CN109710499B - Computer equipment performance identification method and device - Google Patents
Computer equipment performance identification method and device Download PDFInfo
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Abstract
The invention provides a computer equipment performance identification method, which comprises the following steps: reading hardware parameters corresponding to each hardware of the computer equipment; acquiring use parameters of computer equipment; and inputting the hardware parameters and the use parameters into a performance recognition model to obtain the current available performance parameter value of the computer equipment. The invention can obtain the current available performance parameter value of the computer equipment by obtaining the hardware parameter and the use parameter and combining the performance identification model, and can accurately and efficiently identify the performance of the computer equipment. According to the available performance parameter values and the correspondingly obtained judgment threshold values, whether the corresponding computer equipment is in the state to be optimized or not can be judged, and the judgment efficiency and the judgment accuracy are improved. The performance state of the computer equipment can be determined in batch and real time by applying the method. The method of the invention can be applied to hardware management in computer room management, and is particularly convenient for realizing the management of the host equipment.
Description
Technical Field
The invention relates to the field of hardware management, in particular to a method and a device for identifying performance of computer equipment.
Background
In current daily application and office, users put higher requirements on hardware performance of computers due to the use of various professional software and the factors of multi-thread processing tasks. In this case, the corresponding hardware is often required to be updated in time to meet the performance requirements of the user.
In the existing hardware optimization process, whether the corresponding computer hardware meets the requirement of optimization is usually determined by judging whether the computer is stuck or not. In the process of judging whether the hardware reaches the state needing to be optimized, a large judgment error exists, the efficiency is not high, and whether the specific hardware reaches the standard to be optimized or not is difficult to judge quickly.
Disclosure of Invention
The invention aims to solve at least one of the technical defects, in particular to the technical defects of low judgment efficiency and low accuracy of hardware to be optimized. The method has the problems of large judgment error and low efficiency.
The invention provides a computer equipment performance identification method, which comprises the following steps:
reading sub-hardware parameters corresponding to each hardware of the computer equipment, and calculating the hardware parameters;
acquiring use parameters of computer equipment;
and inputting the hardware parameters and the use parameters into a performance recognition model to obtain the current available performance parameter value of the computer equipment.
In one embodiment, the hardware parameters comprise at least one hardware parameter of functional parameters, depreciation time, purchase date, failure frequency, identification codes, maintenance cost and residual life; and/or the use parameters comprise at least one of position information, position information and service information.
In one embodiment, the computer device performance identification method further includes: and if the current available performance parameter value is smaller than a judgment threshold value, judging that the computer equipment belongs to the equipment to be optimized.
In one embodiment, the method further comprises the following steps:
acquiring use parameters of a user;
acquiring a judgment parameter and a corresponding judgment weight according to a use parameter of a user;
and calculating a judgment threshold corresponding to the user according to the judgment parameters and the judgment weight.
In one embodiment, the computer device performance identification method further comprises:
starting a hardware detection module to detect each hardware performance parameter of the computer equipment to be optimized;
determining hardware components needing to be replaced according to the performance parameters of each hardware and the use parameters of a user;
prompting to update the hardware component.
In one embodiment, after the step of prompting to update the corresponding hardware component, the computer device performance identification method further includes:
and acquiring the hardware information of the hardware component for prompting updating, and correspondingly generating purchasing information.
Acquiring budget information, and judging whether the purchasing information conforms to budget or not according to the budget information;
and generating a purchase order according to the purchase information meeting the budget information.
In one embodiment, the computer device performance identification method further includes:
acquiring related computer cluster information;
screening hardware parameters and using parameters of the same associated computer cluster according to the associated computer cluster information to obtain cluster hardware parameters and cluster using parameters;
and inputting the cluster hardware parameters and the cluster use parameters into a performance identification model to obtain the current cluster available performance parameter value of the associated computer cluster.
In one embodiment, the computer device performance identification method further includes:
acquiring available performance parameter values of each computer device in a computer cluster;
acquiring a judgment threshold corresponding to each user;
and screening users using the computer equipment from the users with the judgment threshold value lower than the available performance parameter value.
In one embodiment, the performance recognition model comprises:
K＝Y/(1-R)；
Y＝∑(α 1 y 1 +α 2 y 2 +…+α m y m )；
R＝∑(β 1 r 1 +β 2 r 2 +…+β n r n )；
wherein K represents the value of the available performance parameter, R represents the usage parameter, R n Denotes a single use parameter, β n Scale factors representing corresponding individual use parameters, n representing the serial number of the use parameter, Y representing the integrated hardware parameter, Y m Representing a hardware parameter, α m The impact factors of the corresponding hardware parameters are shown, and m represents the serial number of the sub-hardware parameters.
