CN111831451A - Cloud host memory allocation method, cloud host, cloud device and storage medium - Google Patents
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- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
- G06F9/5016—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals the resource being the memory
Abstract
The invention provides a cloud host memory allocation method, a cloud host, a device and a storage medium, wherein the cloud host memory allocation method comprises the following steps: acquiring a configuration instruction of a user for applying to create a cloud host; acquiring the memory capacity of the cloud host applied by the user according to the configuration instruction; and allocating storage space with corresponding capacity in a nonvolatile memory on a preset server to the cloud host as the memory of the cloud host according to the memory capacity, wherein the nonvolatile memory on the server is a memory adopting a 3D Xpoint storage technology. The invention can achieve the purposes of improving the reliability of the memory of the cloud host, ensuring the reading speed, reducing the cost and improving the memory capacity.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a cloud host memory allocation method, a cloud host, a device and a storage medium.
Background
Cloud services are an augmentation, usage, and interaction model for internet-based related services, typically involving the provision of dynamically scalable and often virtualized resources over the internet. The cloud service means that a required service is obtained through a network in an on-demand and easily-extensible manner. With the development of science and technology, the cloud host which is easier to expand and lower in cost is used by more and more users to replace a local computer, for the cloud host, a memory is an indispensable component of the cloud host, the memory is a bridge communicated with a CPU, and the running of all programs is performed in the memory, so that the performance of the memory has a great influence on the cloud host.
In the prior art, a cloud host usually adopts a Dynamic Random Access Memory (DRAM), which has the advantages of very low latency, usually nanosecond level, sufficient bandwidth, and the like, but has data volatility in abnormal situations such as power failure, and thus has low data reliability and high cost. Therefore, how to configure a memory with high reading speed, high reliability, low cost and large capacity on the cloud host is an urgent need of users.
Disclosure of Invention
The invention provides a cloud host memory allocation method, a cloud host, a device and a storage medium, which can achieve the purposes of improving the reliability of a cloud host memory, ensuring the reading speed, reducing the cost and improving the memory capacity.
In order to solve the technical problems, the invention adopts a technical scheme that: the cloud host memory allocation method comprises the following steps:
acquiring a configuration instruction of a user for applying to create a cloud host;
acquiring the memory capacity of the cloud host applied by the user according to the configuration instruction; and
and allocating storage space with corresponding capacity in a nonvolatile memory on a preset server to the cloud host as the memory of the cloud host according to the memory capacity, wherein the nonvolatile memory on the server is a memory adopting 3DXpoint storage technology.
According to an embodiment of the present invention, the obtaining, according to the configuration instruction, the memory capacity of the cloud host applied by the user includes:
if the memory capacity configuration value is not empty, taking the memory capacity configuration value as the memory capacity of the cloud host applied by the user;
and if the memory capacity configuration value is empty, acquiring the memory capacity of the cloud host applied by the user according to the number of the cpus and the preset memory capacity corresponding to the single cpu.
According to an embodiment of the present invention, the method for allocating memory of a cloud host further includes the following steps:
calculating the cache capacity required by the cloud host according to the memory capacity and a preset proportion; and
and allocating storage space with corresponding capacity in a dynamic random access memory on the preset server to the cloud host according to the cache capacity to serve as the cache of the cloud host.
According to an embodiment of the present invention, the nonvolatile memory includes a plurality of storage modes, the storage modes include a memory mode, and the cloud host memory allocation method further includes:
setting the storage mode of the nonvolatile memory as the memory mode.
According to an embodiment of the present invention, the preset memory capacity corresponding to the single cpu is 8G.
In addition, in order to solve the above technical problems, the present invention further adopts a technical solution in which: the cloud host comprises a memory, wherein the memory adopts a nonvolatile memory, and the nonvolatile memory adopts a 3D Xpoint storage technology.
According to an embodiment of the present invention, the cloud host further comprises a processor, a cache,
the cache adopts a dynamic random access memory, the cache is used for storing first data, and the memory is used for storing second data;
the processor is configured to search for target data from the cached first data, and when the processor fails to search for the target data from the first data, the processor searches for the target data from the second data in the memory, where the target data is data that needs to be called in an operation process of the cloud host.
According to an embodiment of the present invention, the cloud host further includes a memory manager, and when the processor fails to search the target data from the first data, the processor controls the memory manager to search the target data from the second data of the memory.
