The present disclosure includes methods and apparatuses for mapping between program states and data patterns. One method includes: programming a group of G memory cells such that a combination of respective program states of the group maps to a constellation point corresponding to a received n unit data pattern, the group used to store n/G units of data per memory cell; wherein the constellation point is one of a number of constellation points of a constellation associated with mapping respective program state combinations of the group of memory cells to n unit data patterns; and wherein the constellation comprises a first mapping shell and a second mapping shell, the constellation points corresponding to the respective first and second mapping shells determined, at least partially, based on a polynomial expression of order equal to G.
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1. An apparatus, comprising:
a plurality (G) of memory cells; and
a packing component configured to:
map each one of a plurality (2n) of data patterns to a respective one of 2n program state combinations corresponding to the G memory cells in accordance with a mapping constellation comprising at least a first shell of constellation mapping points and a second shell of constellation mapping points;
wherein the G memory cells are configured to store n/G units of data per memory cell.
9. A method, comprising:
storing a n unit data pattern in a plurality (G) of memory cells such that the G memory cells store n/G units of data per memory cell, wherein a combination of respective program states of the G memory cells maps to at least one constellation point corresponding to the n unit data pattern;
wherein the at least one constellation point is part of a mapping constellation comprising at least a first shell of constellation mapping points and a second shell of constellation mapping points; and
wherein quantities of constellation points corresponding to the respective first and second shells are determined, at least partially, based on a polynomial expression of order equal to G.
14. An apparatus, comprising:
an array of memory cells each programmable to a plurality (l) of program states; and
a controller configured to:
store a particular n unit data pattern in a plurality (G) of memory cells each programmed to a respective one of the l program states;
map, via a mapping constellation, the particular n unit data pattern to at least one of 2n program state combinations, wherein the mapping constellation maps between the 2n program state combinations and a respective 2n n unit data patterns;
wherein the mapping is based, at least partially, on a polynomial expression of order equal to G, a first term of the polynomial expression corresponding to a first mapping shell and a second term of the polynomial expression corresponding to a second mapping shell.
2. The apparatus of
3. The apparatus of
4. The apparatus of
5. The apparatus of
6. The apparatus of
8. The apparatus of
a quantity of constellation mapping points corresponding to the first shell is determined based on a first term of a polynomial expression (A+B)G such that AG is the quantity of constellation mapping points of the first shell; and
a quantity of constellation mapping points corresponding to the second shell is determined based on a second term of the polynomial expression such that G×A(G−1) ×B is the quantity of constellation points of the second mapping shell, with B being a quantity of program states equal to L−A, wherein l is a quantity of program states to which the G memory cells are programmable.
10. The method of
11. The method of
12. The method of
13. The method of
15. The apparatus of
16. The apparatus of
17. The apparatus of
18. The apparatus of
19. The apparatus of
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This application is a Continuation of U.S. application Ser. No. 14/304,420, filed Jun. 13, 2014, which issues as U.S. Pat. No. 8,977,808 on Mar. 10, 2015, which is a Continuation of U.S. application Ser. No. 13/444,314, filed Apr. 11, 2012, which issued as U.S. Pat. No. 8,788,743 on Jul. 22, 2014, the contents of which are incorporated herein by reference.
The present disclosure relates generally to semiconductor memory and methods, and more particularly, to mapping between program states and data patterns.
Memory devices are typically provided as internal, semiconductor, integrated circuits in computers or other electronic devices. There are many different types of memory including volatile and non-volatile memory. Volatile memory can require power to maintain its data (e.g., information) and includes random-access memory (RAM), dynamic random access memory (DRAM), and synchronous dynamic random access memory (SDRAM), among others. Non-volatile memory can provide persistent data by retaining stored data when not powered and can include NAND flash memory, NOR flash memory, static random access memory (SRAM), resistance variable memory, such as phase change random access memory (PCRAM) and resistive random access memory (RRAM), and magnetic random access memory (MRAM), such as spin torque transfer random access memory (STT RAM), among others.