The invention also provides a computer equipment performance identification device, comprising:
the reading unit is used for reading the sub-hardware parameters corresponding to each hardware of the computer equipment and calculating the hardware parameters;
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the use parameters of the computer equipment;
and the calculating unit is used for inputting the hardware parameters and the use parameters into the performance recognition model to obtain the current available performance parameter values of the computer equipment.
The invention also provides a computer equipment performance identification electronic equipment, comprising:
a processor;
a memory for storing processor-executable instructions;
the processor is used for executing the computer equipment performance identification method.
The present invention also provides a non-transitory computer-readable storage medium, wherein instructions of the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the computer device performance identification method described above.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
reading sub-hardware parameters corresponding to each hardware of the computer equipment, and calculating the hardware parameters; acquiring use parameters of computer equipment; and inputting the hardware parameters and the use parameters into a performance recognition model to obtain the current available performance parameter values of the computer equipment. By acquiring hardware parameters and use parameters and combining a performance identification model, the current available performance parameter values of the computer equipment can be acquired, and the performance of the computer equipment can be accurately and efficiently identified. According to the available performance parameter values and the correspondingly obtained judgment threshold values, whether the corresponding computer equipment is in the state to be optimized or not can be judged, and the judgment efficiency and the judgment accuracy are improved.
In addition, the performance state of the computer equipment can be determined in batch and real time by applying the method, so that important references are provided for the use arrangement, equipment scrappage identification, hardware optimization and the like of the computer equipment.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow diagram of a computer device performance identification method of an exemplary embodiment;
FIG. 2 is a flowchart of a method of calculating a decision threshold in an exemplary embodiment;
FIG. 3 is a flowchart of a method of prompting an update to a hardware component of an exemplary embodiment;
FIG. 4 is a flowchart of a method of generating a purchase order to update a hardware component of an exemplary embodiment;
FIG. 5 is a flowchart of a method for associating computer cluster device performance identification of an exemplary embodiment;
FIG. 6 is a flowchart of a method of screening available users of an exemplary embodiment;
FIG. 7 is an apparatus block diagram of a computer device capability identification apparatus of an exemplary embodiment;
FIG. 8 is a diagram of an application scenario of an exemplary embodiment.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
It will be understood by those skilled in the art that "terminal" and "terminal device" as used herein include both devices having a wireless signal receiver, which are only devices having a wireless signal receiver without transmit capability, and devices having receive and transmit hardware, which are devices having receive and transmit hardware capable of performing two-way communications over a two-way communications link. Such a device may include: a cellular or other communication device having a single line display or a multi-line display or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service), which may combine voice, data processing, facsimile and/or data Communications capabilities; a PDA (personal Digital Assistant) which may include a radio frequency receiver, a pager, internet/intranet access, web browser, notepad, calendar, and/or GPS (Global Positioning System) receiver; a conventional laptop and/or palmtop computer or other device having and/or including a radio frequency receiver. As used herein, a "terminal" or "terminal device" may be portable, transportable, installed in a vehicle (aeronautical, maritime, and/or land-based), or situated and/or configured to operate locally and/or in a distributed fashion at any other location(s) on earth and/or in space. The "terminal" and "terminal Device" used herein may also be a communication terminal, a Internet access terminal, and a music/video playing terminal, for example, may be a PDA, an MID (Mobile Internet Device), and/or a Mobile phone with music/video playing function, and may also be a smart television, a set-top box, and other devices.
As will be appreciated by those skilled in the art, a remote network device, as used herein, includes, but is not limited to, a computer, a network host, a single network server, a collection of multiple network servers, or a cloud of multiple servers. Here, the Cloud is composed of a large number of computers or network servers based on Cloud Computing (Cloud Computing), which is a kind of distributed Computing, a super virtual computer composed of a group of loosely coupled computer sets. In the embodiment of the present invention, the communication between the remote network device, the terminal device and the WNS server may be implemented by any communication method, including but not limited to mobile communication based on 3GPP, LTE and WIMAX, computer network communication based on TCP/IP and UDP protocols, and short-range wireless transmission based on bluetooth and infrared transmission standards.
