CN116434824B - Method for testing optimal performance of hard disk and product cooperation - Google Patents
Method for testing optimal performance of hard disk and product cooperation Download PDFInfo
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- CN116434824B CN116434824B CN202310701512.XA CN202310701512A CN116434824B CN 116434824 B CN116434824 B CN 116434824B CN 202310701512 A CN202310701512 A CN 202310701512A CN 116434824 B CN116434824 B CN 116434824B
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Classifications
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- G—PHYSICS
- G11—INFORMATION STORAGE
- G11C—STATIC STORES
- G11C29/00—Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
- G11C29/56—External testing equipment for static stores, e.g. automatic test equipment [ATE]; Interfaces therefor
- G11C29/56004—Pattern generation
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- G—PHYSICS
- G11—INFORMATION STORAGE
- G11C—STATIC STORES
- G11C29/00—Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
- G11C29/04—Detection or location of defective memory elements, e.g. cell constructio details, timing of test signals
- G11C29/08—Functional testing, e.g. testing during refresh, power-on self testing [POST] or distributed testing
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- 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
Abstract
The invention belongs to the field of performance test of hard disks, and provides a method for testing optimal performance of hard disks and products, which comprises the following steps: obtaining the type of a hard disk to be tested; setting corresponding preconditions for different types of hard disks to be tested; before performance testing is carried out on a hard disk to be tested, acquiring the depth number under a random scene test and the depth number under a sequential scene test; acquiring an optimal depth parameter of a hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test; taking the optimal depth parameter as a reference to obtain an optimal thread parameter; and performing performance test on the hard disk by adopting the optimal thread parameters and the optimal depth parameters. The invention can model the thread change and the depth change of the hard disk before performance test, analyze the graph of the generated data, obtain the optimal thread number and depth number by analysis, and perform basic performance test or long-time stability test after obtaining the parameter, thereby reaching the optimal performance of the configuration more quickly.
Description
Technical Field
The invention relates to the field of performance test of hard disks, in particular to a method for testing optimal performance of hard disks and products.
Background
The main parameters of the current hard disk performance test are derived from specs of manufacturers, the CPU of different servers are inconsistent with the configured test parameters, the current test is not satisfied according to the parameter test provided by the manufacturers, and repeated pressurization parameter adjustment is needed to achieve the optimal performance, so that time and labor are wasted.
Disclosure of Invention
The invention aims to provide a method for testing the optimal performance of a hard disk and a product, which can be used for bottoming out optimal parameters under different configurations without specs, saves time and labor, and meets the requirements of thread depth performance test.
The invention solves the technical problems and adopts the following technical scheme:
a method for testing optimal performance of hard disk and product cooperation comprises the following steps:
obtaining the type of a hard disk to be tested;
setting corresponding preconditions for different types of hard disks to be tested;
before performance testing is carried out on a hard disk to be tested, acquiring the depth number under a random scene test and the depth number under a sequential scene test;
acquiring an optimal depth parameter of a hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test;
taking the optimal depth parameter as a reference to obtain an optimal thread parameter;
and performing performance test on the hard disk by adopting the optimal thread parameters and the optimal depth parameters.
As further optimization, the types of the hard disk to be tested include Solid State Disk (SSD) and mechanical hard disk (HDD).
As further optimization, for the mechanical hard disk HDD, the depth number under the random scene test and the depth number under the sequential scene test are obtained specifically as follows:
directly performing depth test on a disc of the mechanical hard disk to be tested, wherein the default thread is 1, and the depth is changed from 32 to 1024 in an increasing way;
respectively performing small-block random writing and random reading, judging the data graph IOPS, and acquiring depth saturation points, namely acquiring depth numbers under random scene test;
and respectively performing massive sequential writing and sequential reading, judging the data graph BW, and acquiring a depth saturation point, namely acquiring the depth number under the sequential scene test.
As a further optimization, the obtaining of the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test means:
after the depth number under the random scene test of the mechanical hard disk HDD and the depth number under the sequential scene test are obtained, inquiring a data graph IOPS and a data graph BW;
when the depth number in the data pattern IOPS and the depth number in the data pattern BW are balanced, the depth number at this time is confirmed to be the optimal depth parameter of the mechanical hard disk HDD.
As further optimization, the obtaining the optimal thread parameters based on the optimal depth parameters specifically includes:
after the optimal depth parameter of the mechanical hard disk HDD is obtained, taking the optimal depth parameter as a reference, performing small-block random read-write thread increasing from 1 to 64 to judge a data graph IOPS;
and acquiring saturation points of threads in the data graph IOPS, wherein the sequence default thread is 1, and the saturation points of the threads are the optimal thread parameters of the mechanical hard disk HDD.
