[go: up one dir, main page]

CN107967928A - A kind of flash chip life-span prediction method based on mathematical model - Google Patents

A kind of flash chip life-span prediction method based on mathematical model Download PDF

Info

Publication number
CN107967928A
CN107967928A CN201710973383.4A CN201710973383A CN107967928A CN 107967928 A CN107967928 A CN 107967928A CN 201710973383 A CN201710973383 A CN 201710973383A CN 107967928 A CN107967928 A CN 107967928A
Authority
CN
China
Prior art keywords
flash chip
flash
chip
data
flash memory
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201710973383.4A
Other languages
Chinese (zh)
Other versions
CN107967928B (en
Inventor
潘玉茜
李四林
刘政林
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuhan Zhifu Semiconductor Technology Co.,Ltd.
Original Assignee
Wuhan Memory Storage Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Wuhan Memory Storage Technology Co Ltd filed Critical Wuhan Memory Storage Technology Co Ltd
Priority to CN201710973383.4A priority Critical patent/CN107967928B/en
Publication of CN107967928A publication Critical patent/CN107967928A/en
Application granted granted Critical
Publication of CN107967928B publication Critical patent/CN107967928B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C16/00Erasable programmable read-only memories
    • G11C16/02Erasable programmable read-only memories electrically programmable
    • G11C16/06Auxiliary circuits, e.g. for writing into memory
    • G11C16/34Determination of programming status, e.g. threshold voltage, overprogramming or underprogramming, retention
    • G11C16/349Arrangements for evaluating degradation, retention or wearout, e.g. by counting erase cycles
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/002Biomolecular computers, i.e. using biomolecules, proteins, cells
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C29/00Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
    • G11C29/56External testing equipment for static stores, e.g. automatic test equipment [ATE]; Interfaces therefor
    • G11C29/56004Pattern generation
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C29/00Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
    • G11C29/56External testing equipment for static stores, e.g. automatic test equipment [ATE]; Interfaces therefor
    • G11C29/56008Error analysis, representation of errors
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C29/00Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
    • G11C29/56External testing equipment for static stores, e.g. automatic test equipment [ATE]; Interfaces therefor
    • G11C29/56016Apparatus features

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Biophysics (AREA)
  • Evolutionary Computation (AREA)
  • Molecular Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Artificial Intelligence (AREA)
  • Biomedical Technology (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Organic Chemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Chemical & Material Sciences (AREA)
  • Techniques For Improving Reliability Of Storages (AREA)
  • Read Only Memory (AREA)
  • For Increasing The Reliability Of Semiconductor Memories (AREA)

Abstract

The invention belongs to flash chip forecasting technique in life span, more particularly, to a kind of flash chip life-span prediction method based on mathematical model.The present invention tests the physical message and life information of systematic collection sample flash chip by flash chip first, then the data message obtained with intelligent algorithm to test carries out calculation process and obtains flash chip Life Prediction Model, the physical message of flash chip to be predicted is obtained finally by a small amount of test, physical message input prediction model is obtained into the bimetry value of flash chip.The flash memory test sample method proposed in the present invention is tested using the random data of belt restraining as test data set, can the data manipulation of more efficient simulation flash chip in actual use, obtained flash memory physical message and life information be more valuable.