Memory devices can be combined together to form a solid state drive (SSD). A solid state drive can include non-volatile memory such as NAND flash memory and/or NOR flash memory, and/or can include volatile memory such as DRAM, among various other types of non-volatile and volatile memory. Flash memory devices, including floating gate flash devices and charge trap flash (CTF) devices can comprise memory cells having a storage node (e.g., a floating gate or a charge trapping structure) used to store charge and may be utilized as non-volatile memory for a wide range of electronic applications.
Memory cells can be arranged in an array architecture and can be programmed to a desired state. For instance, electric charge can be placed on or removed from the storage node (e.g., floating gate) of a memory cell to place the cell into one of a number of program states. As an example, a single level cell (SLC) can be programmed to one of two program states which can represent a stored data unit (e.g., binary units 1 or 0). Various flash memory cells can be programmed to more than two program states, which can represent multiple stored data units (e.g., binary units 1111, 0111, 0011, 1011, 1001, 0001, 0101, 1101, 1100, 0100, 0000, 1000, 1010, 0010, 0110, or 1110). Such memory cells may be referred to as multi state cells, multiunit cells, or multilevel cells (MLCs). MLCs can allow the manufacture of higher density memories without increasing the number of memory cells since each cell can represent more than one digit (e.g., more than one bit).
Some MLCs can be programmed to a quantity (L) of program states that does not correspond to an integer number of stored data units. That is, the number of data units capable of being stored in a cell (Log2(L)) can correspond to a fractional number of stored data units (e.g., a fractional number of bits).
The present disclosure includes methods and apparatuses for mapping between program states and data patterns. One method includes: programming a group of G memory cells such that a combination of respective program states of the group maps to a constellation point corresponding to a received N unit data pattern, the group used to store N/G units of data per memory cell; wherein the constellation point is one of a number of constellation points of a constellation associated with mapping respective program state combinations of the group of memory cells to N unit data patterns; and wherein the constellation comprises a first mapping shell and a second mapping shell, the constellation points corresponding to the respective first and second mapping shells determined, at least partially, based on a polynomial expression of order equal to G.
Embodiments of the present disclosure can provide a substantially systematic mapping (e.g., assignment) of program states to data patterns, and vice versa, in association with fractional unit per cell (fractional bit per cell) configurations, for instance. Embodiments can limit error multiplication and/or propagation that can negatively affect error detection and/or correction systems (e.g., systems employing error correcting codes (ECC) such as low density parity check (LDPC) codes and Hamming codes, among others), as compared to previous fractional bit per cell mapping algorithms. Embodiments can also provide benefits such as providing effective fractional bit per cell mapping without adding redundancy and without employing code expansion as in a number of previous approaches (e.g., base conversion mapping which can generate extra parities), among various other benefits.
In the following detailed description of the present disclosure, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration how a number of embodiments of the disclosure may be practiced. These embodiments are described in sufficient detail to enable those of ordinary skill in the art to practice the embodiments of this disclosure, and it is to be understood that other embodiments may be utilized and that process, electrical, and/or structural changes may be made without departing from the scope of the present disclosure. As used herein, the designators “M”, “N”, “n”, “A”, “B”, “G”, and “L,” particularly with respect to reference numerals in the drawings, indicates that a number of the particular feature so designated can be included with a number of embodiments of the present disclosure. As used herein, “a number of” something can refer to one or more of such things.
The figures herein follow a numbering convention in which the first digit or digits correspond to the drawing figure number and the remaining digits identify an element or component in the drawing. Similar elements or components between different figures may be identified by the use of similar digits. For example, 100 may reference element “00” in
As illustrated in
Host 102 can be a host system such as a personal laptop computer, a desktop computer, a digital camera, a mobile telephone, or a memory card reader, among various other types of hosts. Host 102 can include a system motherboard and/or backplane and can include a number of memory access devices (e.g., a number of processors).
