DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is responsive to the reply filed 13 July 2026.
Claims 1-20 are pending and have been presented for examination.
Response to Arguments
Applicant's arguments filed 13 July 2026 have been fully considered but they are not persuasive.
Applicant argues (see page 9):
Beginning on page 3 of the Action, paragraph [0070] of Besinga is cited as describing the limitation of "determin[ing], based on the health of the last programmed wordline, a health of [the] next unprogrammed wordline during the bootup process." However, paragraph [0070] of Besinga describes analyzing a set of erased pages to obtain a charge gain metric. Paragraph [0070] of Besinga does not describe determining the charge gain metric of the erased pages based on the health of a last programmed wordline. Rather, Besinga describes that "[t]o obtain the charge gain metric, the PCT component 113 can cause the set of erased pages to be read with a wordline-level detection technique."
Accordingly, Applicant respectfully submits that Besinga does not disclose or suggest "determin[ing], based on the health of the last programmed wordline, a health of the next unprogrammed wordline during the bootup process," as recited in amended independent claim 9.
The remaining references of record do not remedy the deficiencies of Besinga.
Applicant accordingly respectfully requests withdrawal of the § 102 rejections of amended independent claims 9 and 15.
Amended independent claims 1 and 15 include analogous limitations benefiting from the arguments presented above.
The Examiner respectfully disagrees. BESINGA discloses determining if an open block is valid for programming ([0066]). To make this determination, a charge loss metric is measured to determined if it satisfies a threshold ([0066]). This measurement can is based on programmed pages, which can include the most recent programmed page, which would be a last programmed word line ([0066], [0075], [0077]). Passing this test will result in the block being considered valid for programming. BESINGA discloses that the system can additionally analyze a set of erased pages where programming will resume, these would be the next unprogrammed word line ([0070]). The health of the next programmed word line is based on a charge gain metric. To keep the block open for programming, the charge loss metric and the charge gain metric would need to satisfy their respective thresholds ([0076]). The system can decide to determine the charge gain metric in response to the measurement of the charge loss metric ([0074]). Therefore, the health of the next unprogrammed word line is determined based on the health determination of the last programmed word line.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 9, 12, 15 and 18 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by BESINGA (U.S. Patent Application Publication #2023/0268014).
9. BESINGA discloses A system comprising: a storage device including a virtual block storing user data (see [0077]: the open block includes a set of programmed pages and a set of erased pages, the programmed pages would be the user data), the virtual block including a last programmed wordline (see [0077]: most recent programmed page) and a next unprogrammed wordline (see [0070]: first erased page where programming shall resume); and a controller (see [0062]: memory sub-system controller) to: determine a health of the last programmed wordline (see [0077]: page with newest programmed data) during a bootup process of a storage device that includes the virtual block (see [0064]-[0067]: at power-up the processing logic selects an open block, a charge loss metric is obtained, the charge loss metric is a measure of the health of the block), wherein the bootup process occurs after a power cycle, wherein the virtual block is in an open state (see [0066]: open block); determine, based on the health of the last programmed wordline, a health of the next unprogrammed wordline during the bootup process (see [0070]: charge gain metric of the first erased page); and program additional user data on the virtual block after the bootup process (see [0076]: if the open block is available for programming, the block is kept open for additional programming, which would be the user data), wherein the additional user data is programmed based on the determination of the health of the last programmed wordline and based on the determination of the health of the next unprogrammed wordline (see [0066]: yes path for determining open block is valid for programming; [0075]: if the charge loss metric satisfies the threshold for the last programmed wordline and the charge gain metric satisfies the threshold for the next unprogrammed word line the block is kept open for programming additional user data).
12. The system of claim 9, the determination of the health of the last programmed wordline including: determining that the last programmed wordline is healthy (see [0067]: charge loss metric for written page); and the determination of the health of the next unprogrammed wordline including determining that the next unprogrammed wordline is healthy (see [0071]: charge gain metric for erased page); determine that the next unprogrammed wordline is healthy (see [0071]: charge gain metric for erased page); the programming of the additional user data on the virtual block based on both of the determination that the last programmed wordline is healthy and the determination that the next unprogrammed wordline is healthy (see [0066], [0074]: yes path for determining open block is valid for programming; [0075]: if the charge loss metric satisfies the threshold for the last programmed wordline and the charge gain metric satisfies the threshold for the next unprogrammed word line the block is kept open for programming additional user data).