Referring to fig. 1, fig. 1 is a flowchart of a computer device performance identification method according to an exemplary embodiment, and an embodiment of the computer device performance identification method according to the present invention includes the following steps:
in step S11, hardware parameters corresponding to each hardware of the computer device are read.
The hardware parameters read from the computer device are mainly used to identify the current hardware state, and may include functional parameters, depreciation duration, purchase date, failure frequency, identification code, maintenance cost, remaining life, and the like.
Taking hardware parameters of a complete computer equipment as an example, the functional parameters can be parameters such as processor frequency, processor operation times, display performance, operation speed and the like; the depreciation duration can be the accumulated working duration of the whole computer equipment; the purchase date may be a purchase time of the computer device; the failure frequency may be a blue screen frequency of the computer device, a software flash back frequency, or the like.
In addition, considering the factor of the identification accuracy, the starting time of the computer equipment can be further obtained, so that the states of depreciation, loss and the like of the computer equipment can be estimated by utilizing the starting time.
For the details of reading the hardware parameters, taking reading the hardware parameters of the hard disk as an example:
the rotating speed, reading speed, writing speed and the like of the hard disk can be read; the depreciation duration can be the accumulated writing duration, reading duration, writing data volume and the like of the hard disk; the purchase date refers to the time of purchasing the corresponding hard disk and can also correspond to the quality guarantee period of the hard disk; the failure frequency refers to the number of failures of the hard disk from starting to present, and the failure type of the hard disk can be correspondingly obtained; the identification code can be an internal management code of the hard disk, and can also be a hardware identification code of the hard disk, so that the hard disk is convenient to identify and position; the maintenance cost may be a maintenance cost corresponding to a maintenance item of the hard disk, for example, a price and a labor cost for replacing a screw or a reading part; the remaining life may be the remaining operable capacity of the hard disk, the remaining operating time, and the like.
In addition to reading the hardware parameters of the hard disk, as another example, the hardware parameters of other peripheral devices are read, taking the hardware parameters of the screen as an example: the function parameters can be related parameters directly reflecting screen functions, such as pixels, color gamut, screen refreshing frequency and the like of a screen; the depreciation duration refers to the corresponding accumulated working duration of the screen; the purchase date refers to the purchase date of the screen, and the starting time of the screen can be acquired in other possible embodiments; the failure frequency can be abnormal screen brightness frequency, screen delay frequency and the like; the identification code may be a goods management code of the screen; the maintenance cost can be the related cost of maintenance items such as maintenance of the kinescope, replacement of the liquid crystal layer, capacitance, circuit board and the like; the remaining life may be the length of time that the screen may continue to display while maintaining normal operation.
In the process, for the purpose of scientificity of statistics, the acquired hardware parameters can be calculated to obtain comprehensive hardware parameters in a weight statistics mode, the weights can be determined according to the importance degree of the hardware, the maintenance difficulty, the maintenance cost and the purchase price, the weights of the hardware parameters are finally calculated to obtain the comprehensive hardware parameters, and the comprehensive hardware parameters reflect the integral comprehensive hardware level of the computer equipment. The integrated hardware parameters can replace the hardware parameters for subsequent application.
Besides the complete machine, the hard disk and the screen of the computer device, the computer device can also identify other peripheral devices, such as a keyboard, a mouse and the like, and can also identify hardware of other computer devices, such as internal memory, a mainboard, a video card and the like.
In addition to reading the hardware parameters through direct testing of hardware, the hardware parameters in the process can also be tested through starting a process, calling software, executing a specified instruction or completing a specified task. Specifically, in the above process, drawing software may be called to draw a designated drawing, a screen may be called to display a designated graphic, play a preset video, run an algorithm, and the like.
In step S12, usage parameters of the computer device are acquired.
In the above process, the use parameters of the computer device currently being used are mainly obtained. The use parameters refer to parameters which can characterize the user of the computer equipment, and generally, the parameters can be embodied as parameters related to the user, such as position information, position information and business information. The job information can be job level or department; the post information can be specific posts and items corresponding to the posts; the service information may be a service at a particular time of endeavor. The acquisition of the use parameters can be obtained through login accounts, computer management numbers, user input and the like.
When the user logs in the corresponding computer equipment, the corresponding use information can be obtained through the login account.