The controller 108 can communicate with the memory devices 110-1, . . . , 110-M to control data read, write, and erase operations, among other operations. The controller 108 can include, for example, a number of components in the form of hardware and/or firmware (e.g., one or more integrated circuits) and/or software for controlling access to the number of memory devices 110-1, . . . , 110-M and/or for facilitating data transfer between the host 102 and memory devices 110-1, . . . , 110-M. For instance, in the example illustrated in
The data packer/unpacker component 112 can be used in association with mapping between memory cell program states and data in accordance with a number of embodiments described herein. The error code/decode component 114 can be an LDPC encoder/decoder, for instance, which can encode/decode user data transferred between host 102 and the memory devices 110-1, . . . , 110-M.
The memory devices 110-1, . . . , 110-M can include a number of arrays of memory cells. The arrays can be flash arrays with a NAND architecture, for example. However, embodiments are not limited to a particular type of memory array or array architecture. The memory cells can be grouped, for instance, into a number of blocks including a number of physical pages. A number of blocks can be included in a plane of memory cells and an array can include a number of planes. As one example, a memory device may be configured to store 8 KB (kilobytes) of user data per page, 128 pages of user data per block, 2048 blocks per plane, and 16 planes per device.
In embodiments in which the memory devices 110-1, . . . , 110-M comprise flash arrays having a NAND architecture, the arrays can comprise access lines, e.g., word lines and intersecting data lines, e.g., bit lines. The arrays can comprise “strings” of memory cells connected in series source to drain between a source select gate configured to selectively couple a respective string to a common source and a drain select gate configured to selectively couple a respective string to a respective bit line. The memory cells can comprise, for instance, a source, a drain, a charge storage node (e.g., a floating gate), and a control gate, with the control gates of cells corresponding to a “row” of cells being commonly coupled to a word line. A NOR flash array would be similarly structured with the exception of strings of memory cells being coupled in parallel between select gates.
As one of ordinary skill in the art will appreciate, groups of flash cells coupled to a selected word line can be programmed and/or read together as a page of memory cells. A programming operation (e.g., a write operation), can include applying a number of program pulses (e.g., 16V-20V) to a selected word line in order to increase the threshold voltage (Vt) of selected cells coupled to that selected word line to a desired Vt level corresponding to a target (e.g., desired) program state. A read operation can include sensing a voltage and/or current change of a bit line coupled to a selected cell (e.g., responsive to a read voltage applied to the word line corresponding to the cell) in order to determine the program state of the selected cell.
As described further herein, in a number of embodiments of the present disclosure, a memory cell can be programmed to one of a quantity of program states corresponding to either an integer number of stored data units (e.g., bits) or a fractional number of stored data units. In a number of embodiments, the program states of a number of cells of a group of cells each storing a fractional number of bits can be combined such that the group of cells stores an integer number of bits. For instance, consider a group of cells each programmed to one of five program states, such that each cell can store 2.25 bits. In this example, the combined program states of a group of four cells corresponds to 9 bits (2.25 bits/cell×4 cells). That is, a 9 bit data pattern can be stored in the group of four cells. As such, controller 108 can control programming and/or reading a group of cells each storing a fractional number of bits per cell and can output (e.g., to host 102) an N unit data pattern stored in the group, where N is an integer number data units (e.g., bits). The particular data pattern (e.g., bit pattern) to which the combination of determined program states of the group corresponds can be determined based on a mapping algorithm in accordance with a number of embodiments described herein.
Row 218 indicates the quantity of program states to which the memory cell may be programmed. The program states shown in
In
Memory cells programmable to a power of 2 quantity of program states (e.g., 2 program states, 4 program states, 8, program states, 16 program states, etc.) can individually store an integer number of bits per cell (e.g., log2(L) bits/cell where L is the number of program states to which the cell is programmable). As such, the program state of each memory cell can be directly mapped to one of L different N bit data patterns where N is the integer quantity of bits stored in the cell. For instance, the program states of a cell programmable to two program states (L0 and L1) can be mapped to 0 or 1 (e.g., a 1 bit data pattern), the program states of a cell programmable to 4 program states (L0 to L3) can be mapped to 00, 01, 10, and 11, respectively (e.g., a 2 bit data pattern), and the program states of a cell programmable to 8 program states (L0 to L7) can be mapped to 000, 001, 010, 011, 100, 101, 110, and 111, respectively (e.g., a 3 bit data pattern).