Description

A kind of flash chip life-span prediction method based on mathematical model
Technical field
The invention belongs to flash chip forecasting technique in life span, more particularly, to a kind of flash chip longevity based on mathematical model Order Forecasting Methodology.
Background technology
In hyundai electronics information industry, memory has very heavy always as the carrier that data are stored in electronic equipment The status wanted.At present, the memory of in the market is broadly divided into:Volatile memory and nonvolatile memory.Flash chip is A kind of nonvolatile memory, it can preserve data for a long time after a power failure, and have that data transmission bauds is fast, is produced into The advantages that this is low, memory capacity is big, so being widely used among electronic equipment.
At present, due to continuous progressive, the reduction of distance and the oxidated layer thickness between storage unit of semiconductor fabrication process Reduction make in flash chip intrinsic wrong increasingly severe, what traditional error correction code approach can not meet flash chip can By property demand, the integrity problem of flash memory has become the important topic of current storage research field.The service life of flash memory The number of operations being able to carry out of flash memory before failure is represented, is the most important parameter index of flash chip.Predict the surplus of flash memory Remaining service life, can allow flash memory device user using the loss state that memory is understood during equipment, avoid because Memory cell fail and caused by data be lost in.Meanwhile the flash memory remaining life that memory user can also obtain according to prediction Information, changes storage data policy and efficiently uses flash chip preservation data.
The content of the invention
The above-mentioned technical problem of the present invention is mainly what is be addressed by following technical proposals:
A kind of flash chip life-span prediction method based on mathematical model, it is characterised in that according to one kind of flash chip The life prediction value of the combined prediction flash chip of physical quantity or several physical quantitys.The flash chip physical quantity includes:Flash memory The programming time of storage chip, read access time, erasing time, program current, reading electric current, erasing electric current, threshold voltage distribution And error rate.The specific steps of the method include:
Step 1, sample drawn is as sample flash memory from flash memory products set, in flash memory products set in addition to sample flash memory For flash memory to be tested, and sample flash chip be connected with flash memory test system and starts test collection to establish the flash chip service life pre- Survey the flash chip physical message and flash chip life information needed for model;Flash chip to be tested and flash memory are tested at the same time System connection starts the flash chip physical message and flash chip life information needed for test collection prediction model;
Step 2, the combination of a kind of physical message or several physical messages that are obtained testing is as mathe-matical map in algorithm The input variable of relation, output variable of the flash chip life prediction value as mathe-matical map relation, is handled by intelligent algorithm Data founding mathematical models;
Step 3, test flash memory Life Prediction Model, using the flash chip physical quantity needed for prediction model as life prediction The input of model, the remaining lifetime value of the output valve prediction target flash product of mathematic(al) expectation prediction model.
Preferably, in the step 1, sample flash memory is necessary for the flash chip of same type under same manufacturing process; The chip sample of identical quantity is randomly selected from the chip of different batches, to ensure the diversity of sample.Wherein, batch of sampling Secondary is to randomly select, and sample size can be sampled batch flash chip total amount 1 percent, also, flash memory tests system Including host computer test control system and flash memory control module.Wherein, host computer test system writes journey by computer language Sequence system is realized;Flash memory control module is realized by FPGA.
Preferably, in the step 1, flash chip physical message includes:Flash chip is from beginning to use to can not be just The programming time of block, read access time, erasing time, program current, reading electric current, wiping in normal flash memory storage chip interior during use Except electric current, threshold voltage distribution and error rate information.In the step 2, service life of flash memory predicts the defeated of mathe-matical map relation Enter one or more of combinations that variable is above-mentioned physical message.In the step 1, flash chip life information is flash chip From begin to use to can not during normal use interior experience program/erase operation cycle number.
It is preferably, described
The acquisition modes of flash chip memory block programming time are:Programming time is set to record mould in flash memory test system Block;The programming time logging modle clock cycle that record passes through while flash memory starts to write data manipulation is receiving flash memory core Stop recording clock periodicity after piece returned data programming complement mark;Programming time value is multiplied by volume for clock cycle duration Journey clock periodicity.
The acquisition modes of flash chip memory block erasing time are with programming time acquisition modes:By the wiping in test system Except the lasting clock periodicity of time recording module record erasing operation, erasing time value is multiplied by wiping for clock cycle duration Except clock periodicity.Flash memory chip storage unit threshold voltage distribution acquisition modes be:Test system is sent to flash chip The reading reference voltage that flash memory is altered in steps in READ-RETRY command sets reads simultaneously data according to reading data Data-Statistics threshold voltage Distribution.
Flash chip storage block error rate acquisition modes be:Test system, which performs flash chip, reads data manipulation from sudden strain of a muscle Middle reading data are deposited, the test data of the data of reading and write-in is carried out contrast mistake of statistics data amount check by test system, wrong Rate is number of errors divided by total data amount check by mistake.
Preferably, in the step 1, test collection flash chip physical message is specific with flash chip life information Step includes:
Step 5.1, the randomly drawing sample chip from flash chip set, sample flash chip and test system are connected Connect.
Step 5.2, randomly choose memory block from each sample flash chip, is sent out by the system of testing to flash memory storage block Test data set is sent, write-in data manipulation is performed to flash memory storage block.
Step 5.3, after having sent test data vector, keep the data stored in flash memory storage block for a period of time, protects Time length is deposited to be determined according to the type of flash chip;Flash chip is performed by the system of testing and reads data manipulation, test system System will read data compared with the test data sent, records and preserves error data information, is not preserved if not malfunctioning; After having preserved error message, erasing data manipulation performs flash chip by the system of testing.
Time that step 5.4, the operation for repeating step 5.2 and step 5.3, recording step 5.2 and step 5.3 operate Number;When number of operations reaches setting value, each memory block of sample flash memory in the last step 5.2 operation of test system record Write the duration of data manipulation and preserve recorded Duration Information;Meanwhile test the last step of system record The duration of each memory block erasing data manipulation of sample flash memory and recorded duration letter is preserved in rapid 5.3 operation Breath.
Step 5.5, the threshold voltage distribution by testing systematic survey flash chip unit, record the threshold of simultaneously storage unit Threshold voltage distributed intelligence;The step is optional step, if prediction object does not have READ-RETRY functions in testing procedure not Including the step.
Step 5.6, the data error rate information tested system statistics and preserve each memory block of flash chip.