The usage parameters will be exemplarily shown below by the actual user:
a, a user, wherein the job information is an administrative department manager, the post information is a salary manager, and the service information is a manager salary accounting, salary plan making and the like;
b, the user, the job information is administrative office staff, the post information is personnel, the business information is administrative personnel information, etc.;
c, the user, the position information is an algorithm engineer, the business information is a writing algorithm, and the like;
d, the user, the job information is the ordinary staff of the art designing department, the post information is the art designing engineer, the business information is the designed game figure, etc.;
and E, the user, the position information is the manager of the financial department, the post information is the auditor, and the service information is auditing, budget execution supervision and the like.
In step S13, the hardware parameters and the usage parameters are input into a performance recognition model, and current available performance parameter values of the computer device are obtained.
In the process, the performance of the computer equipment of the user a is identified, the use parameters of the user a (executive supervisor, position information being executive supervisor, business information being supervisor salary accounting, making salary plan, etc.) and the hardware parameters of the computer equipment are input into the performance identification model, and the current available performance parameter value of the computer equipment is finally output.
The input of the hardware parameter may be the hardware parameter after comprehensive calculation, or the hardware parameter corresponding to each hardware of the computer device. Wherein the applied usage parameter may be the usage parameter integrated after the integrated calculation of the weight.
In order to better show the performance recognition model, this embodiment provides an implementation manner of the performance recognition model, which includes:
K＝Y/(1-R)；
Y＝∑(α 1 y 1 +α 2 y 2 +…+α m y m )；
R＝∑(β 1 r 1 +β 2 r 2 +…+β n r n )；
in the above formula, K represents the value of the available performance parameter, R represents the usage parameter, R n Denotes a single use parameter, β n Scale factors representing corresponding individual use parameters, n representing the serial number of the use parameter, Y representing the integrated hardware parameter, Y m Denotes a hardware parameter, α m The impact factors of the corresponding hardware parameters are shown, and m represents the serial number of the sub-hardware parameters.
Continuing to identify the computer equipment of the user A, wherein the hardware parameters of the computer equipment are respectively as follows:
hard disk: hardware parameter y of hard disk 1 0.5, influence factor alpha 1 Is 0.3;
a first memory: hardware parameter y of first memory 2 0.5, influence factor alpha 2 Is 0.6;
a second memory: hardware parameter y of the second memory 3 0.8, influence factor alpha 3 Is 0.6;
a central processing unit: hardware parameter y of central processing unit 3 0.7, influence factor α 3 Is 0.9;
the integrated hardware parameter Y for the user computer device is 1.56.
The corresponding use parameters of the computer equipment used by the user A are respectively as follows:
and (4) post information: administration supervisor, its single use parameter r 1 Is 0.4, scale factor beta 1 Is 0.3;
and (4) position information: executive of salary, its single use parameter r 2 Is 0.3, the scaling factor beta 2 Is 0.5;
service information: calculating salary, making salary plan, using parameter r 3 Is 0.2, scale factor beta 3 Is 0.8;
a user computer device, calculating the use parameter R of the computer device to be 0.43.
According to the above performance recognition model, the available performance parameter value K for the A user computer device is 2.73.
To better show the application of the performance recognition model, take the computer device of B user as an example, wherein the hardware parameters of the computer device are:
hard disk: hardness of hard diskPart parameter y 1 0.2, influence factor alpha 1 Is 0.3;
a first memory: hardware parameter y of the first memory 2 0.2, influence factor alpha 2 Is 0.6;
a second memory: hardware parameter y of second memory 3 Is 0, influence factor alpha 3 Is 0.6;
a central processing unit: hardware parameter y of central processing unit 3 0.3, influence factor alpha 3 Is 0.9;
the integrated hardware parameter Y of the user computer device is 0.45.
The use parameters corresponding to the computer equipment of the user B are respectively as follows:
and (4) post information: administrative staff, whose individual use parameter r 1 Is 0.1, the scaling factor beta 1 Is 0.3;
and (4) position information: personnel, whose individual use parameter r 2 Is 0.1, scale factor beta 2 Is 0.5;
service information: managing personnel information, with a single use parameter r 3 Is 0.1, scale factor beta 3 Is 0.8;
b the usage parameter R of the user computer device is 0.16.
According to the performance recognition model described above, the available performance parameter value K for the B-user computer device is 0.54.
The above-mentioned available performance parameter K is used to indicate the performance matching condition of the current user to the corresponding computer device, and generally, the higher the available performance parameter value is, the higher the degree of meeting the performance requirement of the computer device used by the user is indicated, otherwise, the lower the performance of the computer device used by the user is, the lower the performance requirement is.