In contrast, memory cells programmable to a non-power of 2 quantity of program states individually store a fractional (e.g., non-integer) number of bits per cell. As such, rather than program states of each individual cell mapping to an N bit data pattern, combinations of the L program states to which each individual cell of a group of cells is programmable are mapped to an N bit data pattern where N is an integer quantity of bits stored in the group. For instance, combinations of respective program states of a group of two memory cells programmable to three program states (L0, L1, and L2) (e.g., 1.5 bits/cell) are mapped to a 3 bit (e.g., 1.5 bits/cell×2 cells) data pattern (e.g., 000, 110, 100, etc.). Similarly, combinations of respective program states of a group of four memory cells programmable to five program states (L0 to L4) (e.g., 2.25 bits/cell) are mapped to a 9 bit (e.g., 2.25 bits/cell×4 cells) data pattern (e.g., 110011001, 000001111, 101010101, etc.), and combinations of respective program states of a group of eight memory cells programmable to 9 states (L0 to L8) (e.g., 3.125 bits/cell) are mapped to a 25 bit (e.g., 3.125 bits/cell×8 cells) data pattern (e.g., 0000011111000001111100000, 1010101010101010101010101, 1111111111111111110000000, etc.).
In general, for a group of cells collectively storing an integer number (N) of units of data (e.g., bits), but individually storing a fractional number of units of data, 2N different N unit data patterns are mapped to a corresponding number (e.g., 2N) of different program state combinations of the group. As an example, consider a group of two cells each programmed to one of three program states (L0, L1, L2) such that the group collectively stores 3 bits of data (e.g., 1.5 bits/cell). As such, 23 (e.g., 8) different 3 bit data patterns are mapped to 23 (e.g., 8) different program state combinations of the group.
In a number of embodiments, a constellation (e.g., an L×L square constellation where L is the quantity of program states to which a cell is programmable) can be used to represent the different possible program state combinations associated with a group of fractional unit memory cells. For instance, each possible program state combination can correspond to a different constellation point, which can be mapped to a particular N unit data pattern, where N is the integer quantity of data units stored in the group of cells. The quantity of program state combinations (e.g., the quantity of constellation points) can equal L2, which must be greater than or equal to the 2N different N unit data patterns corresponding to the N quantity of data units stored in the group of cells. As such, one or more of the L2 program state combinations may not be mapped to an N unit data pattern, or one or more of the L2 program state combinations may be mapped to a same one of the N unit data patterns as one or more others of the L2 program state combinations. An example of a mapping constellation in accordance with a number of embodiments of the present disclosure is described below in connection with
The particular mappings of data patterns to respective program state combinations corresponding to groups of fractional unit (e.g., fractional bit) memory cells and vice versa can vary. That is, the manner in which program state combinations are assigned to the data patterns may not be uniform. In some previous approaches, a code expansion can be performed on a data pattern in association with mapping data patterns to particular program state combinations. However, such code expansion leads to an increase in error correction code redundancy and decreases capacity and can lead to error multiplication and/or propagation. In contrast, a number of embodiments of the present disclosure can effectively and efficiently map between data patterns and program states without performing a code expansion, for instance. As such, a number of embodiments of the present disclosure can provide decreased complexity and/or can reduce and/or prevent error multiplication and/or propagation as compared to previous approaches.