In addition, in order to solve the above technical problems, the present invention further adopts a technical solution in which: there is provided a cloud host memory allocation device comprising a processor, a memory coupled to the processor, wherein,
the memory has stored therein computer readable instructions that, when executed by the processor, cause the processor to perform any of the steps of the cloud host memory allocation method described above.
In addition, in order to solve the above technical problems, the present invention further adopts a technical solution in which: there is provided a storage medium having stored thereon computer-readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of any of the cloud host memory allocation methods described above.
According to the cloud host memory allocation method, the cloud host, the equipment and the storage medium, the memory of the 3DXpoint storage technology is used as the nonvolatile memory on the server, and the memory is allocated to the user as the cloud host memory according to the user configuration instruction, so that the high-cost-performance cloud host with high memory reliability, high reading speed and low cost can be provided for the user.
Furthermore, when the user does not specify specific memory capacity, the cloud host memory can be allocated to the user according to the number of the cpus and the preset memory capacity corresponding to a single cpu, so that the performance of the cloud host is fully guaranteed, the user operation is simplified, and the user experience is improved.
Further, the cache capacity required by the cloud host is calculated according to the memory capacity and the preset proportion, the cache is distributed for the cloud host, and the cache and memory dual-storage structure is used, so that the processing performance of the cloud host is improved, and the user experience is further improved.
Furthermore, the processor of the cloud host searches for target data from the cached first data, so that the data reading speed can be increased, and when the processor fails to search for the target data from the first data, the target data is searched from the second data of the memory, so that the operation speed of the cloud host can be increased, the running stability of the cloud host is guaranteed, and the user experience is improved.
Drawings
Fig. 1 is a schematic flow chart illustrating a cloud host memory allocation method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a cloud host according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the cloud host of FIG. 1 looking up target data;
fig. 4 is a schematic structural diagram of a cloud host memory allocation device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a storage medium according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first", "second" and "third" in this application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any indication of the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. All directional indications (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are only used to explain the relative positional relationship between the components, the movement, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indication is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Fig. 1 is a flowchart illustrating a cloud host memory allocation method according to an embodiment of the present invention. The cloud host memory allocation method can be operated on a local server, a remote server or a remote cloud platform, the local server, the remote server or the remote cloud platform can communicate with a user side through a wireless network such as WIFI or a wired network such as Ethernet, and the user side can be any terminal capable of being operated by a user, such as a mobile phone, a tablet computer, a notebook computer and the like. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 1 if the results are substantially the same. As shown in fig. 1, the method comprises the steps of:
step S101: and acquiring a configuration instruction of a user for applying to create the cloud host.
The user can use a script command, a graphical interface and other modes to send a configuration instruction for creating the cloud host to the server through input equipment such as a mouse and a keyboard at a user side.
Step S102: and acquiring the memory capacity of the cloud host requested by the user according to the configuration instruction.
According to an embodiment of the present invention, a configuration interface may be provided for a user, so that the user may input the configuration instruction specification through the configuration interface, including a configuration value of the memory capacity of the cloud host, and the server may obtain, according to the configuration instruction, the memory capacity of the cloud host that the user applies for.
It should be noted that, in this embodiment, in order to not make too much limitation on the operation of the user, and provide simple and convenient operation while meeting the operation habit of the user, the user may input the memory capacity configuration value configured according to the user requirement through the provided configuration interface, or may not input the specified memory capacity configuration value, so that the memory capacity configuration value is null.
Specifically, if the memory capacity configuration value is not empty, the memory capacity configuration value is used as the memory capacity of the cloud host applied by the user; if the memory capacity configuration value is empty, the memory capacity of the cloud host applied by the user can be obtained according to the number of cpus and the preset memory capacity corresponding to a single cpu. In this embodiment, the preset memory capacity corresponding to a single cpu may be set manually, and a reasonable preset memory capacity may be set according to an application requirement of a user, where the preset memory capacity corresponding to the single cpu is 8G, that is, when the user specifies, through the configuration instruction, that the number of cpus of the cloud host is 1, if the memory capacity configuration value in the configuration instruction input by the user is empty, the memory capacity is considered to be 8G, and when the user specifies, through the configuration instruction, that the number of cpus of the cloud host is 2, if the memory capacity configuration value in the configuration instruction input by the user is empty, the memory capacity is considered to be 16G, and so on.