In order to determine whether the computer device needs to be scrapped, the computer device performance identification method further includes: and if the current available performance parameter value is smaller than a judgment threshold value, judging that the computer equipment belongs to the equipment to be optimized.
The available performance parameter K of the user a using the computer device is 2.73, and according to the use parameter of the user a, the corresponding judgment threshold of the user a may be correspondingly matched, for example, in this embodiment, the judgment threshold of the user a is 2.50, and it is determined that the computer device does not belong to the device to be optimized.
The available performance parameter K of the user B using the computer device is 0.54, and according to the usage parameter of the user B, the corresponding judgment threshold of the user B may be correspondingly matched, for example, in this embodiment, the judgment threshold of the user B is 0.60, and the available performance parameter K is smaller than the judgment threshold, so that the computer device of the user B is determined to belong to the device to be optimized.
The judgment threshold value of the user can be correspondingly matched in the database according to the use parameters of the user. For example, the user C may match a corresponding judgment threshold according to the job information, the post information, and the service information, and may match a judgment threshold similar to the component of the usage parameter of the user C when the usage parameter of the user C lacks a corresponding judgment threshold in the database, for example, when the job position or the post of the user C is a newly added post.
In order to efficiently and accurately acquire the judgment threshold of the user, a database of the judgment threshold can be constructed. When the database of the judgment threshold is established, the virtual user can be adopted to correspondingly set the judgment threshold, so that the judgment threshold can be conveniently obtained through the use parameters of the user in the following process. For example, the usage information of the D user and the E user may be copied with reference to the D user and the E user to construct a virtual user.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for calculating a judgment threshold according to an exemplary embodiment, where the method includes:
in step S21, the usage parameters of the user are acquired.
In the above process, the obtained usage parameter may be job information, post information, service information, and the like of the user.
In step S22, a decision parameter and a corresponding decision weight are acquired based on the use parameter of the user.
In the above process, the determination parameters and the determination weights may be respectively obtained according to the user usage information, taking user a as an example:
and (4) post information: administrative supervisor, its decision parameter is 1, judge the weight to be 0.3;
and (4) position information: a paymate, whose determination parameter is 2, and the determination weight is 0.5;
service information: the compensation accounting and compensation plan is made, the determination parameter is 1.5, and the determination weight is 0.8.
In step S23, a determination threshold corresponding to the user is calculated based on the determination parameter and the determination weight.
The judgment threshold is obtained by accumulation calculation according to the product of the judgment parameter and the judgment weight, and the judgment threshold of the user A is 2.5. In this embodiment, the decision weight may be equal to the scaling factor of the single-term usage parameter. In other possible embodiments, the decision weight may be positively correlated with the scale factor of the single use parameter. The judgment threshold value can be adjusted adaptively by correspondingly configuring the judged weight and the judged parameter through the use parameter of the user, so that the judgment threshold value is more matched with the use parameter of the user, and the situation that the judgment threshold value is preset but is separated from the actual situation of the user is reduced. Through the scheme, the judgment threshold value can be adjusted by combining the actual situation of the user, so that the performance identification of the computer is highly related to the use parameters of the user, and the actual situation can be fully reflected.
Referring to fig. 3, fig. 3 is a flowchart illustrating a method for prompting a hardware component to be updated according to an exemplary embodiment, in this embodiment, the method for identifying performance of a computer device further includes a step of calculating a judgment threshold:
in step S31, the enabled hardware detection module detects each hardware performance parameter of the computer device to be optimized.
According to the related data obtained before, the available performance parameter K of the computer device used by the user B is 0.54, and according to the usage parameter of the user B, the corresponding judgment threshold of the user B may be correspondingly matched, for example, in this embodiment, the judgment threshold of the user B is 0.60, and the available performance parameter K is smaller than the judgment threshold, so that the computer device of the user B is determined to belong to the computer device to be optimized.
In order to identify the specific hardware needing to be updated or scrapped, a hardware detection module is started to detect the computer equipment to be optimized of the user B, and each hardware performance parameter in the computer equipment to be optimized in the current state is obtained. For example, the performance parameters of each hardware of the computer device to be optimized are: the performance parameter of the hard disk is 0.2; the performance parameter of the first memory is 0.2; the performance parameter of the second memory is 0; the performance parameter of the cpu is 0.3. In the detection process, the hardware detection module invokes corresponding hardware or running software through a preset instruction so as to detect the actual performance state of the hardware in the current running state.
