CN117472286A - Chip data storage system and method based on artificial intelligence - Google Patents
Chip data storage system and method based on artificial intelligence Download PDFInfo
- Publication number
- CN117472286A CN117472286A CN202311812765.0A CN202311812765A CN117472286A CN 117472286 A CN117472286 A CN 117472286A CN 202311812765 A CN202311812765 A CN 202311812765A CN 117472286 A CN117472286 A CN 117472286A
- Authority
- CN
- China
- Prior art keywords
- data information
- stored
- data
- storage
- 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
Links
- 238000000034 method Methods 0.000 title claims abstract description 59
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 24
- 238000013500 data storage Methods 0.000 title claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims abstract description 70
- 238000012544 monitoring process Methods 0.000 claims abstract description 27
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 claims abstract description 7
- 230000008859 change Effects 0.000 claims abstract description 5
- 238000007781 pre-processing Methods 0.000 claims description 15
- 238000004364 calculation method Methods 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 9
- 238000012545 processing Methods 0.000 claims description 7
- 230000006399 behavior Effects 0.000 claims description 4
- 230000001351 cycling effect Effects 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 2
- 238000002372 labelling Methods 0.000 claims 1
- 230000002159 abnormal effect Effects 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/0604—Improving or facilitating administration, e.g. storage management
- G06F3/0607—Improving or facilitating administration, e.g. storage management by facilitating the process of upgrading existing storage systems, e.g. for improving compatibility between host and storage device
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3037—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a memory, e.g. virtual memory, cache
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
- G06F11/3093—Configuration details thereof, e.g. installation, enabling, spatial arrangement of the probes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
- G06F3/0638—Organizing or formatting or addressing of data
- G06F3/0644—Management of space entities, e.g. partitions, extents, pools
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
- G06F3/0671—In-line storage system
- G06F3/0673—Single storage device
- G06F3/0679—Non-volatile semiconductor memory device, e.g. flash memory, one time programmable memory [OTP]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Computing Systems (AREA)
- Quality & Reliability (AREA)
- Mathematical Physics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention relates to the technical field of artificial intelligence, in particular to a chip data storage system and method based on artificial intelligence, wherein the system comprises a data information analysis module, a attribution area analysis module, an early warning signal generation module and a stored data change module, wherein the attribution area analysis module is used for monitoring data information to be stored in real time, analyzing the importance degree of the data information to be stored, and judging attribution areas of the data information to be stored by combining the area division result of a storage chip in a circuit board.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a chip data storage system and method based on artificial intelligence.
Background
As electronic products become more popular, there is an increasing need for intellectualization of electronic products. Correspondingly, the requirements on the chip performance and the stability of the chip stored data in the electronic product are also higher and higher, a memory bank is built in the existing chip, and programs and data required by the chip operation are stored in the memory bank.
In practical applications, factors such as bad operation of a user or electromagnetic interference in an environment are trigger time for causing abnormal variation of data in a memory bank, and due to abnormal capacity of the memory bank caused by bad operation of the user, chip operation performance is deteriorated, when abnormal variation of the data of the memory bank in the chip occurs, the content in the memory bank is restored by backup data or the rate of deterioration of the chip operation performance is reduced by de-duplication of the data in the memory bank, and the stable condition of the chip operation performance cannot be fundamentally solved, so that an artificial intelligence-based chip data storage system and method are needed.
Disclosure of Invention
The invention aims to provide a chip data storage system and method based on artificial intelligence, which are used for solving the problems in the background technology, and the invention provides the following technical scheme:
a chip data storage method based on artificial intelligence, the method comprising the steps of:
s1, acquiring hardware information of a circuit board to be monitored, reading data information in a flash memory chip in a corresponding circuit board, dividing storage areas by combining the read information, analyzing weight coefficients of corresponding data information in each area according to dividing results, and preprocessing the data information of each area by combining analysis results;
s3, executing corresponding storage operation based on the attribution region judgment result of the data information to be stored in the S2, updating the storage space in the flash memory, monitoring the storage space in the flash memory in real time, and generating an early warning signal by combining the monitoring result;
and S4, receiving early warning signals in real time according to the monitoring result, and adjusting data in the flash memory according to the received early warning signals.