15. BESINGA discloses A non-transitory computer-readable medium storing a set of instructions, the set of instructions (see [0091]: machine-readable medium having stored thereon instructions) comprising: one or more instructions that, when executed by one or more processors of a controller (see [0062]: memory sub-system controller), cause the controller to: determine a health of a last programmed wordline (see [0077]: page with newest programmed data) of a virtual block during a bootup process of a storage device that includes the virtual block (see [0064]-[0067]: at power-up the processing logic selects an open block, a charge loss metric is obtained, the charge loss metric is a measure of the health of the block), wherein the bootup process occurs after a power cycle, wherein the virtual block is an open state (see [0066]: open block), and wherein the virtual block includes user data (see [0077]: the open block includes a set of programmed pages and a set of erased pages, the programmed pages would be the user data); determine, based on the health of the last programmed wordline, a health of a next unprogrammed wordline of the virtual block during the bootup process (see [0070]: charge gain metric of the first erased page); and program additional user data on the virtual block after the bootup process (see [0076]: if the open block is available for programming, the block is kept open for additional programming, which would be the user data), wherein the additional user data is programmed based on the determination of the health of the last programmed wordline and based on the determination of the health of the next unprogrammed wordline (see [0066]: yes path for determining open block is valid for programming; [0075]: if the charge loss metric satisfies the threshold for the last programmed wordline and the charge gain metric satisfies the threshold for the next unprogrammed word line the block is kept open for programming additional user data).
18. The non-transitory computer-readable medium of claim 15, the determination of the health of the next unprogrammed wordline including determining that the next unprogrammed wordline is healthy (see [0071]: charge gain metric for erased page); the programming of the additional user data on the virtual block being based on the determination that the next unprogrammed wordline is healthy (see [0066], [0074]: yes path for determining open block is valid for programming).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over BESINGA (U.S. Patent Application Publication #2023/0268014) in view of LEE (U.S. Patent Application Publication #2020/0110547).
1. BESINGA discloses A method comprising: determining, using a first machine learning model (see LEE below), a health of a last programmed wordline (see [0077]: page with newest programmed data) of a virtual block during a bootup process of a storage device that includes the virtual block (see [0064]-[0067]: at power-up the processing logic selects an open block, a charge loss metric is obtained, the charge loss metric is a measure of the health of the block), wherein the virtual block is in an open state (see [0066]: open block), wherein the virtual block includes user data (see [0077]: the open block includes a set of programmed pages and a set of erased pages, the programmed pages would be the user data): determining, based on the health of the last programmed wordline and using a second machine learning model (see LEE below) a health of a next unprogrammed wordline of the virtual block during the bootup process (see [0070]: charge gain metric of the first erased page; [0064]-[0065]: pages are analyzed during a power up event of the memory device); and programming additional user data on the virtual block after the bootup process (see [0076]: if the open block is available for programming, the block is kept open for additional programming, which would be the user data), wherein the additional user data is programmed based on determining the health of the last programmed wordline and based on determining the health of the next unprogrammed wordline (see [0066]: yes path for determining open block is valid for programming; [0075]: if the charge loss metric satisfies the threshold for the last programmed wordline and the charge gain metric satisfies the threshold for the next unprogrammed word line the block is kept open for programming additional user data).
LEE discloses the following limitations that are not disclosed by BESINGA: the health of the last programmed wordline is determined using a first machine learning model (see [0052]-[0056: machine learning core collects information and determines the expected number of errors for memory cells, the expected number of errors would be the health of the word line; [0057]: the machine learning core is trained on multiple machine learning models, the machine learning core loads the appropriate model, this would be a first machine learning model) and the health of the next unprogrammed wordline is determined using a second machine learning model (see [0052]-[0056: machine learning core collects information and determines the expected number of errors for memory cells, the expected number of errors would be the health of the word line; [0057]: the machine learning core is trained on multiple machine learning models, the machine learning core loads the appropriate model, this would be a second machine learning model). Machine learning is used to determine the health of a memory word line in combination with actual checks. This provides a balance between reliability and time required to perform the checks (see [0085]).