Step 5.7, repeat step step 5.4 arrive step 5.6, until flash chip reaches lifetime limitation;Test system is united Count the program/erase operation cycle number of flash chip.
In the present invention, step 2 is the intelligent algorithm using genetic programming algorithm as founding mathematical models, institute in the present invention The intelligent algorithm stated is not limited to the algorithm.Service life of flash memory value refers to programming/wiping that flash memory products can perform before disabling Except periodicity, specific steps include:
Step 6.1, computer program initialization life prediction function set;Life prediction function screening equation is set.
Step 6.2, by test data substitute into life prediction function set in each function;Function result is calculated, that is, is dodged Deposit chip life prediction value;The flash chip life prediction value being calculated actual life value corresponding with test data is substituted into Fitness equation, life prediction function is screened according to fitness equation calculation result.
Step 6.3, on the basis of the life prediction function set by screening, it is new using the generation of gene programmed method Function set.
Step 6.4, the operation that step 6.2 and step 6.3 are repeated to new function set, number of operations reach setting Upper limit value when terminate operation;Upper limitation is set according to forecast demand.
Step 6.5, select the predicted value function optimal with actual life value matching degree from set, obtains life prediction number Learn model.
Life prediction function described in step 6.1 includes operator, coefficient and input variable;Wherein coefficient is calculating The constant that machine program randomly generates, input variable are programming time, erasing time, threshold voltage distribution and several tests of error rate Data acquisition system, wherein, threshold voltage is distributed as optional input variable;A kind of test data set represents an input and becomes Amount, the input variable number that function is included can be set according to forecast demand.Life prediction function is realized by the form of matrix Set.
Wherein, fitness equation refers to that the absolute value of service life of flash memory predicted value and the difference of test value weights in step 6.2 With.Fitness equation is embodied as:F=ω1|A1-B1|+ω2|A2-B2|+…+ωn|An-Bn|;Wherein, Ai represents prediction Value;Bi is actual value;ω i are weights, and the value of ω i is more than 0 and is less than or equal to 1;N is total sample number.
The operation of new function set described in step 6.3 includes:Intersection, mutation and the breeding operation of function.The letter Several crossover operations be specially exchange tree function node, using the function obtained after exchange as new function set into Member.Mutation operation randomly generates function by computer program, and the function randomly generated is replaced to the expression formula point of former generation's function Branch obtains new offspring's function.Gene programming breeding operation be the function that will be met the requirements after selection operation by certain probability into Row replicates, and the function after duplication is as new offspring.
Therefore, the invention has the advantages that:1. the flash memory test sample method proposed in the present invention is using belt restraining Random data is tested as test data set, being capable of the number of more efficient simulation flash chip in actual use According to operation, obtained flash memory physical message and life information is more valuable.2. the present invention is using a variety of dependability parameters as the longevity Order prediction model input, with only using a kind of accuracy of parameter bimetry value compared with the Life Prediction Model of foundation more It is high.3. the present invention proposes a kind of service life of flash memory prediction side based on the intelligent algorithm modeling technique in current computer realm forward position Method;Compared with current technology, the advance of this method is based on experimental data to establish flash memory core by intelligent algorithm Piece life prediction mathematical model prediction service life of flash memory value.
Brief description of the drawings
Fig. 1 is a kind of flow diagram of the flash chip life-span prediction method based on mathematical model of the embodiment of the present invention.
Fig. 2 is a kind of flow chart of reliability of flash memory test method of the embodiment of the present invention.
Fig. 3 is the structure chart that a kind of flash memory of the embodiment of the present invention tests system.
Fig. 4 is a kind of service life of flash memory prediction model modeling procedure based on gene programming of the embodiment of the present invention.
Fig. 5 is the life prediction function structure exemplary plot used in the embodiment of the present invention.
Fig. 6 is the matrix form exemplary plot of life prediction function in the embodiment of the present invention.
Fig. 7 is that gene programs crossover operation exemplary plot in the embodiment of the present invention.
Fig. 8 is that gene programs mutation operation exemplary plot in the embodiment of the present invention.
Fig. 9 is gene programming breeding operation example figure in the embodiment of the present invention.
Embodiment
Below with reference to the embodiments and with reference to the accompanying drawing the technical solutions of the present invention will be further described.
Embodiment:
It is below in conjunction with attached drawing and specifically real in order to enable the above objects, features and advantages of the present invention to become apparent from Example is applied to be described in detail.
Fig. 1 predicts the flow diagram in flash chip service life, the flow of flash chip life prediction shown in figure for the present invention Suitable for all flash chip types, detailed explain is carried out to Fig. 1 by embodiment of a kind of flash chip product below It is bright.
In the present embodiment, using more pole unit nand flash memories (MLC NAND flash) product under certain manufacturing process as survey Try object and life prediction object.Step S01 as shown in Figure 1, according to following rule extraction sample from the flash memory products set This:Sample flash memory is necessary for the flash chip of same type under same manufacturing process;Randomly selected from the chip of different batches The chip sample of identical quantity, to ensure the diversity of sample.Wherein, the batch of sampling is randomly selects, and sample size can be with To be sampled 1 the percent of batch flash chip total amount.
Step S02, sample flash chip and flash memory test system be connecteds and starts test collection and establishes the flash chip service life Flash chip physical message and flash chip life information needed for prediction model.The flash chip physical message includes:Dodge Chip is deposited from beginning to use to can not the programming time of block, erasing time, threshold value in interior flash memory storage chip during normal use (threshold voltage is distributed as optional thing to the data message that voltage's distribiuting and error rate change under the conditions of increasing in the program/erase cycle Manage information).
The acquisition modes of flash chip memory block programming time are:Programming time is set to record mould in flash memory test system Block;The programming time logging modle clock cycle that record passes through while flash memory starts to write data manipulation is receiving flash memory core Stop recording clock periodicity after piece returned data programming complement mark;Programming time value is multiplied by volume for clock cycle duration Journey clock periodicity.
The acquisition modes of flash chip memory block erasing time with programming time acquisition modes similarly, by test system The lasting clock periodicity of erasing time logging modle record erasing operation, erasing time value are multiplied by for clock cycle duration Wipe clock periodicity.Flash memory chip storage unit threshold voltage distribution acquisition modes be:Test system is sent out to flash chip The reading reference voltage that flash memory is altered in steps in READ-RETRY command sets is sent to read simultaneously data electric according to data Data-Statistics threshold value is read Pressure distribution.