In step S32, the hardware component to be replaced is determined based on the respective hardware performance parameters and the user' S usage parameters.
In step S33, the update of the hardware component is prompted.
And determining whether the current hardware performance parameters meet the requirements or not according to the use parameters of the user. For example, the usage parameter of B user requires the performance parameter of the hard disk to be greater than 0.5, and the performance parameter of the hard disk is not satisfactory. And B, setting a second memory according to the requirement of the computer equipment of the user B, wherein the performance parameter of the second memory is larger than 0.3, and detecting that the performance parameter of the second memory is 0 and smaller than 0.3 when the second memory is possibly not assembled or burnt out due to short circuit and the like according to the detected performance parameter. Thus prompting the hard disk and the second memory for updating.
The judgment according to the hardware performance parameters is mainly determined according to the comparison between the hardware parameters in the computer equipment and the current hardware performance parameters, and aims to detect whether the performance parameters of the current hardware meet the preset condition. In the actual use process, the hardware in the computer equipment causes the actually measured hardware performance parameter to be less than or equal to the hardware parameter due to the use time, natural loss and the like, and when the difference value between the hardware performance parameter and the hardware parameter is overlarge, the loss of the hardware in the actual operation process is over large, and the hardware should be correspondingly replaced. For example, the performance parameter of the second memory is already 0, which indicates that the second memory cannot operate normally and should be replaced.
Further, prompting to update the hardware component may be prompted directly to the user by text or voice by inscription on a display device. More preferably, the requirement corresponding to the replacement of the hardware component can be sent to the relevant department, a maintenance item is generated, and the relevant department is requested to assign a maintenance engineer to replace the component on the computer equipment of the B user.
By replacing the components, hardware parameters of the computer device to be optimized can be optimized, and the value of the available performance parameters is further improved. When the available performance parameter is improved to be larger than the judgment threshold value through the replacement part, the computer equipment can be recovered to be in the usable state from the state to be optimized, and the complete machine scrapping of the computer equipment of the user B is avoided. When the hardware of the computer equipment to be optimized needs to be replaced is too much or the unit price is too high and the maintenance cost is too high, the whole computer equipment is scrapped, and the hardware is not replaced any more.
Referring to FIG. 4, FIG. 4 is a flowchart of a method of generating a purchase order to update a hardware component, according to an exemplary embodiment. In this embodiment, the method for identifying performance of computer equipment further includes the following steps:
in step S41, hardware information of the hardware component to which the update is to be presented is acquired, and purchase information is generated in response to the acquired hardware information.
In the above process, the hardware information of the hardware component for prompting updating is acquired, and the purchase information can be generated according to the hardware information. For example, for the hard disk and the second memory of the B user, purchase information corresponding to purchasing the second memory of the hard disk cartridge may be generated, where the purchase information includes the model, capacity, price, and quantity of the hard disk, and further includes information such as price, capacity, frequency, bandwidth, socket adaptation, and processor adaptation of the second memory.
In order to more accurately acquire the purchase price, price and specification information can be acquired on the purchase platform through corresponding purchase information, so that purchase information is generated, and the whole purchase process can be carried out on the purchase platform.
In step S42, budget information is acquired, and it is determined whether or not the purchase information matches the budget based on the budget information.
For example, in the process of auditing the procurement information, the budget information including the budget balance for hardware replacement in the current year or other budget periods is acquired, and whether the procurement information meets the budget requirements is determined according to the budget balance. When the budget information includes a limit to a specific hardware quantity or amount, the limit also needs to be satisfied, for example, the budget information limits the purchasing upper limit of the storage-type hardware in the month to 2000 yuan, and when the purchasing is still within the range of 2000 yuan in the month, it can be determined that the purchasing information conforms to the budget information.
In step S43, a purchase order is generated based on the purchase information conforming to the budget information.
In the process, the purchasing information meeting the budget information is screened, and a purchasing order is generated according to the purchasing information. The purchase order, having been subject to budget review, may be sent directly to the supplier to complete the order. The auditing of the purchasing process can reduce auditing risks, and simultaneously accelerate the purchasing speed of hardware, so that the computer equipment corresponding to the hardware needing to be replaced can operate at preset performance as soon as possible.
Referring to fig. 5, fig. 5 is a flowchart of a method for performance identification of associated computer cluster devices in an exemplary embodiment. In this embodiment, the method for identifying the performance of the computer device further includes:
in step S51, associated computer cluster information is acquired.