Further, the method in S1 includes the following steps:
step 1001, obtaining data information in flash memory chips in corresponding circuit boards in the area to be monitored, dividing the storage area according to the type of the corresponding data information, and marking as a set A,
，
wherein the method comprises the steps ofA storage area corresponding to the data information of the nth type;
step 1002, based on the storage area division result in step 1001, marking the corresponding data information in each storage area in sequence, arbitrarily selecting the marking value of the same data information, marking as b, extracting the data information marked as b in the storage area corresponding to the nth type of data information, marking the weight coefficient of the data information marked as b in the storage area corresponding to the nth type of data information as b，
，
Wherein the method comprises the steps ofRepresenting a proportionality coefficient, which is a database preset value, < >>Indicating the number of data information b in the storage area corresponding to the nth type of data information, ++>Representing the total number of data information in the storage area corresponding to the nth type of data information;
step 1003, cycling step 1002 to obtain corresponding weight coefficients of different marked data information in the storage area corresponding to the nth type of data information, and generating a sequence B according to the order of the weight coefficients from big to small by combining the analysis result,
，
wherein the method comprises the steps ofThe weight coefficient of the data information denoted as m in the storage area corresponding to the nth type of data information is represented.
According to the method, the data information in the flash memory chips in the corresponding circuit boards in the area to be monitored is obtained, the storage area is divided according to the types of the corresponding data information, the corresponding weight coefficients of the data information with different labels in the corresponding storage area are calculated in combination with the storage area division result, the data information in the corresponding storage area is sequenced, and data reference is provided for the attribution area of the data to be stored in the subsequent judgment.
Further, the method in S2 includes the following steps:
step 2001, monitoring the data information to be stored in real time, dividing the data information to be stored according to types to generate a set C,
，
wherein the method comprises the steps ofRepresenting an i-th type of data information set to be stored, i representing the number of types of the data information set to be stored;
step 2002, sequentially analyzing the importance degree of the elements in the data information sets to be stored of different types, obtaining the elements in the data information sets to be stored of the ith type, sequentially analyzing the importance degree of the elements in the data information sets to be stored of the ith type, and recording the importance degree of the c element in the data information sets to be stored of the ith type as，
，
Wherein the method comprises the steps ofRepresenting a scaling factor, which is a database preset value, H () representing a judgment function,/-, for a judgment function>Property attributes representing the c-th element, said property attributes including temporary files and system files, when +.>If the judgment result is the temporary file, then +.>Representing that the c-th element is stored in the RAM, performing importance level analysis of the next element when +.>If the judgment result is the system file, then +.>Indicating that the c-th element is stored in the flash memory, continuing to judge the attribution area of the data to be stored,/-for the data to be stored>Represents the same element number, +_f, in set A as the c-th element in the i-th type of data information set to be stored>Representing the sum +.>Total number of elements;
step 2003, mapping the storage areas corresponding to the different kinds of data information in the flash memory into a first plane rectangular coordinate system based on the analysis results in the steps 1001-1003,
a point o is taken as an origin, the type of data information is taken as an x axis, the maximum weight coefficient of the same type of data information is taken as a y axis, a first plane rectangular coordinate system is constructed,
in the first plane rectangular coordinate system, the attribution areas of the data information corresponding to different data information types are marked in turn,
marking coordinate points corresponding to the nth type of data information in a first plane rectangular coordinate system, sequentially constructing circles by taking the marked coordinate points as dots and taking elements in the sequence B as radiuses, and generating corresponding storage areas corresponding to the marked data information;
step 2004, looping step 2003 to obtain storage areas corresponding to different types of data information, and memorizing the storage areas as a set，
，
Wherein the method comprises the steps ofRepresenting a set of storage areas of the nth type of data information in a first planar rectangular coordinate system,
，
wherein the method comprises the steps ofRepresenting a storage area of corresponding data marked as m in the n-th type of data information in a first plane rectangular coordinate system;
step 2005, extraction step 2002Combining the calculation result to obtain the data information of the c element in the ith type of data information set to be stored, which is the same as the data information in the flash memory chip, wherein the data information is in the set +.>Extracting the storage area corresponding to the same data information and marking the storage area as a set F, wherein the set FComprising g storage areas of the memory card,
determining the attribution area of the c-th element in the i-th type of data information set to be stored,
matching dot coordinates corresponding to the same data information in a first plane rectangular coordinate system, and taking the origin coordinates as reference points to obtainA circle is built for the radius, denoted as circle T,
wherein the method comprises the steps of，/>Representing a proportionality coefficient, which is a database preset value, < >>Representing the value of the occupied space of the c-th element, < >>The occupancy space value is a database preset value, < + >>Indicating the same number of data information as the element c in the storage area corresponding to the n-th type of data information,
comparing the circle T with any element in the set F in turn, and marking the attribution area of the c element in the i type data information set to be stored as，
，
Wherein the method comprises the steps ofRepresenting the area of circle T>Representing the area of a circle formed by the V-th storage area in set F, whenWhen (I)>On the contrary->，/>Represents the radius of circle T +.>Representing the radius of the circle formed by the V-th storage area in set F, +.>To select the function whenWhen the data information set is stored, a storage area where the circle V is located is selected as a home area of a c element in the i type data information set to be stored;
step 2006, looping step 2005 to obtain a matching result of the attribution region of each element in each type of data information set in the set C.