Flash chip storage block error rate acquisition modes be:Test system, which performs flash chip, reads data manipulation from sudden strain of a muscle Middle reading data are deposited, the test data of the data of reading and write-in is carried out contrast mistake of statistics data amount check by test system, wrong Rate is number of errors divided by total data amount check by mistake.
The flash memory test method used in step S02, its flow are as shown in Figure 2.According to Fig. 2, the specific step of flash memory test Suddenly it is:
(1) the randomly drawing sample chip from flash chip set, sample flash chip is connected with test system.
(2) memory block is randomly choosed from each sample flash chip, is sent and surveyed to flash memory storage block by the system of testing Data acquisition system is tried, write-in data manipulation is performed to flash memory storage block.
(3) after having sent test data vector, the data stored in flash memory storage block are kept for a period of time, the holding time Length is determined according to the type of flash chip;Flash chip is performed by the system of testing and reads data manipulation, test system will be read Go out data compared with the test data sent, record and preserve error data information, do not preserved if not malfunctioning;Preserve After error message, erasing data manipulation performs flash chip by the system of testing.
(4) number of the operation of step (2) and step (3), recording step (2) and step (3) operation is repeated;Work as behaviour When reaching setting value as number, each memory block write-in number of sample flash memory in the last step (2) operation of test system record According to operation duration and preserve recorded Duration Information;Meanwhile test the last step (3) behaviour of system record The duration of each memory block erasing data manipulation of sample flash memory and recorded Duration Information is preserved in work.
(5) it is distributed by testing the threshold voltage of systematic survey flash chip unit, records and the threshold value of storage unit is electric Press distributed intelligence;The step is optional step, and do not have if prediction object does not include if READ-RETRY functions in testing procedure The step.
(6) test system statistics and preserve the data error rate information of each memory block of flash chip.
(7) repeat step (4) arrives step (6), until flash chip reaches lifetime limitation;Test system statistics flash chip Program/erase operation cycle number.
The flash memory test system used in step S02, its structure is as shown in figure 3, mainly include host computer testing and control system System and flash memory control module.Wherein, host computer test system is write programming system by computer language and is realized;Flash memory controls mould Block is realized by FPGA.
Step S03, data founding mathematical models are handled by intelligent algorithm, will test obtained physical message as algorithm The input variable of middle mathe-matical map relation, output variable of the flash chip life prediction value as mathe-matical map relation;This implementation In example the calculation is not limited to using genetic programming algorithm as the intelligent algorithm of founding mathematical models, heretofore described intelligent algorithm Method.Service life of flash memory value refers to the program/erase periodicity that flash memory products can perform before disabling.
In the present embodiment step S03, flow such as Fig. 4 institutes of service life of flash memory prediction model are established using genetic programming algorithm Show.According to Fig. 4, concretely comprising the following steps for service life of flash memory prediction model is established:
(1) computer program initialization life prediction function set;Life prediction function screening equation is set.
(2) test data is substituted into each function in life prediction function set;Calculate function result, i.e. flash chip Life prediction value;The flash chip life prediction value being calculated actual life value corresponding with test data is substituted into fitness Equation, life prediction function is screened according to fitness equation calculation result.
(3) on the basis of the life prediction function set by screening, new function is generated using gene programmed method Set.
(4) operation of step (2) and step (3) is repeated to new function set, number of operations reaches the upper of setting Operation is terminated during limit value;Upper limitation is set according to forecast demand.
(5) the predicted value function optimal with actual life value matching degree is selected from set, obtains life prediction mathematical modulo Type.
Establish the required data processing operation of flash chip Life Prediction Model to realize by computer program, made Computer language is not limited to a certain computer language.
It is as shown in Figure 5 according to the definition of gene programming, the expression way of the life prediction function described in step (1).It is described Function includes operator, coefficient and input variable;Wherein coefficient is the constant that computer program randomly generates, and input variable is volume (threshold voltage is distributed as optional input and becomes for journey time, erasing time, threshold voltage distribution and several test data set of error rate Amount);A kind of test data set represents an input variable, and the input variable number that function is included can be according to prediction need Ask setting.Computer program can realize life prediction function set by the form of matrix, specific as shown in Figure 6.
Step (2) the fitness equation refers to the absolute value weighted sum of service life of flash memory predicted value and the difference of test value. Fitness equation is embodied as:F=ω1|A1-B1|+ω2|A2-B2|+…+ωn|An-Bn|;Wherein, fitness equation represents Symbol is F;Ai represents predicted value;Bi is actual value;ω i are weights, and the value of ω i is more than 0 and is less than or equal to 1;N is total for sample Number.
The definition programmed according to gene, the operation of the new function set described in step (3) include:The intersection of function, dash forward Become and breeding operates.The crossover operation of the function is as shown in fig. 7, concrete operations are incited somebody to action to exchange the node of tree function The function obtained after exchange is as new function set member.The schematic diagram of mutation operation is as shown in figure 8, mutation operation passes through meter Calculation machine program randomly generates function, and the expression formula branch that the function randomly generated is replaced to former generation's function obtains new offspring's letter Number.The schematic diagram of gene programming breeding operation is as shown in figure 9, breeding operates the function that will be met the requirements after selection operation by one Determine probability to be replicated, the function after duplication is as new offspring.
In the present invention, experimental data is divided into two groups:Training data set and validation data set are closed.The present invention is using friendship The method training mathematical model of fork verification, is divided into 5 groups by experimental data.Wherein 4 groups are used to train, and 1 group is used to verify.Per height Experimental data set will be all verified once.
Step S04, test Life Prediction Model is closed using validation data set.In the present invention, by calculating root-mean-square error Test flash memory Life Prediction Model:Wherein, RMSE represents for root-mean-square error Symbol;N is total sample number;Xobs,iFor i-th of flash chip lifetime measurement value;Xmodel,iI-th of flash chip life prediction mould Type predicted value.
Step S05, programming time and the erasing time of flash memory to be predicted are measured using the flash memory test platform in step S02 Etc. physical message, the input variable using the physical message that measurement obtains as Life Prediction Model, mathematic(al) expectation prediction model Output valve predicts the remaining lifetime value of target flash product.
Specific embodiment described herein is only to spirit explanation for example of the invention.Technology belonging to the present invention is led The technical staff in domain can do various modifications or additions to described specific embodiment or replace in a similar way Generation, but without departing from spirit of the invention or beyond the scope of the appended claims.

