Read level tracking and optimization
Systems and methods for read level tracking and optimization are described. Pages from a wordline of a flash memory device read and the raw page data read from the wordline may be buffered in a first set of buffers. The raw page data for each of the pages may be provided to a decoder for decoding and the decoded page data for each of the pages buffered in a second set of buffers. First bin identifiers may be identified for memory cells of the wordline based on the raw page data and second bin identifiers may be identified for the memory cells of the wordline based on the decoded page data. Cell-level statistics may be accumulated based on the first bin identifiers and the second bin identifiers, and a gradient may be determined for respective read levels based on decoding results for each of the pages and the cell-level statistics. Settings for the read levels may be configured in the flash memory device based on the determined gradients.
1. A data storage system, comprising:
one or more memory devices; and
one or more controllers configured to cause:
obtaining raw data read from memory cells of the one or more memory devices, for decoding;
obtaining decoded data based on the raw data;
computing memory cell-level statistics based on first bin identifiers associated with the raw data and second bin identifiers associated with the decoded data;
determining gradients for read levels associated with the one or more memory devices based on results of the decoding and the memory cell-level statistics; and
setting parameters of the read levels associated with the one or more memory devices based on the determined gradients.
2. The data storage system of claim 1 , wherein the one or more controllers are configured to cause:
identifying the first bin identifiers for the memory cells based on the raw data stored in one or more first memories; and
identifying the second bin identifiers for the memory cells based on the decoded data stored in one or more second memories.
3. The data storage system of claim 1 , wherein each of the determined gradients comprises a magnitude and a direction for adjusting a respective read level of the read levels associated with the one or more memory devices.
4. The data storage system of claim 1 , wherein the one or more controllers are configured to cause:
identifying the first bin identifiers for the memory cells based on logical values of the raw data, and
identifying the second bin identifiers for the memory cells based on logical values of the decoded data.
5. The data storage system of claim 4 , wherein the one or more controllers are configured to cause:
identifying the first bin identifiers by applying reverse gray coding to the logical values of the raw data, and
identifying the second bin identifiers by applying the reverse gray coding to the logical values of the decoded data.
6. The data storage system of claim 1 , wherein the one or more controllers are configured to cause computing the memory cell-level statistics by:
incrementing bin counts based on the first bin identifiers or the second bin identifiers;
comparing the first bin identifiers to the second bin identifiers; and
incrementing first error-type counts and second error-type counts based on the comparison of the first bin identifiers to the second bin identifiers.
7. The data storage system of claim 6 , wherein the one or more controllers are configured to cause determining the gradients for the read levels by:
applying a gradient generator matrix to the bin counts to determine a first set of gradients;
determining a second set of gradients based on a difference between the first error-type counts and the second error-type counts; and
selecting the gradients, for the read levels, from the first set of gradients or from the second set of gradients based on the results of the decoding.
8. The data storage system of claim 7 , wherein the one or more controllers are configured to cause applying the gradient generator matrix to the bin counts by:
selecting the gradient generator matrix from gradient generator matrices based on the results of the decoding; and
multiplying the gradient generator matrix by the bin counts to determine the first set of gradients.
9. A method, comprising:
obtaining raw data read from memory cells of one or more memory devices, for decoding;
obtaining decoded data based on the raw data;
computing memory cell-level statistics based on first bin identifiers associated with the raw data and second bin identifiers associated with the decoded data;
determining gradients for read levels associated with the one or more memory devices based on results of the decoding and the memory cell-level statistics; and
setting parameters of the read levels associated with the one or more memory devices based on the gradients.
10. The method of claim 9 , comprising:
identifying the first bin identifiers for the memory cells based on the raw data stored in one or more first memories; and
identifying the second bin identifiers for the memory cells based on the decoded data stored in one or more second memories.
11. The method of claim 9 , wherein each of the gradients comprises a magnitude and a direction for adjusting a respective read level of the read levels associated with the one or more memory devices.
12. The method of claim 9 , comprising:
identifying the first bin identifiers for the memory cells based on logical values of the raw data, and
identifying the second bin identifiers for the memory cells based on logical values of the decoded data.
13. The method of claim 12 ,
wherein identifying the first bin identifiers comprises identifying the first bin identifiers by applying reverse gray coding to the logical values of the raw data, and
wherein identifying the second bin identifiers comprises identifying the second bin identifiers by applying the reverse gray coding to the logical values of the decoded data.
14. The method of claim 9 , wherein computing the memory cell-level statistics comprises:
incrementing bin counts based on the first bin identifiers or the second bin identifiers;
comparing the first bin identifiers to the second bin identifiers; and
incrementing first error-type counts and second error-type counts based on the comparison of the first bin identifiers to the second bin identifiers.
15. The method of claim 14 , wherein determining the gradients for the read levels comprises:
applying a gradient generator matrix to the bin counts to determine a first set of gradients;
determining a second set of gradients based on a difference between the first error-type counts and the second error-type counts; and
selecting the gradients, for the read levels, from the first set of gradients or from the second set of gradients based on the results of the decoding.
16. The method of claim 15 , wherein applying the gradient generator matrix to the bin counts comprises:
selecting the gradient generator matrix from gradient generator matrices based on the results of the decoding; and
multiplying the gradient generator matrix by the bin counts to determine the first set of gradients.
17. An apparatus, comprising:
means for obtaining raw data read from memory cells of one or more memory devices, for decoding;
means for obtaining decoded data based on the raw data;
means for computing memory cell-level statistics based on first bin identifiers associated with the raw data and second bin identifiers associated with the decoded data;
means for determining gradients for read levels associated with the one or more memory devices based on results of the decoding and the memory cell-level statistics; and
means for setting parameters of the read levels associated with the one or more memory devices based on the gradients.
18. The apparatus of claim 17 , comprising:
means for identifying the first bin identifiers for the memory cells based on logical values of the raw data, and
means for identifying the second bin identifiers for the memory cells based on logical values of the decoded data.
19. The apparatus of claim 18 ,
wherein the means for identifying the first bin identifiers comprises means for identifying the first bin identifiers by applying reverse gray coding to the logical values of the raw data, and
wherein the means for identifying the second bin identifiers comprises means for identifying the second bin identifiers by applying the reverse gray coding to the logical values of the decoded data.
20. The apparatus of claim 17 , wherein the means for computing the memory cell-level statistics comprises:
means for incrementing bin counts based on the first bin identifiers or the second bin identifiers;
means for comparing the first bin identifiers to the second bin identifiers; and
means for incrementing first error-type counts and second error-type counts based on the comparison of the first bin identifiers to the second bin identifiers.