The method and the device monitor the data information to be stored in real time, divide the data information to be stored according to types, randomly extract one type of data information to be stored, judge the storage position of the data information to be stored by analyzing the importance degree of the corresponding data information in the corresponding data information to be stored, matching the relationship between the data information to be stored and the storage area through the identical degree, analyze the attribution area of the data information to be stored in the plane rectangular coordinate system by constructing the plane rectangular coordinate system, provide data reference for the follow-up real-time monitoring of the storage space change condition of the flash memory storage area and generating an early warning signal by combining the change condition.
Further, the method in S3 includes the following steps:
step (a)3001. Constructing a second plane rectangular coordinate system by taking o1 as an origin, taking time as an x1 axis and taking storage capacity as a y1 axis, marking coordinate points corresponding to the storage capacity in a flash memory in the second plane rectangular coordinate system, sequentially connecting two adjacent coordinate points, generating a fitting curve, and marking the curve as a curve；
Step 3002, obtaining the capacity limit value of the flash memory through the history data, and marking the straight line of the capacity limit value in a second plane rectangular coordinate system as a curve；
Step 3003, based on the analysis results of step 3001 and step 3002, determining the minimum distance value between the two curves, and recording as，
If it isWithin the preset interval, no warning signal is sent out if +.>If the signal is not in the preset interval, an early warning signal is sent out.
According to the invention, whether the storage capacity of the flash memory exceeds the limit value is judged, and then an early warning signal is generated according to the judgment result, so that data reference is provided for the subsequent adjustment of the data information in the flash memory.
Further, in the step S4, based on the analysis result in the step S3, the early warning signal is received in real time, the data in the flash memory is adjusted according to the received early warning signal, the data with the same data information is obtained in the flash memory, a group of the same data information is arbitrarily extracted, the data information with the highest calling frequency is reserved, and the rejection calling period based on the updated data information in the flash memory exceeds the calling periodAnd (3) finishing the storage capacity calibration operation of the flash memory according to the data information of the time period, repeating the steps 3001-3003, if the early warning signal is in the early warning state, sending a manual request for processing the data information in the flash memory, and if the early warning signal is in the failure state, continuing to monitor the storage capacity condition in the flash memory.
An artificial intelligence based chip data storage system, the system comprising the steps of:
and the data information analysis module is used for: the data information analysis module is used for acquiring hardware information of the circuit board to be monitored, reading data information in a flash memory chip in the corresponding circuit board, dividing storage areas by combining the read information, analyzing corresponding data information weight coefficients in each area according to the dividing result, and preprocessing the data information of each area by combining the analysis result;
home zone analysis module: the attribution area analysis module is used for monitoring the data information to be stored in real time, analyzing the importance degree of the data information to be stored, and judging the attribution area of the data information to be stored by combining the area division result of the memory chip in the circuit board;
the early warning signal generation module: the early warning signal generation module is used for generating an early warning signal based on the analysis results of the data information analysis module and the attribution area analysis module;
a stored data changing module: the storage data changing module is used for receiving the analysis result of the early warning signal generating module and adjusting the data in the flash memory according to the received early warning signal.
Further, the data information analysis module comprises a region dividing unit, a weight coefficient calculating unit and a data preprocessing unit:
the region dividing unit is used for acquiring data information in the flash memory chips in the corresponding circuit boards in the region to be monitored and dividing the storage region according to the type of the corresponding data information;
the weight coefficient calculation unit is used for calculating the weight coefficient of the same data information relative to the corresponding storage area based on the analysis result of the area division unit;
the data preprocessing unit is used for generating a sequence for the data information in the corresponding storage area by taking the analysis result of the weight coefficient calculation unit as a reference.
Further, the home area analysis module comprises a data preprocessing unit to be stored, an importance degree analysis unit and a home area analysis unit:
the data preprocessing unit is used for monitoring the data information to be stored in real time and dividing the data information to be stored according to types;
the importance degree analysis unit is used for sequentially calculating importance degree values of different types of data information to be stored based on the analysis result of the data preprocessing unit to be stored;
the attribution area analysis unit is used for judging the relation between the corresponding data information to be stored and the data information analysis module according to the analysis result of the importance degree analysis unit, and screening the attribution area which accords with the corresponding data information to be stored according to the judgment result.
Further, the early warning signal generating module comprises a storage space monitoring unit and an early warning signal generating unit:
the storage space monitoring unit is used for monitoring the change condition of the storage capacity in the flash memory in real time;
the early warning signal generation unit is used for generating an early warning signal by combining the analysis result of the storage space monitoring unit.
Further, the stored data changing module includes an early warning signal receiving unit and a stored data processing unit:
the early warning signal receiving unit is used for receiving the analysis result of the early warning signal generating unit in real time;
the storage data processing unit is used for adjusting the data in the flash memory based on the analysis result of the early warning signal receiving unit, eliminating the data information with calling time exceeding the preset time and changing the same data in the flash memory.