Claims (5)

1. a kind of flash chip life-span prediction method based on mathematical model, it is characterised in that according to a kind of thing of flash chip The life prediction value of the combined prediction flash chip of reason amount or several physical quantitys;The flash chip physical quantity includes:Flash memory is deposited Store up the programming time of chip, read access time, the erasing time, program current, read electric current, erasing electric current, threshold voltage distribution and Error rate;The specific steps of the method include:
Step 1, sample drawn is as sample flash memory from flash memory products set, to treat in addition to sample flash memory in flash memory products set Test flash memory, and sample flash chip and flash memory test system be connected and starts test collection and establishes flash chip life prediction mould Flash chip physical message and flash chip life information needed for type;Flash chip to be tested and flash memory are tested into system at the same time Connection starts the flash chip physical message and flash chip life information needed for test collection prediction model;
Step 2, the combination of a kind of physical message or several physical messages that are obtained testing is as mathe-matical map relation in algorithm Input variable, output variable of the flash chip life prediction value as mathe-matical map relation, data are handled by intelligent algorithm Founding mathematical models;
Step 3, test flash memory Life Prediction Model, using the flash chip physical quantity needed for prediction model as Life Prediction Model Input, mathematic(al) expectation prediction model output valve prediction target flash product remaining lifetime value.
A kind of 2. flash chip life-span prediction method based on mathematical model according to claim 1, it is characterised in that institute State in step 1, sample flash memory is necessary for the flash chip of same type under same manufacturing process;From the chip of different batches with Machine extracts the chip sample of identical quantity, to ensure the diversity of sample;Wherein, the batch of sampling is randomly selects, sample number Amount can be sampled batch flash chip total amount 1 percent, also, flash memory test system includes host computer testing and control System and flash memory control module;Wherein, host computer test system is write programming system by computer language and is realized;Flash memory controls Module is realized by FPGA.
A kind of 3. flash chip life-span prediction method based on mathematical model according to claim 1, it is characterised in that institute State in step 1, flash chip physical message includes:Flash chip is from beginning to use to can not interior flash memory storage during normal use Programming time, read access time, erasing time, program current, reading electric current, erasing electric current, threshold voltage distribution and the mistake of chip Rate data message by mistake;In the step 2, the input variable of service life of flash memory prediction mathe-matical map relation is the one of above-mentioned physical message Kind or several combinations;In the step 1, flash chip life information is flash chip from beginning to use to can not normal use The program/erase operation cycle number of experience in period.
A kind of 4. flash chip life-span prediction method based on mathematical model according to claim 3, it is characterised in that institute State
The acquisition modes of flash chip memory block programming time are:Programming time logging modle is set in flash memory test system; The programming time logging modle clock cycle that record passes through while flash memory starts to write data manipulation is receiving flash chip Stop recording clock periodicity after returned data programming complement mark;Programming time value is multiplied by programming for clock cycle duration Clock periodicity;
The acquisition modes of flash chip memory block erasing time are with programming time acquisition modes:During by erasing in test system Between the lasting clock periodicity of logging modle record erasing operation, when erasing time value is that clock cycle duration is multiplied by erasing Clock periodicity;Flash memory chip storage unit threshold voltage distribution acquisition modes be:Test system sends READ- to flash chip The reading reference voltage that flash memory is altered in steps in RETRY command sets reads simultaneously data according to reading data Data-Statistics threshold voltage distribution;
Flash chip storage block error rate acquisition modes be:Test system, which performs flash chip, reads data manipulation from flash memory Data are read, the test data of the data of reading and write-in is carried out contrast mistake of statistics data amount check, error rate by test system For number of errors divided by total data amount check.
A kind of 5. flash chip life-span prediction method based on mathematical model according to claim 1, it is characterised in that institute State in step 1, flash chip physical message and the specific steps of flash chip life information are collected in test to be included:
Step 5.1, the randomly drawing sample chip from flash chip set, sample flash chip is connected with test system;
Step 5.2, randomly choose memory block from each sample flash chip, is sent and surveyed to flash memory storage block by the system of testing Data acquisition system is tried, write-in data manipulation is performed to flash memory storage block;
Step 5.3, after having sent test data vector, keep in flash memory storage block the data that store for a period of time, during preservation Between length determined according to the type of flash chip;Flash chip is performed by the system of testing and reads data manipulation, test system will Data are read compared with the test data sent, records and preserves error data information, do not preserved if not malfunctioning;Preserve After complete error message, erasing data manipulation performs flash chip by the system of testing;
The number that step 5.4, the operation for repeating step 5.2 and step 5.3, recording step 5.2 and step 5.3 operate;When When number of operations reaches setting value, each memory block write-in of sample flash memory in the last step 5.2 operation of test system record The duration of data manipulation simultaneously preserves recorded Duration Information;Meanwhile test the last step 5.3 of system record The duration of each memory block erasing data manipulation of sample flash memory and recorded Duration Information is preserved in operation;
Step 5.5, the threshold voltage distribution by testing systematic survey flash chip unit, record and the threshold value of storage unit are electric Press distributed intelligence;The step is optional step, and do not have if prediction object does not include if READ-RETRY functions in testing procedure The step;
Step 5.6, the data error rate information tested system statistics and preserve each memory block of flash chip;
Step 5.7, repeat step step 5.4 arrive step 5.6, until flash chip reaches lifetime limitation;System statistics is tested to dodge Deposit the program/erase operation cycle number of chip.
CN201710973383.4A 2017-10-18 2017-10-18 Flash memory chip life prediction method based on mathematical model Active CN107967928B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710973383.4A CN107967928B (en) 2017-10-18 2017-10-18 Flash memory chip life prediction method based on mathematical model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710973383.4A CN107967928B (en) 2017-10-18 2017-10-18 Flash memory chip life prediction method based on mathematical model