As described further below in connection with
In a number of embodiments, mapping between program state combinations and data patterns is based on a polynomial expression of order G, where G is a number of fractional unit cells combined to store an integer number of units of data corresponding to a data pattern. In a number of embodiments, a first term of the polynomial expression corresponds to a first mapping shell and a second term of the polynomial expression corresponds to a second mapping shell, with each mapping shell corresponding to a number of constellation points. As an example, the polynomial expression on which the mapping is based can be the expression (A+B)G, with AG being the first term and corresponding to a quantity of constellation points of the first mapping shell, and G×A(G−1)×B being the second term and corresponding to a quantity of constellation points of the second mapping shell. As described further below, A can be the quantity of program states from which the respective program state combinations corresponding to the first mapping shell are determined and B can be the quantity of additional program states (e.g., an additional quantity of the L program states) from which the respective program state combinations corresponding to the second mapping shell are determined. As such, in embodiments in which two mapping shells are used, A+B is equal to the quantity of program states to which the memory cells are programmable. As an example, A can be equal to 2a with “a” being a value such that 2a is an uppermost power of 2 value that is less than the quantity of program states (e.g., L) to which the memory cells are programmable. For instance, for cells programmable to 6 different program states and storing 2.5 bits/cell, A is equal to 4 since 22 is the closest power of 2 value that is less than 6. Since A is equal to 4, B is equal to 2 (e.g., 6−4). As such, the quantity of program states from which the respective program state combinations corresponding to the first mapping shell are determined is four. That is, only combinations of the first four program states (e.g., L0 to L3) of the six program states (e.g., L0 to L5) to which the memory cells are programmable, correspond to constellation points of the first mapping shell. In this example, the quantity of additional program states from which the respective program state combinations corresponding to the second mapping shell is two (e.g., B=2). As such, only combinations comprising at least one of the last two program states (e.g., L4 and L5) of the six program states (e.g., L0 to L5) to which the memory cells are programmable, correspond to constellation points of the second mapping shell. In a number of embodiments, the A program states corresponding to the first mapping shell comprise the lowermost A program states of the L program states (e.g., the program states corresponding to the lowermost Vt levels), and the B program states corresponding to the second mapping shell comprise program states other than the lowermost A program states.
At 338 of
The outputs of mappers 340-1 to 340-n can be multiplexed 344 and a mapper 346 (shown as “Bits2State Map”) can map the bits assigned to the respective cells (e.g., cells 1 to nD) to respective program states. The output 348-1 (shown as “States_1D”) indicates the program state to which the first cell of the group of n cells is to be programmed and the output 348-n (shown as “States_nD”) indicates the program state to which the nth cell of the group is to be programmed such that the combination of the program states of cells 1 to n maps to the appropriate N-bit data pattern of the 2N data patterns corresponding to the particular symbol size employed.
As an example, the method illustrated in
Table 1 shown below provides configuration information associated with the example described in connection with
TABLE 1
First
First
Second shell
Constellation
shell
shell
additional
Second shell
Packing
bpc
States
Cells/nD
points
states
points
states
points
density
1.5
3
2
8
2
4
1
4
88.89%
Therefore, in the example shown in
The quantity of constellation points of the respective first and second mapping shells can be determined using the first two terms of the polynomial expression described above (e.g., (A+B)G), with AG being the first term and indicating the quantity of constellation points of the first mapping shell and G×A(G−1)×B being the second term and corresponding to a quantity of constellation points of the second mapping shell. In the 1.5 bits/cell example of
As shown in
The mappings of
The mappings of
Table 2 shown below provides configuration information associated with the example described in connection with
TABLE 2
First
First
Second shell
Constellation
shell
shell
additional
Second shell
Packing
bpc
States
Cells/nD
points
states
points
states
points
density
2.25
5
4
512
4
256
1
256
81.92%
The quantity of constellation points of the respective first and second mapping shells can be determined using the first two terms of the polynomial expression described above (e.g., (A+B)G), with AG being the first term and indicating the quantity of constellation points of the first mapping shell and G×A(G−1)×B being the second term and corresponding to a quantity of constellation points of the second mapping shell. In the 2.25 bits/cell example of
As such,
Table 3 shown below provides configuration information associated with the example described in connection with
TABLE 3
First
First
Second shell
Constellation
shell
shell
additional
Second shell
Packing
bpc