According to the invention, the data stored in the chip is divided into the areas, the attribution area of the data information to be stored is judged, and the storage space in the chip is monitored in real time, so that the data in the storage space is adjusted in real time, the running performance of the chip is ensured, and the chip is prevented from being abnormal due to overlarge occupation of the data information.
Drawings
FIG. 1 is a flow chart of an artificial intelligence based chip data storage method of the present invention;
FIG. 2 is a schematic block diagram of an artificial intelligence based chip data storage system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: referring to fig. 1, in this embodiment:
a chip data storage method based on artificial intelligence, the method comprising the steps of:
s1, acquiring hardware information of a circuit board to be monitored, reading data information in a flash memory chip in a corresponding circuit board, dividing storage areas by combining the read information, analyzing weight coefficients of corresponding data information in each area according to dividing results, and preprocessing the data information of each area by combining analysis results;
the method in S1 comprises the following steps:
step 1001, obtaining data information in flash memory chips in corresponding circuit boards in the area to be monitored, dividing the storage area according to the type of the corresponding data information, and marking as a set A,
，
wherein the method comprises the steps ofA storage area corresponding to the data information of the nth type;
step 1002, based on the storage area division result in step 1001, marking the corresponding data information in each storage area in sequence, arbitrarily selecting the marking value of the same data information, marking as b, extracting the data information marked as b in the storage area corresponding to the nth type of data information, marking the weight coefficient of the data information marked as b in the storage area corresponding to the nth type of data information as b，
，
Wherein the method comprises the steps ofRepresenting a proportionality coefficient, which is a database preset value, < >>Indicating the number of data information b in the storage area corresponding to the nth type of data information, ++>Representing the total number of data information in the storage area corresponding to the nth type of data information;
step 1003, cycling step 1002 to obtain corresponding weight coefficients of different marked data information in the storage area corresponding to the nth type of data information, and generating a sequence B according to the order of the weight coefficients from big to small by combining the analysis result,
，
wherein the method comprises the steps ofThe weight coefficient of the data information denoted as m in the storage area corresponding to the nth type of data information is represented.
S2, extracting data information to be stored in user operation behaviors in real time, analyzing importance degree of the data information to be stored, and judging attribution areas of the data information to be stored by combining area division results of memory chips in a circuit board;
the method in S2 comprises the steps of:
step 2001, monitoring the data information to be stored in real time, dividing the data information to be stored according to types to generate a set C,
，
wherein the method comprises the steps ofRepresenting an i-th type of data information set to be stored, i representing the number of types of the data information set to be stored;
step 2002, sequentially analyzing the importance degree of the elements in the data information sets to be stored of different types, obtaining the elements in the data information sets to be stored of the ith type, sequentially analyzing the importance degree of the elements in the data information sets to be stored of the ith type, and recording the importance degree of the c element in the data information sets to be stored of the ith type as，
，
Wherein the method comprises the steps ofRepresenting a scaling factor, which is a database preset value, H () representing a judgment function,/-, for a judgment function>Property attributes representing the c-th element, said property attributes including temporary files and system files, when +.>If the judgment result is the temporary file, then +.>Representing that the c-th element is stored in the RAM, performing importance level analysis of the next element when +.>If the judgment result is the system file, then +.>Indicating that the c-th element is stored in the flash memory, continuing to judge the attribution area of the data to be stored,/-for the data to be stored>Represents the same element number, +_f, in set A as the c-th element in the i-th type of data information set to be stored>Representing the sum +.>Total number of elements;
step 2003, mapping the storage areas corresponding to the different kinds of data information in the flash memory into a first plane rectangular coordinate system based on the analysis results in the steps 1001-1003,
a point o is taken as an origin, the type of data information is taken as an x axis, the maximum weight coefficient of the same type of data information is taken as a y axis, a first plane rectangular coordinate system is constructed,
in the first plane rectangular coordinate system, the attribution areas of the data information corresponding to different data information types are marked in turn,
marking coordinate points corresponding to the nth type of data information in a first plane rectangular coordinate system, sequentially constructing circles by taking the marked coordinate points as dots and taking elements in the sequence B as radiuses, and generating corresponding storage areas corresponding to the marked data information;
step 2004, looping step 2003 to obtain storage areas corresponding to different types of data information,remembering as a collection，
，
Wherein the method comprises the steps ofRepresenting a set of storage areas of the nth type of data information in a first planar rectangular coordinate system,
，
wherein the method comprises the steps ofRepresenting a storage area of corresponding data marked as m in the n-th type of data information in a first plane rectangular coordinate system;
step 2005, extraction step 2002Combining the calculation result to obtain the data information of the c element in the ith type of data information set to be stored, which is the same as the data information in the flash memory chip, wherein the data information is in the set +.>Extracting storage areas corresponding to the same data information, marking the storage areas as a set F, wherein the set F comprises g storage areas,
determining the attribution area of the c-th element in the i-th type of data information set to be stored,
matching dot coordinates corresponding to the same data information in a first plane rectangular coordinate system, and taking the origin coordinates as reference points to obtainA circle is built for the radius, denoted as circle T,
wherein the method comprises the steps of，/>Representing a proportionality coefficient, which is a database preset value, < >>Representing the value of the occupied space of the c-th element, < >>The occupancy space value is a database preset value, < + >>Indicating the same number of data information as the element c in the storage area corresponding to the n-th type of data information,
comparing the circle T with any element in the set F in turn, and marking the attribution area of the c element in the i type data information set to be stored as，
，
Wherein the method comprises the steps ofRepresenting the area of circle T>Representing the area of a circle formed by the V-th storage area in set F, whenWhen (I)>On the contrary->，/>Represents the radius of circle T +.>Representing the radius of the circle formed by the V-th storage area in set F, +.>To select the function whenWhen the data information set is stored, a storage area where the circle V is located is selected as a home area of a c element in the i type data information set to be stored;
step 2006, looping step 2005 to obtain a matching result of the attribution region of each element in each type of data information set in the set C.