As further optimization, the solid state disk SSD is pre-embedded with write data before acquiring the depth number under the random scene test and the depth number under the sequential scene test.
As further optimization, for the solid state disk SSD, the obtaining the depth number under the random scene test and the depth number under the sequential scene test specifically includes:
erasing a disc of the SSD to be tested, and sequentially writing the whole disc twice;
the default thread is 1, the large-block sequential writing and the sequential reading are respectively carried out, the depth test is carried out, and the depth is changed from 32 to 1024 in an increasing way;
judging a data graph BW, and acquiring a depth saturation point, namely acquiring the depth number under a sequential scene test;
after the depth number under the sequential scene is obtained, performing small-block random writing to a steady state, performing small-block random writing and random reading respectively, performing depth test, and changing the depth from 32 to 1024 in an incremental manner;
and judging the data graph IOPS, and acquiring a depth saturation point, namely acquiring a depth number under a random scene test.
As a further optimization, the obtaining of the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test means:
after the depth number under the SSD random scene test and the depth number under the sequential scene test are obtained, inquiring a data graph IOPS and a data graph BW;
when the depth number in the data graph IOPS and the depth number in the data graph BW are balanced, the depth number at the moment is confirmed to be the optimal depth parameter of the solid state disk SSD.
As further optimization, the obtaining the optimal thread parameters based on the optimal depth parameters specifically includes:
after the optimal depth parameter of the SSD is obtained, taking the optimal depth parameter as a reference, performing small-block random read-write thread increasing from 1 to 64 to judge a data graph IOPS;
and acquiring a saturation point of a thread in the data graph IOPS, wherein the sequence default thread is 1, and the saturation point of the thread is the optimal thread parameter of the solid state disk SSD.
The beneficial effects of the invention are as follows: through the method for testing the optimal performance of the hard disk and the product, firstly, the type of the hard disk to be tested is obtained; secondly, setting corresponding preconditions for different types of hard disks to be tested; then, before the performance test of the hard disk to be tested, acquiring the depth number under the random scene test and the depth number under the sequential scene test; then, obtaining the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test; then, taking the optimal depth parameter as a reference to obtain an optimal thread parameter; and finally, performing performance test on the hard disk by adopting the optimal thread parameters and the optimal depth parameters.
Therefore, the invention can model the thread change and the depth change of the hard disk before performance test, analyze the graph of the generated data to obtain the optimal thread number and the depth number, acquire the parameter and then perform basic performance test or long-time stability test to achieve the optimal performance of the configuration, model the optimal parameter under different configurations without spec, save time and labor, and simultaneously meet the thread depth performance test.
Drawings
FIG. 1 is a flow chart of a method for testing the optimal performance of a hard disk and a product in accordance with the embodiment 1 of the present invention;
FIG. 2 is a graph of the IOPS data trend obtained from the 4k random write, thread 1, and depth change from 1-128 in embodiment 2 of the present invention;
FIG. 3 is a schematic diagram of a BW data trend graph obtained from a thread change of 1-128, according to the 128K sequential read bandwidth test of embodiment 2 of the present invention, wherein the depth is S3/S4, and an optimal depth value is obtained.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
The embodiment provides a method for testing optimal performance of matching between a hard disk and a product, a flow chart of which is shown in fig. 1, wherein the method comprises the following steps:
s1, obtaining the type of a hard disk to be tested;
s2, setting corresponding preconditions for different types of hard disks to be tested;
s3, before performance testing is carried out on the hard disk to be tested, acquiring the depth number under the random scene test and the depth number under the sequential scene test;
s4, obtaining an optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test;
s5, taking the optimal depth parameter as a reference to obtain an optimal thread parameter;
and S6, performing performance test on the hard disk by adopting the optimal thread parameters and the optimal depth parameters.
According to the method, the influence of the thread and the depth on the performance of the hard disk performance test is ensured to be matched with the parameters to reach the saturation point with the optimal hard disk performance, and the pressure of the disk is different due to the difference of different CPUs of different servers, so that the optimal parameters of the maximum capacity of the disk can be ensured to be exerted in each scene; aiming at different types of discs such as mechanical discs and solid state disks, the required preconditions are inconsistent, and in order to better enable the disc performance to tend to be stable, the characteristics of the solid state disks lead to the need of pre-embedding of data to be written; the difference between the random scene and the sequential scene of the mechanical disk and the solid state disk is that the sequential scene does not involve multithreading, and when the multithreading final performance adopted in the sequential scene tends to the performance in the random scene, the sequential thread is not used as a reference point and is mainly 1 thread according to the conventional default.
In addition, the embodiment can model the thread change and the depth change of the hard disk before performance test, analyze the graph of the generated data to obtain the optimal thread number and the optimal depth number, acquire the parameter, and then perform basic performance test or long-time stability test to achieve the optimal performance of the configuration, and model the optimal parameter under different configurations without spec, thereby saving time and labor and meeting the thread depth performance test.