In the above process, the associated computer cluster is preset. The associated computer clusters can be computer clusters formed by association of computers in corresponding departments, teams and work groups. Referring to fig. 8, fig. 8 is an application scenario diagram of an exemplary embodiment, and fig. 8 takes a work group formed by the user a, the user B, the user C, the user D, and the user E as an example, and accordingly the user associations form an associated computer cluster. The associated computer cluster information includes: personnel composition, computer equipment condition, etc.
In step S52, according to the information of the associated computer clusters, the hardware parameters and the usage parameters of the same associated computer cluster are screened to obtain cluster hardware parameters and cluster usage parameters.
According to the associated computer cluster information, screening the hardware parameters and the use parameters belonging to the same associated computer cluster, namely the same working group, and clustering to generate cluster hardware parameters and cluster use parameters.
For example, the hardware parameters and the usage parameters of the computer devices corresponding to each user in the same working group may be accumulated to generate the cluster hardware parameters and the cluster usage parameters, respectively. And quantizing to form cluster factors corresponding to each user according to the division condition and the traffic ratio in the working group, and performing weighted statistics on the hardware parameters and the use parameters according to the weights of the cluster factors to generate cluster hardware parameters and cluster use parameters.
In step S53, the cluster hardware parameter and the cluster use parameter are input into the performance identification model, and a current cluster available performance parameter value of the associated computer cluster is obtained.
In the above process, the performance recognition model that generates the single user available performance parameter values may continue to be employed. The corresponding generated cluster available performance parameter value may be used to identify a computer device performance level for the work team. The computer equipment performance of the working group is identified through unified regulation and control of the cloud server, and managers can conveniently and comprehensively master the computer equipment performance of the working group in time. Furthermore, the remote server can be opened to corresponding managers for remote monitoring, and the managers can regulate and control the available performance parameter values of the computer equipment and the cluster available performance parameter values of each user according to project progress and project requirements, so that the better effect of the existing computer equipment can be brought into play.
Referring to fig. 6, fig. 6 is a flowchart of a method of screening available users according to an exemplary embodiment. In this embodiment, the method for identifying the performance of the computer device further includes:
in step S61, available performance parameter values for the individual computer devices in the computer cluster are obtained.
In step S62, the determination threshold corresponding to each user is acquired.
In the process, the available performance parameters are generated according to the use parameters and the hardware parameters of each user, and the judgment threshold value of the corresponding user is obtained from the judgment threshold value database according to the use parameters. The computer cluster can be a work group, and can also be a computer cluster formed by all related computer equipment in departments or companies.
In step S63, users using the computer device are filtered from the users whose judgment threshold is lower than the available performance parameter value.
For example, when the available performance parameter value of the C user is determined to be less than the determination threshold, the corresponding computer device is determined to be the computer device to be optimized. This indicates that the device is not suitable for the C user, but there may be other users in the computer cluster that can use the computer device. To this end, users having a decision threshold below the available performance parameter value are screened from the computer cluster for users who can use the computer device. For example, the computer device of the user C is marked as the computer device to be optimized, but is screened from the work group, and the judgment threshold of the user B is lower than the available performance parameter value of the computer device, then the user B is screened out, and as the user who can use the computer device, the state of the corresponding computer device can also be changed from the state to be optimized to the available state.
Through the process, the computer equipment scrapped from the user C can be prompted and allocated to the user B which can be used, the replacement cost can be reduced, the increase of the purchasing budget caused by direct scrapping or frequent optimization of the computer equipment is avoided, and meanwhile, the recycling of the computer equipment is facilitated.
Referring to fig. 7, fig. 7 is a block diagram of an apparatus for identifying performance of a computer device according to an exemplary embodiment. In this embodiment, an apparatus for identifying performance of a computer device is provided, which includes:
a reading unit 71, configured to read hardware parameters corresponding to each piece of hardware of the computer device;
an acquisition unit 72 for acquiring usage parameters of the computer device;
a calculating unit 73, configured to input the hardware parameters and the usage parameters into the performance recognition model, and obtain current available performance parameter values of the computer device.
In this embodiment, an electronic device for identifying performance of a computer device is further provided, including:
a processor;
a memory for storing processor-executable instructions;
the processor is used for executing the computer equipment performance identification method.
In this embodiment, there is also provided a non-transitory computer readable storage medium, wherein instructions of the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the computer device performance identification method described above.