S3, executing corresponding storage operation based on the attribution region judgment result of the data information to be stored in the S2, updating the storage space in the flash memory, monitoring the storage space in the flash memory in real time, and generating an early warning signal by combining the monitoring result;
the analysis method in S3 comprises the following steps:
3001, using o1 as origin, time as x1 axis, and storage capacity as y1 axis to construct a second plane rectangular coordinate system, marking coordinate points corresponding to storage capacity in flash memory in the second plane rectangular coordinate system, sequentially connecting two adjacent coordinate points, generating a fitting curve, and marking as curve；
Step 3002, obtaining the capacity limit value of the flash memory through the history data, and marking the straight line of the capacity limit value in a second plane rectangular coordinate system as a curve；
Step 3003, based on the analysis results of step 3001 and step 3002, determining the minimum distance value between the two curves, and recording as，
If it isWithin the preset interval, no warning signal is sent out if +.>If the signal is not in the preset interval, an early warning signal is sent out.
S4, receiving early warning signals in real time according to monitoring results, adjusting data in the flash memory according to the received early warning signals, acquiring data with the same data information in the flash memory, randomly extracting a group of the same data information, retaining the data information with the highest calling frequency, and eliminating and calling the data information in the flash memory based on updated data information to exceed the calling periodAnd (3) finishing the storage capacity calibration operation of the flash memory according to the data information of the time period, repeating the steps 3001-3003, if the early warning signal is in the early warning state, sending a manual request for processing the data information in the flash memory, and if the early warning signal is in the failure state, continuing to monitor the storage capacity condition in the flash memory.
In this embodiment: an artificial intelligence based chip data storage system (as shown in fig. 2) for implementing the details of a method is disclosed.
Example 2: the data information in the flash memory chip in the corresponding circuit board in the area to be monitored is set to be divided into 3 areas, namely a storage area 1, a storage area 2 and a storage area 3,
acquiring user operation behaviors, extracting data information to be stored in the user operation behaviors, dividing the data information to be stored according to types, recording as a set C,
，
sequentially analyzing all types of data information sets to be stored in set CThe degree of importance of the elements willThe importance of the c-th element in (a) is recorded as +.>，
Obtained by calculationThe determination result of the c-th element in the operation formula is a system file, so that the c-th element needs to be stored in the flash memory, and the same calculation and analysis are combined to obtain that the c-th element should be stored in the storage area 3,
a point o is taken as an origin, the type of data information is taken as an x axis, the maximum weight coefficient of the same type of data information is taken as a y axis, a first plane rectangular coordinate system is constructed,
the attribution areas of the data information corresponding to the 3 different data information types of the storage area are marked in the first plane rectangular coordinate system, the storage area 3 is taken as a reference point, the weight value corresponding to each element is taken as a radius, the corresponding storage area is generated and marked as a set F,
in the first plane rectangular coordinate system, the storage area 3 is taken as a reference point, andthe circle is constructed for radius and marked as circle T, and the attribution area of the c element is marked as +.>And stores the c-th element to the corresponding area,
monitoring the storage space in the flash memory in real time, sending out an early warning signal when the storage space in the flash memory is not in a preset interval, acquiring the data with the same data information in the flash memory, randomly extracting a group of the same data information, reserving the data information with the highest calling frequency, and eliminating and calling the data information based on the updated data information in the flash memory to exceed the calling periodAnd (5) data information of the time period, and finishing the storage capacity calibration operation of the flash memory.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An artificial intelligence based chip data storage method, characterized in that the method comprises the following steps:
s1, acquiring hardware information of a circuit board to be monitored, reading data information in a flash memory chip in a corresponding circuit board, dividing storage areas by combining the read information, analyzing weight coefficients of corresponding data information in each area according to dividing results, and preprocessing the data information of each area by combining analysis results;
s2, extracting data information to be stored in user operation behaviors in real time, analyzing importance degree of the data information to be stored, and judging attribution areas of the data information to be stored by combining area division results of memory chips in a circuit board;
s3, executing corresponding storage operation based on the attribution region judgment result of the data information to be stored in the S2, updating the storage space in the flash memory, monitoring the storage space in the flash memory in real time, and generating an early warning signal by combining the monitoring result;
and S4, receiving early warning signals in real time according to the monitoring result, and adjusting data in the flash memory according to the received early warning signals.