Publications (2)

Publication Number Publication Date
CN107967928A true CN107967928A (en) 2018-04-27
CN107967928B CN107967928B (en) 2020-06-26

Family

ID=61997655

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710973383.4A Active CN107967928B (en) 2017-10-18 2017-10-18 Flash memory chip life prediction method based on mathematical model

Country Status (1)

Country Link
CN (1) CN107967928B (en)

Cited By (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108682442A (en) * 2018-05-23 2018-10-19 武汉忆数存储技术有限公司 A kind of different encapsulation flash chip on-line testing and sorting technique and test system
CN108777157A (en) * 2018-05-08 2018-11-09 南京邮电大学 The adaptive approach of MLC flash voltage threshold is predicted based on deep neural network
CN108831517A (en) * 2018-05-23 2018-11-16 武汉忆数存储技术有限公司 A kind of method and test device judging flash chip reliability based on operating time or electric current
CN108847267A (en) * 2018-05-23 2018-11-20 武汉忆数存储技术有限公司 A kind of service life of flash memory test method based on error pattern
CN109215725A (en) * 2017-07-03 2019-01-15 无锡华润上华科技有限公司 Flush memory device method for testing reliability, storage medium and electronic equipment
CN109634527A (en) * 2018-12-12 2019-04-16 华中科技大学 A kind of interior service life of flash memory prediction technique realized of SSD
CN109637576A (en) * 2018-12-17 2019-04-16 华中科技大学 A kind of service life of flash memory prediction technique based on support vector regression
CN109815534A (en) * 2018-12-17 2019-05-28 武汉忆数存储技术有限公司 A flash memory life prediction method and device based on decision tree algorithm
CN109817267A (en) * 2018-12-17 2019-05-28 武汉忆数存储技术有限公司 A deep learning-based flash memory life prediction method, system and computer-readable access medium
CN109830254A (en) * 2018-12-17 2019-05-31 武汉忆数存储技术有限公司 A kind of service life of flash memory prediction technique, system, storage medium
CN109830255A (en) * 2018-12-17 2019-05-31 武汉忆数存储技术有限公司 A kind of service life of flash memory prediction technique, system and storage medium based on characteristic quantity
CN109857607A (en) * 2018-12-24 2019-06-07 北京大学 A kind of reliability checking method and device of NAND Flash solid state hard disk
CN110007857A (en) * 2019-03-08 2019-07-12 北京星网锐捷网络技术有限公司 A kind of life-span prediction method and device of flash chip
CN110147290A (en) * 2019-04-15 2019-08-20 深圳市纽创信安科技开发有限公司 Chip Age estimation method, apparatus, chip and terminal
CN110211626A (en) * 2019-05-13 2019-09-06 华中科技大学 A kind of measure and gauging system of flash memories health degree
CN110232948A (en) * 2019-05-28 2019-09-13 华中科技大学 A kind of UFS stores the measure and system of UFS chip health degree in equipment
CN110491437A (en) * 2018-05-14 2019-11-22 慧荣科技股份有限公司 The method and related storage device of storage access administration are carried out by machine learning
CN110851079A (en) * 2019-10-28 2020-02-28 华中科技大学 Adaptive storage device loss balancing method and system
CN111312326A (en) * 2020-03-09 2020-06-19 宁波三星医疗电气股份有限公司 Flash memory life testing method and device, power acquisition terminal and storage medium
CN112908399A (en) * 2021-02-05 2021-06-04 置富科技(深圳)股份有限公司 Flash memory abnormality detection method and device, computer equipment and storage medium
CN112908391A (en) * 2021-02-08 2021-06-04 置富科技(深圳)股份有限公司 Flash memory classification method and device based on mathematical model
CN113792878A (en) * 2021-08-18 2021-12-14 南华大学 An Automatic Recognition Method of Numerical Program Metamorphosis Relation
CN115295064A (en) * 2022-08-05 2022-11-04 安徽丰士通电子科技有限公司 Memory chip test system
CN116822383A (en) * 2023-08-31 2023-09-29 成都态坦测试科技有限公司 Equipment life prediction model construction method and device, readable storage medium and equipment
CN116880747A (en) * 2023-06-13 2023-10-13 珠海妙存科技有限公司 Flash memory wear degree judging method and system and electronic equipment
CN117130822A (en) * 2023-10-24 2023-11-28 杭州阿姆科技有限公司 Method and system for predicting NAND flash data errors
WO2024187572A1 (en) * 2023-03-16 2024-09-19 中国科学院微电子研究所 Service life prediction and repair method for resistive random access memory chip

