in FIG. 13.
Methods for reducing the overhead of read operations from the flash device according to certain embodiments of the present invention, are now described in detail and are shown in FIG. 5 at step 510 and 520, and in FIGS. 7 and 8. As described hereinabove, read operations are done from the flash memory device in order to build the threshold voltage histogram of a population of cells within the device. In order to reduce the overhead associated with these read operations, read operations may be performed as follows. If it is desired estimate the mean and standard deviation of the highest program level, for which an appropriate voltage search interval [VL, VR ] is chosen. The process begins with the rightmost (largest) read voltage, and works its way towards the leftmost (smallest) read voltage. After the desired maximum is identified, continue reading a sufficient number of read voltages to complete 2*NB+1 histogram bins, and then terminate the reading process and continue with the processing of the sampled histogram in order to estimate the mean and standard deviation. This approach is beneficial especially in new devices where the threshold voltage distribution of the highest program level is close to the right edge of the voltage interval [VL, VR].
Although the highest program level is used herein as an example for the possible benefit of this approach, this approach can be beneficial whenever read operations are used to estimate the means and standard deviations as described hereinabove.
Methods for ensuring uniform spreading of cells across program levels according to certain embodiments of the present invention, are now described in detail.
The accuracy of estimating the mean and standard deviation of the threshold distribution of a program level as described hereinabove depends on the number of cells which occupy this level. The more cells are programmed to a certain program level, the more accurate the mean and standard deviation estimation is. Since the data stored in the flash device is arbitrary, it may well be that the program levels of a particular page within a flash device are all the same, or that certain program levels are only scarcely occupied. This situation, unless changed, can cause inaccuracies in the estimation procedure, because the estimation might be based on too little cells. Such inaccuracies might be too high to the degree that the resulting reading thresholds will yield many detection errors and the error correcting code will fail. This situation may be circumvented by employing a scrambler on the data bits which are to be stored in the flash device and a descrambler on the bits which are read from the flash (unit 2200 of FIG. 27). For the purposes of the present specification, a scrambler may comprise any device which receives at its input a bit sequence and produces at its output another sequence of bits such that the following two conditions are met:
1. The 1s and 0s in the output bit sequence are equally likely.
2. The original bit sequence can be easily obtained from the output sequence by employing the inverse of the scrambling operation (descrambling).
When the bit sequence to be written to the flash is guaranteed to have 1s and 0s equally likely, the distribution of cells among the program levels is guaranteed to be more or less the same. In other words, the number of cells which will be programmed to each program level will be more or less the same. The phrase “more or less” is used to stipulate that the probability that the number of cells in any particular program level is too small to ensure sufficient accuracy of estimation is small enough so as not to degrade the overall performance, e.g. as shown in FIG. 2A at steps 202 and 320, and in FIG. 16.
Methods for preventing misidentification of local maximum corresponding to desired program level according to certain embodiments of the present invention, are now described in detail.
The procedure described hereinabove for finding the lobe corresponding to the estimated program level by searching for the first maximum from the right hinges on the assumption that the histogram H(m) does not exhibit any other local maxima to the right of the desired lobe. In situations where a local maximum does exist due to some fluctuating behavior in a small set of cells, this assumption does not hold. This situation might introduce a dramatic estimation error causing the reading threshold to be wrongly placed and the entire reading process to fail. In order to prevent misidentification of the lobe corresponding to the estimated program level, the search for the maximum may be modified as follows. Upon identifying a local maximum in the histogram, the number of cells which lie to the right of this maximum is tested (FIG. 8, step 850). If this number is above some threshold Th, this maximum is assumed to be the appropriate one. Otherwise, the search for the next maximum commences. Finally, it is noted that this procedure can also be employed in situations where the search for the local maximum is done from left to right.
Methods for maintaining a threshold history table to reduce the number of training procedures according to certain embodiments of the present invention, are now described in detail and are shown e.g. in FIG. 2A at step 220, in FIG. 2B at step 300 and in FIGS. 4 and 15.
The training procedures described hereinabove can be performed whenever it is difficult or impossible to determine reading thresholds which yield a sufficiently low bit error count, thus enabling the error correcting mechanism to recover the encoded data correctly. As mentioned above, performing these training procedures for each page in an erase sector might be prohibitively complex and/or might consume too much of the overall system's resources. For this reason, it is important to be able to determine appropriate reading thresholds without resorting to training.
In one embodiment of the present invention, reading thresholds of a certain page in a certain erase sector are stored in a data base and retrieved later on when reading successive pages of the same erase sector or other erase sectors. In one embodiment, a threshold history table (or data base) is structured as depicted in FIG. 23, in which BPC represents “bits per cell”.
Each entry in the table comprises threshold information pertaining to a set of physical rows in the flash device. The set of rows associated with a particular row entry comprises of all the rows in the flash device sharing some common features, namely:
1. The row number within the erase sector.
2. The cycle count of the erase sector in which the row resides.
3. The retention period of the erase sector in which the row resides.
It is assumed that a pair of rows having the same row index but residing in distinct erase sectors who share the same cycle count and retention period will behave the same in the sense that reading thresholds which are appropriate for the former row will also be appropriate for the latter. Each row entry includes reading thresholds which are organized in three data structures corresponding to the number of bits programmed to each cell in the row (BPC). A suitable structure of each set of thresholds is portrayed in FIG. 24.