The computer equipment performance identification method discloses the technical scheme that: reading hardware parameters corresponding to each hardware of the computer equipment; acquiring use parameters of computer equipment; and inputting the hardware parameters and the use parameters into a performance recognition model to obtain the current available performance parameter values of the computer equipment. According to the technical scheme, the hardware parameters and the use parameters are obtained, and the performance identification model is combined, so that the current available performance parameter values of the computer equipment can be output, and the performance of the computer equipment can be accurately and efficiently identified. According to the available performance parameter values and the correspondingly obtained judgment threshold values, whether the corresponding computer equipment is in the state to be optimized or not can be judged, and the judgment efficiency and the judgment accuracy are improved. The performance state of the computer equipment can be determined in batch and real time by applying the method. The method of the invention can be applied to hardware management in computer room management, and is particularly convenient for realizing host management. The method can be carried out before the computer equipment is started, accounts log in and shut down, and the host can be managed at the terminal and the mobile terminal corresponding to hardware management personnel.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a partial embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (8)
1. A computer equipment performance identification method is characterized by comprising the following steps:
reading hardware parameters corresponding to each hardware of the computer equipment;
acquiring use parameters of computer equipment;
inputting the hardware parameters and the use parameters into a performance identification model to obtain the current available performance parameter values of the computer equipment;
the method further comprises the following steps:
if the current available performance parameter value is smaller than a judgment threshold value, judging that the computer equipment belongs to equipment to be optimized;
acquiring use parameters of a user;
acquiring a judgment parameter and a corresponding judgment weight according to a use parameter of a user;
and calculating a judgment threshold corresponding to the user according to the judgment parameters and the judgment weight.
2. The computer device performance identification method of claim 1, further comprising:
starting a hardware detection module to detect each hardware performance parameter of the computer equipment to be optimized;
determining hardware components needing to be replaced according to the performance parameters of each hardware and the use parameters of a user;
prompting to update the hardware component.
3. The computer device performance identification method of claim 2, wherein after the step of prompting to update the hardware component, further comprising:
acquiring hardware information of a hardware component prompting updating, and correspondingly generating purchasing information;
acquiring budget information, and judging whether the purchasing information conforms to budget or not according to the budget information;
and generating a purchase order according to the purchase information conforming to the budget information.
4. The computer device performance identification method of claim 1, further comprising:
acquiring related computer cluster information;
screening hardware parameters and using parameters of the same associated computer cluster according to the associated computer cluster information to obtain cluster hardware parameters and cluster using parameters;
and inputting the cluster hardware parameters and the cluster use parameters into a performance identification model to obtain the current cluster available performance parameter value of the associated computer cluster.
5. The computer device performance identification method of claim 4, further comprising:
acquiring available performance parameter values of each computer device in a computer cluster;
acquiring a judgment threshold corresponding to each user;
and screening users using the computer equipment from the users with the judgment threshold value lower than the available performance parameter value.
6. The computer device performance identification method of any one of claims 1 to 5, wherein the performance identification model comprises:
K＝Y/(1-R)；
Y＝∑(α 1 y 1 +α 2 y 2 +…+α m y m )；
R＝∑(β 1 r 1 +β 2 r 2 +…+β n r n )；
wherein K represents the value of the available performance parameter, R represents the usage parameter, R n Denotes a single item of use parameter, β n Scale factors representing corresponding individual use parameters, n representing the serial number of the use parameter, Y representing the integrated hardware parameter, Y m Representing a hardware parameter, α m The impact factors of the corresponding hardware parameters are shown, and m represents the serial number of the sub-hardware parameters.
7. A computer device performance identification apparatus, comprising:
the reading unit is used for reading the sub-hardware parameters corresponding to each hardware of the computer equipment and calculating the hardware parameters;
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the use parameters of the computer equipment;
the computing unit is used for inputting the hardware parameters and the use parameters into a performance identification model to obtain the current available performance parameter values of the computer equipment;
the apparatus is further configured to: if the current available performance parameter value is smaller than a judgment threshold value, judging that the computer equipment belongs to equipment to be optimized;
acquiring use parameters of a user;
acquiring a judgment parameter and a corresponding judgment weight according to a use parameter of a user;
and calculating a judgment threshold corresponding to the user according to the judgment parameters and the judgment weight.
8. A computer device capability recognition electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the computer device capability identification method of any one of claims 1-6.
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