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to use a machine learning model to determine health, as disclosed by LEE. One of ordinary skill in the art would have been motivated to make such a modification to strike a balance between reliability and time requirements, as taught by LEE. BESINGA and LEE are analogous/in the same field of endeavor as both references are directed to analysis of memory cells for programming.
2. The method of claim 1, wherein the determination of the health of the last programmed wordline comprises: determining whether the last programmed wordline has been subjected to a data retention degradation (see BESINGA [0067]-[0068]: charge loss metric) or subjected to an erase bake effect.
3. The method of claim 2, wherein the determination of the health of the next unprogrammed wordline comprises: determining whether the next unprogrammed wordline has been subjected to a data retention degradation (see BESINGA [0071]: charge gain metric) or subjected to an erase bake effect.
4. The method of claim 1, comprising: determining, during the bootup process (see BESINGA [0064]-[0066] open block validation is performed during a power up event, which is considered a boot process), a health of a subsequent unprogrammed wordline of the virtual block that is subsequent to the next unprogrammed wordline (see BESINGA [0076]: select another open block for analysis).
5. The method of claim 1,the determination of the health of the last programmed wordline including determining that the last programmed wordline has been subjected to a data retention degradation (see BESINGA [0067]-[0068]: charge loss metric); comprising: causing the virtual block to be in a closed state based on the determination that the last programmed wordline has been subjected to the data retention degradation (see BESINGA [0076]: abandon the open block, this is considered closing the block).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over BESINGA (U.S. Patent Application Publication #2023/0268014) and LEE (U.S. Patent Application Publication #2020/0110547) as applied to claims 1-5 above, and further in view of LIU (U.S. Patent Application Publication #2022/0147252).
6. The method of claim 5 (see BESINGA above), comprising: causing a garbage collection operation to be performed on the virtual block in the closed state to move valid data of the user data and the additional user data to a different virtual block (see LIU below).
LIU discloses the following limitations that are not disclosed by BESINGA: causing a garbage collection operation to be performed on the virtual block in the closed state to move valid data of the user data and the additional user data to a different virtual block (see [0066]: data refresh operation that copies data from one block to another block, this refresh is performed as part of a garbage collection operation). LIU discloses performing media management on power up that includes determining a block is an open block. The system determines a health characteristic of the block (see [0046]-[0048]). The refresh is performed in response to determining the health of the block to prevent errors (see [0049]). BESINGA already discloses performing a health check of an open block. A combination of BESINGA and LIU would result in BESINGA performing a garbage collection on an open block based on the health.
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to perform a garbage collection operation, as disclosed by LIU. One of ordinary skill in the art would have been motivated to make such a modification to prevent errors, as taught by LIU. BESINGA and LIU are analogous/in the same field of endeavor as both references are directed to analyzing the health of open blocks.
Claim(s) 7 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over BESINGA (U.S. Patent Application Publication #2023/0268014) and LEE (U.S. Patent Application Publication #2020/0110547) as applied to claims 1-5 above, and further in view of YEUNG (U.S. Patent Application Publication #2024/0256142).
7. The method of claim 1 (see BESINGA above), the determination of the health of the next unprogrammed wordline including determining that the next unprogrammed wordline has been subjected to an open bake condition after programming the additional user data, and comprising: causing the virtual block to be in a closed state based on the determination that the next unprogrammed wordline has been subjected to the open bake condition (see YEUNG below).
YEUNG discloses the following limitations that are not disclosed by BESINGA: the determination of the health of the next unprogrammed wordline including determining that the next unprogrammed wordline has been subjected to an open bake condition after programming the additional user data (see [00418]: determine whether last page has been programmed, if not this would be the next unprogrammed word line; [0051]: partially programmed word line; [0040]: read window budget, exceeding the read window in considered an open bake condition); causing the virtual block to be in a closed state based on the determination that the next unprogrammed wordline has been subjected to the open bake condition (see [0062]-[0067]: ganged programming operation to copy data from a first block in a partially programmed state to a second block). Eliminating a block that is in an open bake condition mitigates a read window budget that would be imposed (see [0041]).
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to determine if an open bake condition is present, as disclosed by YEUNG. One of ordinary skill in the art would have been motivated to make such a modification to mitigate a read window budget for the memory, as taught by YEUNG. BESINGA and YEUNG are analogous/in the same field of endeavor as both references are directed to managing memory blocks.