States
Cells/nD
points
states
points
states
points
density
2.5
6
2
32
4
16
2
16
88.89%
The quantity of constellation points of the respective first and second mapping shells can be determined using the first two terms of the polynomial expression described above (e.g., (A+B)G), with AG being the first term and indicating the quantity of constellation points of the first mapping shell and G×A(G−1)×B being the second term and corresponding to a quantity of constellation points of the second mapping shell. In the 2.5 bits/cell example of
Table 4 shown below provides configuration information associated with the example described in connection with
TABLE 4
bpc
3.125
States
9
Cells/nD
8
Constellation points
33,554,432
First shell states
8
First shell points
16,777,216
Second shell additional states
1
Second shell points
16,777,216
Packing density
77.95%
The quantity of constellation points of the respective first and second mapping shells can be determined using the first two terms of the polynomial expression described above (e.g., (A+B)G), with AG being the first term and indicating the quantity of constellation points of the first mapping shell and G×A(G−1)×B being the second term and corresponding to a quantity of constellation points of the second mapping shell. In the 3.125 bits/cell example of
As such,
Mappings such as those described above in connection with
For instance, determining the particular N bit data pattern to which the combination of the respective determined program states of the group corresponds (e.g., in association with a read operation) can be based, at least partially, on a mapping constellation comprising a first mapping shell and a second mapping shell, with the first and second mapping shells being defined by a polynomial expression of order G. A data packing component such as component 112 shown in
As illustrated by the example shell mappings shown in
In a number of embodiments, a controller (e.g., controller 108) can determine the bit pattern stored in the group (e.g., in association with a read operation), and can provide the data to a host (e.g., host 102). The bit pattern stored in the group of cells can be decoded (e.g., via error code/decode component 114) prior to being provided to the host (e.g., if previously encoded with error data).
The present disclosure includes methods and apparatuses for mapping between program states and data patterns. One method includes: programming a group of G memory cells such that a combination of respective program states of the group maps to a constellation point corresponding to a received N unit data pattern, the group used to store N/G units of data per memory cell; wherein the constellation point is one of a number of constellation points of a constellation associated with mapping respective program state combinations of the group of memory cells to N unit data patterns; and wherein the constellation comprises a first mapping shell and a second mapping shell, the constellation points corresponding to the respective first and second mapping shells determined, at least partially, based on a polynomial expression of order equal to G.
It will be understood that when an element is referred to as being “on,” “connected to” or “coupled with” another element, it can be directly on, connected, or coupled with the other element or intervening elements may be present. In contrast, when an element is referred to as being “directly on,” “directly connected to” or “directly coupled with” another element, there are no intervening elements or layers present. As used herein, the term “and/or” includes any and all combinations of a number of the associated listed items.
As used herein, the term “and/or” includes any and all combinations of a number of the associated listed items. As used herein the term “or,” unless otherwise noted, means logically inclusive or. That is, “A or B” can include (only A), (only B), or (both A and B). In other words, “A or B” can mean “A and/or B” or “a number of A and B.”
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. Thus, a first element could be termed a second element without departing from the teachings of the present disclosure.
Although specific embodiments have been illustrated and described herein, those of ordinary skill in the art will appreciate that an arrangement calculated to achieve the same results can be substituted for the specific embodiments shown. This disclosure is intended to cover adaptations or variations of a number of embodiments of the present disclosure. It is to be understood that the above description has been made in an illustrative fashion, and not a restrictive one. Combination of the above embodiments, and other embodiments not specifically described herein will be apparent to those of skill in the art upon reviewing the above description. The scope of the a number of embodiments of the present disclosure includes other applications in which the above structures and methods are used. Therefore, the scope of a number of embodiments of the present disclosure should be determined with reference to the appended claims, along with the full range of equivalents to which such claims are entitled.
In the foregoing Detailed Description, some features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the disclosed embodiments of the present disclosure have to use more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.
Shen, Zhenlei, Kaynak, Mustafa N., Parthasarathy, Sivagnanam, Khayat, Patrick R.
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