2. The method for storing chip data based on artificial intelligence according to claim 1, wherein the method in S1 comprises the steps of:
step 1001, obtaining data information in flash memory chips in corresponding circuit boards in the area to be monitored, dividing the storage area according to the type of the corresponding data information, and marking as a set A,
，
wherein the method comprises the steps ofA storage area corresponding to the data information of the nth type;
step 1002, marking corresponding data information in each storage area in sequence based on the storage area division result in step 1001, and arbitrarily selecting the same typeThe labeling value of the data information is denoted as b, the data information labeled as b in the storage area corresponding to the nth type of data information is extracted, and the weight coefficient of the data information labeled as b in the storage area corresponding to the nth type of data information is denoted as，
，
Wherein the method comprises the steps ofRepresenting a proportionality coefficient, which is a database preset value, < >>Indicating the number of data information b in the storage area corresponding to the nth type of data information, ++>Representing the total number of data information in the storage area corresponding to the nth type of data information;
step 1003, cycling step 1002 to obtain corresponding weight coefficients of different marked data information in the storage area corresponding to the nth type of data information, and generating a sequence B according to the order of the weight coefficients from big to small by combining the analysis result,
，
wherein the method comprises the steps ofThe weight coefficient of the data information denoted as m in the storage area corresponding to the nth type of data information is represented.
3. The method for storing chip data based on artificial intelligence according to claim 2, wherein the method in S2 comprises the steps of:
step 2001, monitoring the data information to be stored in real time, dividing the data information to be stored according to types to generate a set C,
，
wherein the method comprises the steps ofRepresenting an i-th type of data information set to be stored, i representing the number of types of the data information set to be stored;
step 2002, sequentially analyzing the importance degree of the elements in the data information sets to be stored of different types, obtaining the elements in the data information sets to be stored of the ith type, sequentially analyzing the importance degree of the elements in the data information sets to be stored of the ith type, and recording the importance degree of the c element in the data information sets to be stored of the ith type as，
，
Wherein the method comprises the steps ofRepresenting a scaling factor, which is a database preset value, H () representing a judgment function,/-, for a judgment function>Property attributes representing the c-th element, said property attributes including temporary files and system files, when +.>If the judgment result is the temporary file, then +.>Representing that the c-th element is stored in the RAM, performing importance level analysis of the next element when +.>If the judgment result is the system file, then +.>Indicating that the c-th element is stored in the flash memory, continuing to judge the attribution area of the data to be stored,/-for the data to be stored>Represents the same element number, +_f, in set A as the c-th element in the i-th type of data information set to be stored>Representing the sum +.>Total number of elements;
step 2003, mapping the storage areas corresponding to the different kinds of data information in the flash memory into a first plane rectangular coordinate system based on the analysis results in the steps 1001-1003,
a point o is taken as an origin, the type of data information is taken as an x axis, the maximum weight coefficient of the same type of data information is taken as a y axis, a first plane rectangular coordinate system is constructed,
in the first plane rectangular coordinate system, the attribution areas of the data information corresponding to different data information types are marked in turn,
marking coordinate points corresponding to the nth type of data information in a first plane rectangular coordinate system, sequentially constructing circles by taking the marked coordinate points as dots and taking elements in the sequence B as radiuses, and generating corresponding storage areas corresponding to the marked data information;
step 2004, looping step 2003 to obtain storage areas corresponding to different types of data information, remembering asAggregation，
，
Wherein the method comprises the steps ofRepresenting a set of storage areas of the nth type of data information in a first planar rectangular coordinate system,
，
wherein the method comprises the steps ofRepresenting a storage area of corresponding data marked as m in the n-th type of data information in a first plane rectangular coordinate system;
step 2005, extraction step 2002Combining the calculation result to obtain the data information of the c element in the ith type of data information set to be stored, which is the same as the data information in the flash memory chip, wherein the data information is in the set +.>Extracting storage areas corresponding to the same data information, marking the storage areas as a set F, wherein the set F comprises g storage areas,
determining the attribution area of the c-th element in the i-th type of data information set to be stored,
matching dot coordinates corresponding to the same data information in a first plane rectangular coordinate system, and taking the origin coordinates as reference points to obtainA circle is built for the radius, denoted as circle T,
wherein the method comprises the steps of，/>Representing a proportionality coefficient, wherein the proportionality coefficient is a database preset value,representing the value of the occupied space of the c-th element, < >>The occupancy space value is a database preset value, < + >>Indicating the same number of data information as the element c in the storage area corresponding to the n-th type of data information,
comparing the circle T with any element in the set F in turn, and marking the attribution area of the c element in the i type data information set to be stored as，
，
Wherein the method comprises the steps ofRepresenting the area of circle T>Representing the area of a circle formed by the V-th storage area in set F, whenWhen (I)>On the contrary->，/>Represents the radius of circle T +.>Representing the radius of the circle formed by the V-th storage area in set F, +.>To select the function whenWhen the data information set is stored, a storage area where the circle V is located is selected as a home area of a c element in the i type data information set to be stored;
step 2006, looping step 2005 to obtain a matching result of the attribution region of each element in each type of data information set in the set C.