8. The method of claim 7, comprising: causing a new virtual block of the storage device to be in an open state for programming of subsequent user data (see YEUNG [0069]: data is copied to a second block, the second block would be the new virtual block).
Claim(s) 10, 11, 16 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over BESINGA (U.S. Patent Application Publication #2023/0268014) in view of LEE (U.S. Patent Application Publication #2020/0110547).
10. The system of claim 9 (see BESINGA above), the controller including a first machine learning model, the determination of the health of the last programmed wordline including using the first machine learning model (see LEE below).
LEE discloses the following limitations that are not disclosed by BESINGA: the controller including a first machine learning model, the determination of the health of the last programmed wordline using the first machine learning model (see [0052]-[0056: machine learning core collects information and determines the expected number of errors for memory cells, the expected number of errors would be the health of the word line; [0057]: the machine learning core is trained on multiple machine learning models, the machine learning core loads the appropriate model, this would be a first machine learning model). Machine learning is used to determine the health of a memory word line in combination with actual checks. This provides a balance between reliability and time required to perform the checks (see [0085]).
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to use a machine learning model to determine health, as disclosed by LEE. One of ordinary skill in the art would have been motivated to make such a modification to strike a balance between reliability and time requirements, as taught by LEE. BESINGA and LEE are analogous/in the same field of endeavor as both references are directed to analysis of memory cells for programming.
11. The system of claim 10, the controller including a second machine learning model, the determination of the health of the next unprogrammed wordline including using the second machine learning model (see LEE [0052]-[0056: machine learning core collects information and determines the expected number of errors for memory cells, the expected number of errors would be the health of the word line; [0057]: the machine learning core is trained on multiple machine learning models, the machine learning core loads the appropriate model, this would be a second machine learning model).
16. The non-transitory computer-readable medium of claim 15 (see BESINGA above), the determination of the health of the last programmed wordline including using a first machine learning model (see LEE below).
LEE discloses the following limitations that are not disclosed by BESINGA: the determination of the health of the last programmed wordline including using a first machine learning model (see [0052]-[0056: machine learning core collects information and determines the expected number of errors for memory cells, the expected number of errors would be the health of the word line; [0057]: the machine learning core is trained on multiple machine learning models, the machine learning core loads the appropriate model, this would be a first machine learning model). Machine learning is used to determine the health of a memory word line in combination with actual checks. This provides a balance between reliability and time required to perform the checks (see [0085]).
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to use a machine learning model to determine health, as disclosed by LEE. One of ordinary skill in the art would have been motivated to make such a modification to strike a balance between reliability and time requirements, as taught by LEE. BESINGA and LEE are analogous/in the same field of endeavor as both references are directed to analysis of memory cells for programming.
17. The non-transitory computer-readable medium of claim 15 (see BESINGA above), the determination of the health of the next unprogrammed wordline including using a second machine learning model (see LEE below).
LEE discloses the following limitations that are not disclosed by BESINGA: the determination of the health of the next unprogrammed wordline including using a second machine learning model (see [0052]-[0056: machine learning core collects information and determines the expected number of errors for memory cells, the expected number of errors would be the health of the word line; [0057]: the machine learning core is trained on multiple machine learning models, the machine learning core loads the appropriate model, this would be a second machine learning model). Machine learning is used to determine the health of a memory word line in combination with actual checks. This provides a balance between reliability and time required to perform the checks (see [0085]).
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to use a machine learning model to determine health, as disclosed by LEE. One of ordinary skill in the art would have been motivated to make such a modification to strike a balance between reliability and time requirements, as taught by LEE. BESINGA and LEE are analogous/in the same field of endeavor as both references are directed to analysis of memory cells for programming.
Claim(s) 13, 14, 19 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over BESINGA (U.S. Patent Application Publication #2023/0268014) in view of LIU (U.S. Patent Application Publication #2022/0147252).
13. The system of claim 9, the storage device comprising an other virtual block (see [0076]: another open block), the determination of the health of the last programmed wordline including determining that the last programmed wordline is unhealthy (see BESINGA [0067]-[0068]: charge loss metric outside the threshold), wherein the controller is to: cause the virtual block to be in a closed state based on the determination that the last programmed wordline is unhealthy (see BESINGA [0076]: abandon the open block, this is considered closing the block); and cause a garbage collection operation to be performed to move valid data of the valid data and the additional user data of the virtual block, in the closed state, to the other virtual block (see LIU below).