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101159169A (en) * 2006-10-05 2008-04-09 国际商业机器公司 End of life prediction of flash memory
CN101266840A (en) * 2008-04-17 2008-09-17 北京航空航天大学 A life prediction method for flash memory electronic products
CN104376875A (en) * 2014-11-19 2015-02-25 华为数字技术(苏州)有限公司 Methods and devices for predicting and determining life of storage device
CN105159840A (en) * 2015-10-16 2015-12-16 华中科技大学 Method for extracting soft information of flash memory device
CN105679369A (en) * 2015-12-28 2016-06-15 上海华虹宏力半导体制造有限公司 Flash memory service predicting method and flash memory screening method
CN106504794A (en) * 2015-09-04 2017-03-15 Hgst荷兰公司 Operating Parameters for Flash Memory Devices
WO2017136220A1 (en) * 2016-02-01 2017-08-10 Qualcomm Incorporated Flash device lifetime monitor systems and methods
US20170228161A1 (en) * 2016-02-10 2017-08-10 Ricoh Company, Ltd. Lifetime management device and lifetime management method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101159169A (en) * 2006-10-05 2008-04-09 国际商业机器公司 End of life prediction of flash memory
CN101266840A (en) * 2008-04-17 2008-09-17 北京航空航天大学 A life prediction method for flash memory electronic products
CN104376875A (en) * 2014-11-19 2015-02-25 华为数字技术(苏州)有限公司 Methods and devices for predicting and determining life of storage device
CN106504794A (en) * 2015-09-04 2017-03-15 Hgst荷兰公司 Operating Parameters for Flash Memory Devices
CN105159840A (en) * 2015-10-16 2015-12-16 华中科技大学 Method for extracting soft information of flash memory device
CN105679369A (en) * 2015-12-28 2016-06-15 上海华虹宏力半导体制造有限公司 Flash memory service predicting method and flash memory screening method
WO2017136220A1 (en) * 2016-02-01 2017-08-10 Qualcomm Incorporated Flash device lifetime monitor systems and methods
US20170228161A1 (en) * 2016-02-10 2017-08-10 Ricoh Company, Ltd. Lifetime management device and lifetime management method

Cited By (39)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109215725A (en) * 2017-07-03 2019-01-15 无锡华润上华科技有限公司 Flush memory device method for testing reliability, storage medium and electronic equipment
CN108777157B (en) * 2018-05-08 2021-07-09 南京邮电大学 An Adaptive Method for Predicting Voltage Threshold of MLC Flash Memory Based on Deep Neural Network
CN108777157A (en) * 2018-05-08 2018-11-09 南京邮电大学 The adaptive approach of MLC flash voltage threshold is predicted based on deep neural network
CN110491437B (en) * 2018-05-14 2021-05-11 慧荣科技股份有限公司 Method and related storage device for memory access management through machine learning
CN110491437A (en) * 2018-05-14 2019-11-22 慧荣科技股份有限公司 The method and related storage device of storage access administration are carried out by machine learning
US11449806B2 (en) 2018-05-14 2022-09-20 Silicon Motion, Inc. Method for performing memory access management with aid of machine learning in memory device, associated memory device and controller thereof, and associated electronic device
CN108847267A (en) * 2018-05-23 2018-11-20 武汉忆数存储技术有限公司 A kind of service life of flash memory test method based on error pattern
CN108847267B (en) * 2018-05-23 2022-04-08 置富科技(深圳)股份有限公司 Flash memory life test method based on error mode
CN108682442B (en) * 2018-05-23 2022-04-05 置富科技(深圳)股份有限公司 Online testing and classifying method and testing system for different packaged flash memory chips
CN108831517A (en) * 2018-05-23 2018-11-16 武汉忆数存储技术有限公司 A kind of method and test device judging flash chip reliability based on operating time or electric current
CN108831517B (en) * 2018-05-23 2021-04-27 武汉忆数存储技术有限公司 Method and test device for judging reliability of flash memory chip based on operation time or current
CN108682442A (en) * 2018-05-23 2018-10-19 武汉忆数存储技术有限公司 A kind of different encapsulation flash chip on-line testing and sorting technique and test system
CN109634527A (en) * 2018-12-12 2019-04-16 华中科技大学 A kind of interior service life of flash memory prediction technique realized of SSD
CN109637576A (en) * 2018-12-17 2019-04-16 华中科技大学 A kind of service life of flash memory prediction technique based on support vector regression
CN109830254A (en) * 2018-12-17 2019-05-31 武汉忆数存储技术有限公司 A kind of service life of flash memory prediction technique, system, storage medium
CN109815534A (en) * 2018-12-17 2019-05-28 武汉忆数存储技术有限公司 A flash memory life prediction method and device based on decision tree algorithm
CN109817267A (en) * 2018-12-17 2019-05-28 武汉忆数存储技术有限公司 A deep learning-based flash memory life prediction method, system and computer-readable access medium
CN109830255A (en) * 2018-12-17 2019-05-31 武汉忆数存储技术有限公司 A kind of service life of flash memory prediction technique, system and storage medium based on characteristic quantity
CN109817267B (en) * 2018-12-17 2021-02-26 武汉忆数存储技术有限公司 A deep learning-based flash memory life prediction method, system and computer-readable access medium
CN109857607A (en) * 2018-12-24 2019-06-07 北京大学 A kind of reliability checking method and device of NAND Flash solid state hard disk
CN110007857A (en) * 2019-03-08 2019-07-12 北京星网锐捷网络技术有限公司 A kind of life-span prediction method and device of flash chip
CN110007857B (en) * 2019-03-08 2022-08-19 北京星网锐捷网络技术有限公司 Method and device for predicting service life of flash memory chip
CN110147290A (en) * 2019-04-15 2019-08-20 深圳市纽创信安科技开发有限公司 Chip Age estimation method, apparatus, chip and terminal
CN110211626B (en) * 2019-05-13 2020-11-17 华中科技大学 Method and system for measuring health degree of flash memory
CN110211626A (en) * 2019-05-13 2019-09-06 华中科技大学 A kind of measure and gauging system of flash memories health degree
CN110232948A (en) * 2019-05-28 2019-09-13 华中科技大学 A kind of UFS stores the measure and system of UFS chip health degree in equipment
CN110851079A (en) * 2019-10-28 2020-02-28 华中科技大学 Adaptive storage device loss balancing method and system
CN111312326A (en) * 2020-03-09 2020-06-19 宁波三星医疗电气股份有限公司 Flash memory life testing method and device, power acquisition terminal and storage medium
CN111312326B (en) * 2020-03-09 2021-11-12 宁波三星医疗电气股份有限公司 Flash memory life testing method and device, power acquisition terminal and storage medium
CN112908399A (en) * 2021-02-05 2021-06-04 置富科技(深圳)股份有限公司 Flash memory abnormality detection method and device, computer equipment and storage medium
CN112908391B (en) * 2021-02-08 2022-04-12 置富科技(深圳)股份有限公司 Flash memory classification method and device based on mathematical model
CN112908391A (en) * 2021-02-08 2021-06-04 置富科技(深圳)股份有限公司 Flash memory classification method and device based on mathematical model
CN113792878A (en) * 2021-08-18 2021-12-14 南华大学 An Automatic Recognition Method of Numerical Program Metamorphosis Relation
CN113792878B (en) * 2021-08-18 2024-03-15 南华大学 Automatic recognition method for numerical program metamorphic relation
CN115295064A (en) * 2022-08-05 2022-11-04 安徽丰士通电子科技有限公司 Memory chip test system
WO2024187572A1 (en) * 2023-03-16 2024-09-19 中国科学院微电子研究所 Service life prediction and repair method for resistive random access memory chip
CN116880747A (en) * 2023-06-13 2023-10-13 珠海妙存科技有限公司 Flash memory wear degree judging method and system and electronic equipment
CN116822383A (en) * 2023-08-31 2023-09-29 成都态坦测试科技有限公司 Equipment life prediction model construction method and device, readable storage medium and equipment
CN117130822A (en) * 2023-10-24 2023-11-28 杭州阿姆科技有限公司 Method and system for predicting NAND flash data errors