4. A method for storing chip data based on artificial intelligence according to claim 3, wherein the method in S3 comprises the steps of:
3001, using o1 as origin, time as x1 axis, and storage capacity as y1 axis to construct a second plane rectangular coordinate system, marking coordinate points corresponding to storage capacity in flash memory in the second plane rectangular coordinate system, sequentially connecting two adjacent coordinate points, generating a fitting curve, and marking as curve；
Step 3002, obtaining the capacity limit value of the flash memory through the history data, and marking the straight line of the capacity limit value in a second plane rectangular coordinate system as a curve；
Step 3003, based on the analysis results of step 3001 and step 3002, determining the minimum distance value between the two curves, and recording as，
If it isWithin the preset interval, no warning signal is sent out if +.>If the signal is not in the preset interval, an early warning signal is sent out.
5. The method for storing chip data based on artificial intelligence according to claim 4, wherein in S4, based on the analysis result in S3, the early warning signal is received in real time, the data in the flash memory is adjusted according to the received early warning signal, the data with the same data information is obtained in the flash memory, a group of the same data information is arbitrarily extracted, the data information with the highest calling frequency is reserved, and the rejection and calling period is exceeded based on the updated data information in the flash memoryAnd (3) finishing the storage capacity calibration operation of the flash memory according to the data information of the time period, repeating the steps 3001-3003, if the early warning signal is in the early warning state, sending a manual request for processing the data information in the flash memory, and if the early warning signal is in the failure state, continuing to monitor the storage capacity condition in the flash memory.
6. An artificial intelligence based chip data storage system, the system comprising the steps of:
and the data information analysis module is used for: the data information analysis module is used for acquiring hardware information of the circuit board to be monitored, reading data information in a flash memory chip in the corresponding circuit board, dividing storage areas by combining the read information, analyzing corresponding data information weight coefficients in each area according to the dividing result, and preprocessing the data information of each area by combining the analysis result;
home zone analysis module: the attribution area analysis module is used for monitoring the data information to be stored in real time, analyzing the importance degree of the data information to be stored, and judging the attribution area of the data information to be stored by combining the area division result of the memory chip in the circuit board;
the early warning signal generation module: the early warning signal generation module is used for generating an early warning signal based on the analysis results of the data information analysis module and the attribution area analysis module;
a stored data changing module: the storage data changing module is used for receiving the analysis result of the early warning signal generating module and adjusting the data in the flash memory according to the received early warning signal.
7. The chip data storage system based on artificial intelligence according to claim 6, wherein the data information analysis module comprises a region dividing unit, a weight coefficient calculating unit and a data preprocessing unit:
the region dividing unit is used for acquiring data information in the flash memory chips in the corresponding circuit boards in the region to be monitored and dividing the storage region according to the type of the corresponding data information;
the weight coefficient calculation unit is used for calculating the weight coefficient of the same data information relative to the corresponding storage area based on the analysis result of the area division unit;
the data preprocessing unit is used for generating a sequence for the data information in the corresponding storage area by taking the analysis result of the weight coefficient calculation unit as a reference.
8. The chip data storage system based on artificial intelligence according to claim 7, wherein the home area analysis module comprises a data preprocessing unit to be stored, an importance degree analysis unit and a home area analysis unit:
the data preprocessing unit is used for monitoring the data information to be stored in real time and dividing the data information to be stored according to types;
the importance degree analysis unit is used for sequentially calculating importance degree values of different types of data information to be stored based on the analysis result of the data preprocessing unit to be stored;
the attribution area analysis unit is used for judging the relation between the corresponding data information to be stored and the data information analysis module according to the analysis result of the importance degree analysis unit, and screening the attribution area which accords with the corresponding data information to be stored according to the judgment result.