LIU discloses the following limitations that are not disclosed by BESINGA: cause a garbage collection operation to be performed to move valid data of the valid data and the additional user data of the virtual block, in the closed state, to the other virtual block (see [0066]: data refresh operation that copies data from one block to another block, this refresh is performed as part of a garbage collection operation). LIU discloses performing media management on power up that includes determining a block is an open block. The system determines a health characteristic of the block (see [0046]-[0048]). The refresh is performed in response to determining the health of the block to prevent errors (see [0049]). BESINGA already discloses performing a health check of an open block. A combination of BESINGA and LIU would result in BESINGA performing a garbage collection on an open block based on the health.
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to perform a garbage collection operation, as disclosed by LIU. One of ordinary skill in the art would have been motivated to make such a modification to prevent errors, as taught by LIU. BESINGA and LIU are analogous/in the same field of endeavor as both references are directed to analyzing the health of open blocks.
14. The system of claim 13, the storage device including a new virtual block, the determination of the health of the next unprogrammed wordline including determining that the next unprogrammed wordline is unhealthy after programming the additional user data (see BESINGA [0067]-[0068]: charge loss metric outside the threshold) wherein the controller is to: cause the virtual block to be in a closed state based on the determination that the next unprogrammed wordline is unhealthy (see BESINGA [0076]: abandon the open block, this is considered closing the block); and cause the new virtual block to be in an open state for programming of subsequent user data (see BESINGA [0076]: after abandoning the block, another open block can be selected for analysis).
19. The non-transitory computer-readable medium of claim 15, the determination of the health of the last programmed wordline including-determining that the last programmed wordline is unhealthy (see BESINGA [0067]-[0068]: charge loss metric outside the threshold) wherein the one or more instructions further cause the controller to: cause the virtual block to be in a closed state based on the determination that the last programmed wordline is unhealthy (see BESINGA [0076]: abandon the open block, this is considered closing the block); and cause a garbage collection operation to be performed to move valid data of the user data and the additional user data of the virtual block, in the closed state, to a different virtual block (see LIU below).
LIU discloses the following limitations that are not disclosed by BESINGA: cause a garbage collection operation to be performed to move valid data of the user data and the additional user data of the virtual block, in the closed state, to a different virtual block (see [0066]: data refresh operation that copies data from one block to another block, this refresh is performed as part of a garbage collection operation). LIU discloses performing media management on power up that includes determining a block is an open block. The system determines a health characteristic of the block (see [0046]-[0048]). The refresh is performed in response to determining the health of the block to prevent errors (see [0049]). BESINGA already discloses performing a health check of an open block. A combination of BESINGA and LIU would result in BESINGA performing a garbage collection on an open block based on the health.
It would have been obvious, before the effective filing date of the claimed invention, to a person having ordinary skill in the art to which said subject matter pertains to modify BESINGA to perform a garbage collection operation, as disclosed by LIU. One of ordinary skill in the art would have been motivated to make such a modification to prevent errors, as taught by LIU. BESINGA and LIU are analogous/in the same field of endeavor as both references are directed to analyzing the health of open blocks.
20. The non-transitory computer-readable medium of claim 19, the determination of the health of the next unprogrammed wordline including-determining that the next unprogrammed wordline is unhealthy after programming the additional user data (see BESINGA [0067]-[0068]: charge loss metric outside the threshold), wherein the one or more instructions further cause the controller to: cause the virtual block to be in a closed state based on the determination that the next unprogrammed wordline is unhealthy (see BESINGA [0076]: abandon the open block, this is considered closing the block); and cause a new virtual block of the storage device to be in an open state for programming of subsequent user data (see BESINGA [0076]: after abandoning the block, another open block can be selected for analysis).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EDWARD J DUDEK JR whose telephone number is (571)270-1030. The examiner can normally be reached Monday - Friday, 8:00A-4:00P.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hosain T Alam can be reached at 571-272-3978. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/EDWARD J DUDEK JR/Primary Examiner, Art Unit 2132