Also Published As

Publication number Publication date
CN107967928B (en) 2020-06-26

Similar Documents

Publication Publication Date Title
CN107967928A (en) A kind of flash chip life-span prediction method based on mathematical model
CN108766496A (en) A kind of method and device in online dynamic prediction flash chip service life
CN109817267B (en) A deep learning-based flash memory life prediction method, system and computer-readable access medium
CN113468803B (en) WOA-GRU flood flow prediction method and system based on improvement
CN109830254A (en) A kind of service life of flash memory prediction technique, system, storage medium
CN109637576A (en) A kind of service life of flash memory prediction technique based on support vector regression
US20180357535A1 (en) Identifying memory block write endurance using machine learning
CN104871250B (en) Apparatus and method for re-forming resistance memory cell
CN103105246A (en) Greenhouse environment forecasting feedback method of back propagation (BP) neural network based on improvement of genetic algorithm
CN109634527A (en) A kind of interior service life of flash memory prediction technique realized of SSD
US20220058488A1 (en) Partitionable Neural Network for Solid State Drives
CN108831517A (en) A kind of method and test device judging flash chip reliability based on operating time or electric current
CN109947652A (en) An Improved Ranking Learning Method for Software Defect Prediction
CN112817524A (en) Flash memory reliability grade online prediction method and device based on dynamic neural network
CN117976029A (en) A method for predicting the life of flash memory chips
CN109830255A (en) A kind of service life of flash memory prediction technique, system and storage medium based on characteristic quantity
CN112098833B (en) Relay service life prediction method, system, medium and equipment
CN109273039A (en) A kind of erasing verifying device and method of flash memories
CN111612648A (en) Training method and device of photovoltaic power generation prediction model and computer equipment
CN109815534A (en) A flash memory life prediction method and device based on decision tree algorithm
CN119939112A (en) A data insertion and extension method and system based on neural network
CN104067348B (en) Programming and erasing scheme for analog memory unit
CN117077546B (en) Power system load modeling method and system based on data driving
CN118151038A (en) A method, system, device and storage medium for predicting remaining life of lithium-ion battery
CN118093385A (en) Training of code quality evaluation model, and code quality evaluation method and device

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CP03 Change of name, title or address
CP03 Change of name, title or address

Address after: 430000 room 806-807, 8 / F, high tech building, 6-12 / F, scientific research building, No. 11, Jiayuan Road, Wuhan East Lake New Technology Development Zone, Wuhan, Hubei Province

Patentee after: Wuhan Zhifu Semiconductor Technology Co.,Ltd.

Address before: 430000 room 304-5, floor 3, building 2, Lanyu, Shuguang Software Park, central China, No. 1, Guanshan 1st Road, Donghu New Technology Development Zone, Wuhan, Hubei Province

Patentee before: WUHAN RECADATA STORAGE TECHNOLOGY CO.,LTD.