Step S103: and allocating storage space with corresponding capacity in a nonvolatile memory on a preset server to the cloud host as the memory of the cloud host according to the memory capacity, wherein the nonvolatile memory on the server is a memory adopting a 3D Xpoint storage technology.
In step S103, a nonvolatile memory is installed on the server, the nonvolatile memory may also be installed on another storage device and is in communication connection with the server, and the server allocates a storage space with a corresponding capacity in the nonvolatile memory on a preset server to the cloud host as a memory of the cloud host according to the memory capacity obtained from the configuration instruction or the memory capacity calculated from the configuration instruction.
According to one embodiment of the invention, the non-volatile memory on the server is memory using 3DXpoint storage technology. In this embodiment, the memory adopting the 3D Xpoint storage technology may be an exaggeration non-volatile memory DCPM (data center) persistent memory), which can provide sufficient capacity in a scenario that a large amount of memory is needed for virtualization, and since it has non-volatility, it can save the loading time of data and processes after the server is restarted, and the exaggeration non-volatile memory DCPM has a lower cost compared to a DRAM memory, which can reduce the total cost of the server and the cloud host, and provide sufficient memory, thereby reducing the number of devices, energy consumption, and the like, in particular, the speed and delay difference between a dynamic random access memory and a DRAM SSD is too large for a scenario that the read/write performance is required, and the exaggeration non-volatile memory DCPM can provide a relatively large storage capacity and simultaneously provide a read/write speed and delay close to the DRAM, is incomparable with conventional SSDs.
According to the cloud host memory allocation method, the memory of the 3D Xpoint storage technology is used as the nonvolatile memory on the server, and the memory is allocated to the user as the cloud host memory according to the user configuration instruction, so that the cloud host with high memory reliability, high reading speed and low cost performance can be provided for the user.
Furthermore, when the user does not specify specific memory capacity, the cloud host memory can be allocated to the user according to the number of the cpus and the preset memory capacity corresponding to a single cpu, so that the performance of the cloud host is guaranteed, and the user experience is improved.
In another embodiment, the cloud host memory allocation method further includes the following steps:
step S104: and calculating the cache capacity required by the cloud host according to the memory capacity and a preset proportion.
It should be noted that, according to an embodiment of the present invention, a dynamic random access Memory DRAM is disposed on the server, and the nonvolatile Memory includes multiple storage modes. In the Memory Mode (Memory Mode), the aortan nonvolatile Memory DCPM is recognized by the cloud host system as the DRAM Memory, and the actual DRAM Memory can be used as a cache of the aortan nonvolatile Memory DCPM. The CPU of the cloud host uses a DRAM as a cache and the Pratent non-volatile memory DCPM as a memory.
Specifically, in step S104, the cache capacity required by the cloud host may be calculated according to the memory capacity and a preset ratio, where the preset ratio may be manually set according to the requirement of the application program on the cloud host.
Step S105: and allocating storage space with corresponding capacity in a dynamic random access memory on the preset server to the cloud host according to the cache capacity to serve as the cache of the cloud host.
In step S105, after the cache capacity is calculated, the storage space with the corresponding capacity in the dynamic random access memory DRAM on the server may be allocated to the cloud host as the cache of the cloud host, so that when the CPU of the cloud host reads data, the CPU of the cloud host may search for the data from the dynamic random access memory DRAM first, and when the CPU of the cloud host fails to read the data from the dynamic random access memory DRAM, the CPU of the cloud host searches for the data from the nonvolatile memory.
According to the cloud host memory allocation method, the cache capacity required by the cloud host is calculated according to the memory capacity and the preset proportion, and the cache is allocated to the cloud host, so that the processing performance of the cloud host is improved, and the user experience is further improved.
Furthermore, the CPU of the cloud host may search the data from the dynamic random access memory DRAM, and when the CPU of the cloud host fails to read the data from the dynamic random access memory DRAM, the CPU may search the data from the nonvolatile memory, which may improve the operation speed of the cloud host and improve user experience.
Referring to fig. 2 and fig. 3, fig. 2 is a schematic structural diagram of a cloud host 1 according to an embodiment of the present invention; fig. 3 is a schematic diagram illustrating the cloud host 1 of fig. 1 looking up target data. The application further provides a cloud host 1, which comprises a memory 10 and a processor 11.