9. The chip data storage system based on artificial intelligence according to claim 8, wherein the early warning signal generating module comprises a storage space monitoring unit and an early warning signal generating unit:
the storage space monitoring unit is used for monitoring the change condition of the storage capacity in the flash memory in real time;
the early warning signal generation unit is used for generating an early warning signal by combining the analysis result of the storage space monitoring unit.
10. The chip data storage system based on artificial intelligence according to claim 9, wherein the stored data changing module comprises an early warning signal receiving unit and a stored data processing unit:
the early warning signal receiving unit is used for receiving the analysis result of the early warning signal generating unit in real time;
the storage data processing unit is used for adjusting the data in the flash memory based on the analysis result of the early warning signal receiving unit, eliminating the data information with calling time exceeding the preset time and changing the same data in the flash memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311812765.0A CN117472286B (en) | 2023-12-27 | 2023-12-27 | Chip data storage system and method based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311812765.0A CN117472286B (en) | 2023-12-27 | 2023-12-27 | Chip data storage system and method based on artificial intelligence |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117472286A true CN117472286A (en) | 2024-01-30 |
| CN117472286B CN117472286B (en) | 2024-04-09 |
Family
ID=89639974
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311812765.0A Active CN117472286B (en) | 2023-12-27 | 2023-12-27 | Chip data storage system and method based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117472286B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109634515A (en) * | 2017-10-09 | 2019-04-16 | 北京握奇智能科技有限公司 | A kind of the reading and writing data method and system of chip memory |
| CN112732172A (en) * | 2019-10-28 | 2021-04-30 | 三星电子株式会社 | Memory device and computer system |
-
2023
- 2023-12-27 CN CN202311812765.0A patent/CN117472286B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109634515A (en) * | 2017-10-09 | 2019-04-16 | 北京握奇智能科技有限公司 | A kind of the reading and writing data method and system of chip memory |
| CN112732172A (en) * | 2019-10-28 | 2021-04-30 | 三星电子株式会社 | Memory device and computer system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117472286B (en) | 2024-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111401609B (en) | Prediction method and prediction device for traffic flow time series | |
| CN112329847A (en) | Abnormity detection method and device, electronic equipment and storage medium | |
| CN111353549B (en) | Image label verification method and device, electronic equipment and storage medium | |
| CN115936262B (en) | Yield prediction method, system and medium based on big data environment interference | |
| CN115660262B (en) | Engineering intelligent quality inspection method, system and medium based on database application | |
| CN112632609A (en) | Abnormality detection method, abnormality detection device, electronic apparatus, and storage medium | |
| CN112990386A (en) | User value clustering method and device, computer equipment and storage medium | |
| CN113569965A (en) | User behavior analysis method and system based on Internet of things | |
| CN114187036A (en) | Internet advertisement intelligent recommendation management system based on behavior characteristic recognition | |
| CN116610821B (en) | Knowledge graph-based enterprise risk analysis method, system and storage medium | |
| CN117472286B (en) | Chip data storage system and method based on artificial intelligence | |
| CN115941807A (en) | Efficient data compression method for park security system | |
| CN115494431A (en) | Transformer fault warning method, terminal equipment and computer readable storage medium | |
| CN113239031A (en) | Big data denoising processing method | |
| CN113328988A (en) | Network security verification method and system based on big data and cloud computing | |
| CN110570025A (en) | prediction method, device and equipment for real reading rate of WeChat seal | |
| CN118378193B (en) | Intelligent community data analysis method and system based on big data | |
| CN111258788A (en) | Disk failure prediction method, device and computer readable storage medium | |
| CN114625786B (en) | Dynamic data mining method and system based on wind control technology | |
| CN118519820B (en) | Cloud platform-based data storage abnormality detection method and equipment | |
| CN118013248B (en) | Working condition identification method, device, equipment and medium based on semi-mechanism model screening | |
| CN118337525B (en) | Cloud asset security management system based on big data | |
| CN107508789B (en) | Abnormal data identification method and device | |
| CN111552790B (en) | Method and device for identifying article form | |
| CN114867046B (en) | Wireless network equipment firmware updating method and wireless network equipment |
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: Building 63, Jinghui Science and Technology Innovation Park, 123 Jinghui West Road, Xinwu District, Wuxi City, Jiangsu Province, 214000 Patentee after: Jiangsu Yangheyang Microelectronics Technology Co.,Ltd. Country or region after: China Address before: 210000 building 12-80, 29 buyue Road, Qiaolin street, Pukou District, Nanjing City, Jiangsu Province Patentee before: NANJING HEYANGTEK Co.,Ltd. Country or region before: China |