The threshold set for the case where only the MSB bit is programmed includes only one MSB reading threshold. When two bits are programmed to each cell, a set of three thresholds is employed to read both the MSB and the CSB bit. Finally, seven thresholds are employed to read all the bits when MSB, CSB, and LSB bits are programmed. As reference, the thresholds marked in FIG. 19 correspond to the thresholds in the 3 BPC threshold structure of FIG. 24.
In one embodiment of the present invention, e.g. as shown in FIG. 2B at step 300 and in FIG. 15, each time a training procedure is performed on a physical row, the obtained thresholds are stored in an appropriate data structure of an appropriate row entry. A suitable method for updating the threshold history table in this case is shown in FIG. 15. At first, the data base is searched for an entry which matches the row number, cycle count and retention period. If no such entry is found, one is created. Then, the corresponding threshold structure is updated with the thresholds from the training procedure.
In one embodiment of the present invention, e.g. as shown in FIG. 2A at step 202 and in FIG. 16, the threshold history table is used as follows. When a page is to be read from the flash device, the controller checks if an entry exists which corresponds to the row number where the page resides, the cycle count of the erase sector where the page resides, and the retention period thereof. If such an entry exists, the controller checks if thresholds exist for the appropriate value of BPC of the row in which the page resides. If such thresholds exist, the controller uses these thresholds to read the desired page. If no entry is found in the table, and/or if no thresholds are found which match the value of BPC, the controller proceeds to perform training for the row in which the page resides. FIG. 25 is a simplified flowchart illustration of a method for rapidly assessing functionality of erase sectors in a flash memory operative in accordance with certain embodiments of the present invention. The method of FIG. 25 typically includes the following steps, suitably ordered e.g. as shown:
Step 2000: Estimate a mean and standard deviation of a 2nd physical level over at least a portion of at least one flash memory page
Step 2010: Estimate a mean and standard deviation of a 3rd physical level over at least a portion of at least one flash memory page
Step 2020: Estimate a mean and standard deviation of a first physical level residing above the 2nd physical level and below the 3rd physical level by interpolating between previously found means and standard deviations of the 2nd and 3rd levels.
FIG. 26 is a simplified flowchart illustration of a method for assessing effects of retention and cycling on individual erase sectors in a flash memory which has undergone retention and cycling, operative in accordance with certain embodiments of the present invention. The method of FIG. 26 typically includes the following steps, suitably ordered e.g. as shown:
Step 2110: receive a first centerpoint of a rightmost lobe of a distribution of physical values within the cells of a new flash memory device and a second centerpoint of a rightmost lobe of a distribution of physical values within the cells of an entirely degraded flash memory device
Step 2120: generate a histogram representing distribution of physical values within the cells of an individual erase sector in a flash memory which has undergone retention and cycling, over a range extending at least between the second and first centerpoints
Step 2130: compute at least one statistic of a rightmost lobe of the histogram thereby assessing effects of retention and cycling on the individual erase sector.
FIG. 27 is a simplified functional block diagram of the external controller 102 of FIG. 1B, according to certain embodiments of the present invention. Alternatively, some or all of the functionalities shown may be implemented in the internal controller 110 of FIG. 1B. As shown, the controller includes a scrambler/descrambler 2200 which typically employs a linear feedback shift register 2210 such as that illustrated in FIG. 18. The scrambler/descrambler 2200 receives and scrambles data from the host 100 of FIG. 1B for writing to the flash memory 105 as well as, conversely, receiving and de-scrambling data read from the flash memory 105 which is intended for the host 100. A histogram processing unit 2230 may be operative to perform at least some of steps 240, 260, 270 and 290 of FIG. 2B, providing output to a final reading threshold computation unit 2240 which computes actual (as opposed to mock) reading thresholds, e.g. performing at least some of steps 280 and 290 of FIG. 2B, and stores suitable information in a threshold history database 2250 such as that of FIG. 23. A mock reading threshold computation unit 2260 receives output from the histogram processing unit 2230. Unit 2230 is operative based on output of mock reading operations in the flash, carried out using mock reading thresholds generated by unit 2260. Mock reading threshold computation unit 2260 typically performs some or all of steps 240, 250 and 260 of FIG. 2B. A conventional control unit 2270, which may have some or all of the functionalities of conventional external flash memory device controllers, is connected to all units.
3 Boaz Eitan, Guy Cohen, Assaf Shappor, 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.
6 David Esseni, Bruno Ricco, "Trading-Off Programing Speed and Current Absorption in Flash Memories with the Ramped-Gate Programming Technique", Ieee Transactions on Electron Devices, vol. 47, No. 4, Apr. 2000.
10 International Search Report and written opinion for Application No. PCT/IL2008/001232, dated Jan. 28, 2009.
11 J.M. Portal, H. Aziza, D. Nee, "EEPROM Diagnosis Based on Threshold Voltage Embedded Measurment", Journal of Electronic Testing: Theory and Applications 21, 33-42, 2005.
13 JEDEC Standard, "Stress-Test-Driven Qualification of Integrated Circuits", JEDEC Solid State Technology Assocation. JEDEC Standard No. 47F pp. 1-26.
US-Klassifikation 711/103, 711/154
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