The memory 10 is a nonvolatile memory, and the nonvolatile memory is a memory adopting a 3D Xpoint storage technology. In this embodiment, the memory adopting the 3D Xpoint storage technology may be an exaggeration non-volatile memory DCPM (data center) persistent memory), which can provide sufficient capacity in a scenario that a large amount of memory is needed for virtualization, and since it has non-volatility, it can save the loading time of data and processes after the server is restarted, and the exaggeration non-volatile memory DCPM has a lower cost compared to a dynamic random access memory DRAM memory, which can reduce the total cost of the server and the cloud host 1, and provide sufficient memory 10, thereby reducing the number of devices, energy consumption, and the like, in particular, the speed and delay difference between the dynamic random access memory DRAM and the SSD is too large for a scenario that the read/write performance is very high, and the exaggeration non-volatile memory can provide relatively large storage capacity and simultaneously provide read/write speed and delay close to the dynamic random access memory DRAM, is incomparable with conventional SSDs.
The processor 11 reads target data from the memory 10, where the target data is data that needs to be called in the operation process of the cloud host 1.
According to another embodiment of the present invention, the cloud host further includes a cache 12, where the cache 12 is a dynamic random access memory, the cache 12 is used to store first data, and the memory 10 is used to store second data; the Memory 10 using the nonvolatile Memory includes a plurality of storage modes, in this embodiment, the nonvolatile Memory is set to a Memory Mode (Memory Mode), and the Memory Mode (Memory Mode) is mainly applied to a scenario requiring a large-capacity Memory. In the Memory Mode (Memory Mode), the aortan nonvolatile Memory DCPM is recognized by the cloud host system as the DRAM Memory, and the actual DRAM Memory can be used as a cache of the aortan nonvolatile Memory DCPM. The CPU of the cloud host 1 uses a DRAM memory as a cache memory and the uprated nonvolatile memory DCPM as a memory.
The processor 11 searches for target data from the first data in the cache 12, as shown in fig. 3(a), when the processor 11 fails to search for the target data from the first data, the processor 11 searches for the target data from the second data in the memory 10.
According to another embodiment of the present invention, the cloud host further includes a memory manager 13, and when the processor 11 fails to search the target data from the first data, the processor 11 controls the memory manager 13 to search the target data from the second data of the memory 10, and returns the searched target data to the processor 11, as shown in fig. 3 (b).
According to the cloud host 1 provided by the invention, the memory of the 3D Xpoint storage technology is used as the nonvolatile memory on the server and is allocated to the user as the memory 10 of the cloud host 1, so that the cloud host 1 with high reliability, high reading speed, low cost and high cost performance of the memory 10 can be provided for the user.
Furthermore, the DRAM cache 12 is in mixed configuration, so that the processing performance of the cloud host 1 is improved, and the user experience is further improved.
Further, for the target data searched from the first data in the cache 12 by the processor 11 of the cloud host, when the target data searched from the first data by the processor 11 fails, the target data is searched from the second data in the memory 10, so that the operation speed of the cloud host 1 can be increased, and the user experience can be improved.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a cloud host memory allocation apparatus 30 according to an embodiment of the present invention. The cloud host memory allocation device 30 includes a processor 32, a memory 31 coupled to the processor 32, wherein,
the memory 31 has stored therein computer readable instructions which, when executed by the processor 32, carry out the steps of: acquiring a configuration instruction of a user for applying to create a cloud host; acquiring the memory capacity of the cloud host applied by the user according to the configuration instruction; and allocating storage space with corresponding capacity in a nonvolatile memory on a preset server to the cloud host as the memory of the cloud host according to the memory capacity, wherein the nonvolatile memory on the server is a memory adopting a 3D Xpoint storage technology.
In an embodiment, the obtaining, according to the configuration instruction, the memory capacity of the cloud host applied by the user includes: if the memory capacity configuration value is not empty, taking the memory capacity configuration value as the memory capacity of the cloud host applied by the user; and if the memory capacity configuration value is empty, acquiring the memory capacity of the cloud host applied by the user according to the number of the cpus and the preset memory capacity corresponding to the single cpu.