Example 2
The present embodiment is based on embodiment 1, referring to fig. 2 and 3, in which the types of hard disks to be tested include solid state disks SSD and mechanical hard disks HDD.
FIG. 2 is a 4k random write, thread 1, IOPS data trend graph with depth varying from 1-128, IOPS values on the ordinate, and depth values on the abscissa, and hard disk IOPS values are saturated when depth 4 can be obtained from the trend graph of FIG. 2, thus determining the optimal depth number.
FIG. 3 is a 128K sequential read Bandwidth test, the depth is S3/S4, the thread obtains a BW data trend graph from 1-128 changes, the ordinate is BW value, the abscissa is thread value, when the thread can be obtained from the trend graph of FIG. 3 as 16, the BW value of the hard disk is saturated, so as to determine the optimal thread number.
Aiming at a mechanical hard disk HDD, the depth number under random scene test and the depth number under sequential scene test are obtained, specifically:
directly performing depth test on the disc of the mechanical hard disk to be tested, wherein the default thread is 1, the depth is changed from 32 increment to 1024 increment, most of the disc 32 basically reaches saturation, and the increase of the depth caused by insufficient server pressure is eliminated;
respectively performing small-block random writing and random reading, judging the data graph IOPS, and acquiring depth saturation points, namely acquiring depth numbers under random scene test;
and respectively performing massive sequential writing and sequential reading, judging the data graph BW, and acquiring a depth saturation point, namely acquiring the depth number under the sequential scene test.
It should be noted that, obtaining the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test refers to:
after the depth number under the random scene test of the mechanical hard disk HDD and the depth number under the sequential scene test are obtained, inquiring a data graph IOPS and a data graph BW;
when the depth number in the data pattern IOPS and the depth number in the data pattern BW are balanced, the depth number at this time is confirmed to be the optimal depth parameter of the mechanical hard disk HDD.
For the mechanical hard disk HDD, the optimal thread parameters are obtained by taking the optimal depth parameters as the reference, and the method specifically comprises the following steps:
after the optimal depth parameter of the mechanical hard disk HDD is obtained, taking the optimal depth parameter as a reference, performing small-block random read-write thread increasing from 1 to 64 to judge a data graph IOPS;
and acquiring saturation points of threads in the data graph IOPS, wherein the sequence default thread is 1, and the saturation points of the threads are the optimal thread parameters of the mechanical hard disk HDD.
In this embodiment, for different types of discs, such as a mechanical disc and a solid state disk, the required preconditions are inconsistent, so that the disc performance tends to be stable better, and the solid state disk characteristics lead to the need of data pre-embedding, so that the solid state disk SSD performs data pre-embedding before acquiring the depth number under the random scene test and the depth number under the sequential scene test.
Aiming at a solid state disk SSD, the depth number under a random scene test and the depth number under a sequential scene test are obtained, and specifically:
erasing a disc of the SSD to be tested, and sequentially writing the whole disc twice;
the default thread is 1, the large-block sequential writing and the sequential reading are respectively carried out, the depth test is carried out, and the depth is changed from 32 to 1024 in an increasing way;
judging a data graph BW, and acquiring a depth saturation point, namely acquiring the depth number under a sequential scene test;
after the depth number under the sequential scene is obtained, performing small-block random writing to a steady state, performing small-block random writing and random reading respectively, performing depth test, and changing the depth from 32 to 1024 in an incremental manner;
and judging the data graph IOPS, and acquiring a depth saturation point, namely acquiring a depth number under a random scene test.
Here, obtaining the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test means:
after the depth number under the SSD random scene test and the depth number under the sequential scene test are obtained, inquiring a data graph IOPS and a data graph BW;
when the depth number in the data graph IOPS and the depth number in the data graph BW are balanced, the depth number at the moment is confirmed to be the optimal depth parameter of the solid state disk SSD.
For the solid state disk SSD, the optimal thread parameters are obtained based on the optimal depth parameters, specifically:
after the optimal depth parameter of the SSD is obtained, taking the optimal depth parameter as a reference, performing small-block random read-write thread increasing from 1 to 64 to judge a data graph IOPS;
and acquiring a saturation point of a thread in the data graph IOPS, wherein the sequence default thread is 1, and the saturation point of the thread is the optimal thread parameter of the solid state disk SSD.
In this embodiment, after the thread depth parameter obtained from the above-mentioned obtaining to the optimal test is adopted, the parameter can be used to continue other performance tests to reach the optimal.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. 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 (6)
1. The method for testing the optimal performance of the matching of the hard disk and the product is characterized by comprising the following steps:
obtaining the types of hard disks to be tested, wherein the types of the hard disks to be tested comprise solid state disks SSD and mechanical hard disks HDD;
setting corresponding preconditions for different types of hard disks to be tested;
before performance testing is carried out on a hard disk to be tested, acquiring the depth number under a random scene test and the depth number under a sequential scene test;
acquiring an optimal depth parameter of a hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test;
taking the optimal depth parameter as a reference to obtain an optimal thread parameter;
performing performance test on the hard disk by adopting the optimal thread parameters and the optimal depth parameters;
aiming at the mechanical hard disk HDD, the depth number under the random scene test and the depth number under the sequential scene test are obtained specifically as follows:
directly performing depth test on a disc of the mechanical hard disk to be tested, wherein the default thread is 1, and the depth is changed from 32 to 1024 in an increasing way;
respectively performing small-block random writing and random reading, judging the data graph IOPS, and acquiring depth saturation points, namely acquiring depth numbers under random scene test;
respectively performing massive sequential writing and sequential reading, judging a data graph BW, and acquiring a depth saturation point, namely acquiring the depth number under a sequential scene test;
aiming at the SSD, the depth number under the random scene test and the depth number under the sequential scene test are obtained, and the method specifically comprises the following steps:
erasing a disc of the SSD to be tested, and sequentially writing the whole disc twice;
the default thread is 1, the large-block sequential writing and the sequential reading are respectively carried out, the depth test is carried out, and the depth is changed from 32 to 1024 in an increasing way;
judging a data graph BW, and acquiring a depth saturation point, namely acquiring the depth number under a sequential scene test;
after the depth number under the sequential scene is obtained, performing small-block random writing to a steady state, performing small-block random writing and random reading respectively, performing depth test, and changing the depth from 32 to 1024 in an incremental manner;
and judging the data graph IOPS, and acquiring a depth saturation point, namely acquiring a depth number under a random scene test.
2. The method for testing optimal performance of a hard disk and a product according to claim 1, wherein the obtaining the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test is:
after the depth number under the random scene test of the mechanical hard disk HDD and the depth number under the sequential scene test are obtained, inquiring a data graph IOPS and a data graph BW;
when the depth number in the data pattern IOPS and the depth number in the data pattern BW are balanced, the depth number at this time is confirmed to be the optimal depth parameter of the mechanical hard disk HDD.
3. The method for testing the optimal performance of the hard disk and the product according to claim 2, wherein the obtaining the optimal thread parameter based on the optimal depth parameter specifically comprises:
after the optimal depth parameter of the mechanical hard disk HDD is obtained, taking the optimal depth parameter as a reference, performing small-block random read-write thread increasing from 1 to 64 to judge a data graph IOPS;
and acquiring saturation points of threads in the data graph IOPS, wherein the sequence default thread is 1, and the saturation points of the threads are the optimal thread parameters of the mechanical hard disk HDD.
4. The method for testing optimal performance of a hard disk and a product according to claim 1, wherein write data embedding is performed before the SSD obtains the depth number under the random scene test and the depth number under the sequential scene test.
5. The method for testing optimal performance of a hard disk and a product according to claim 1, wherein the obtaining the optimal depth parameter of the hard disk to be tested based on the depth number under the random scene test and the depth number under the sequential scene test is:
after the depth number under the SSD random scene test and the depth number under the sequential scene test are obtained, inquiring a data graph IOPS and a data graph BW;
when the depth number in the data graph IOPS and the depth number in the data graph BW are balanced, the depth number at the moment is confirmed to be the optimal depth parameter of the solid state disk SSD.
6. The method for testing optimal performance of hard disk and product according to claim 5, wherein the obtaining optimal thread parameters based on the optimal depth parameters specifically comprises:
after the optimal depth parameter of the SSD is obtained, taking the optimal depth parameter as a reference, performing small-block random read-write thread increasing from 1 to 64 to judge a data graph IOPS;
and acquiring a saturation point of a thread in the data graph IOPS, wherein the sequence default thread is 1, and the saturation point of the thread is the optimal thread parameter of the solid state disk SSD.
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| CN115966247A (en) * | 2022-12-14 | 2023-04-14 | 武汉麓谷科技有限公司 | ZNS solid state disk performance test method |
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| CN109471762A (en) * | 2018-10-30 | 2019-03-15 | 新华三技术有限公司 | Solid-state hard disk SSD performance test methods and device |
| WO2021026509A1 (en) * | 2019-08-08 | 2021-02-11 | Intel Corporation | Link performance prediction and media streaming technologies |
| CN115129572A (en) * | 2022-07-29 | 2022-09-30 | 苏州浪潮智能科技有限公司 | Performance test method, device, equipment and medium |
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