In one embodiment, the cloud host memory allocation method further includes the following steps: calculating the cache capacity required by the cloud host according to the memory capacity and a preset proportion; and allocating storage space with corresponding capacity in a dynamic random access memory on the preset server to the cloud host according to the cache capacity to serve as the cache of the cloud host.
In one embodiment, the non-volatile memory includes a plurality of storage modes, the storage modes include a memory mode, and the cloud host memory allocation method further includes: setting the storage mode of the nonvolatile memory as the memory mode.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a storage medium according to an embodiment of the invention. As shown in fig. 5, a storage medium storing computer readable instructions 41, the computer readable instructions 41, when executed by one or more processors, cause the one or more processors to perform the steps of: acquiring a configuration instruction of a user for applying to create a cloud host; acquiring the memory capacity of the cloud host applied by the user according to the configuration instruction; and allocating storage space with corresponding capacity in a nonvolatile memory on a preset server to the cloud host as the memory of the cloud host according to the memory capacity, wherein the nonvolatile memory on the server is a memory adopting a 3D Xpoint storage technology.
In an embodiment, the obtaining, according to the configuration instruction, the memory capacity of the cloud host applied by the user includes: if the memory capacity configuration value is not empty, taking the memory capacity configuration value as the memory capacity of the cloud host applied by the user; and if the memory capacity configuration value is empty, acquiring the memory capacity of the cloud host applied by the user according to the number of the cpus and the preset memory capacity corresponding to the single cpu.
In one embodiment, the cloud host memory allocation method further includes the following steps: calculating the cache capacity required by the cloud host according to the memory capacity and a preset proportion; and allocating storage space with corresponding capacity in a dynamic random access memory on the preset server to the cloud host according to the cache capacity to serve as the cache of the cloud host.
In one embodiment, the non-volatile memory includes a plurality of storage modes, the storage modes include a memory mode, and the cloud host memory allocation method further includes: setting the storage mode of the nonvolatile memory as the memory mode.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the computer program is executed. The storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A cloud host memory allocation method is characterized by comprising the following steps:
acquiring a configuration instruction of a user for applying to create a cloud host;
acquiring the memory capacity of the cloud host applied by the user according to the configuration instruction; and
and allocating storage space with corresponding capacity in a nonvolatile memory on a preset server to the cloud host as the memory of the cloud host according to the memory capacity, wherein the nonvolatile memory on the server is a memory adopting a 3D Xpoint storage technology.
2. The method according to claim 1, wherein the configuration instruction includes a cpu number and a memory capacity configuration value of the cloud host requested by the user, and the obtaining the memory capacity of the cloud host requested by the user according to the configuration instruction includes:
if the memory capacity configuration value is not empty, taking the memory capacity configuration value as the memory capacity of the cloud host applied by the user;
and if the memory capacity configuration value is empty, acquiring the memory capacity of the cloud host applied by the user according to the number of the cpus and the preset memory capacity corresponding to the single cpu.
3. The method according to claim 1, wherein the method further comprises:
calculating the cache capacity required by the cloud host according to the memory capacity and a preset proportion; and
and allocating storage space with corresponding capacity in a dynamic random access memory on the preset server to the cloud host according to the cache capacity to serve as the cache of the cloud host.
4. The cloud host memory allocation method of claim 1, wherein the non-volatile storage includes a plurality of storage modes, the storage modes including a memory mode, the cloud host memory allocation method further comprising:
setting the storage mode of the nonvolatile memory as the memory mode.
5. The method according to claim 2, wherein the preset memory capacity corresponding to the single cpu is 8G.
6. The cloud host is characterized by comprising a memory, wherein the memory adopts a nonvolatile memory, and the nonvolatile memory adopts a 3D Xpoint storage technology.
7. The cloud host of claim 6, wherein the cloud host further comprises a processor, a cache,
the cache adopts a dynamic random access memory, the cache is used for storing first data, and the memory is used for storing second data;
the processor is configured to search for target data from the cached first data, and when the processor fails to search for the target data from the first data, the processor searches for the target data from the second data in the memory, where the target data is data that needs to be called in an operation process of the cloud host.
8. The cloud host of claim 7, wherein the cloud host further comprises a memory manager, and when the processor fails to search the target data from the first data, the processor controls the memory manager to search the target data from the second data of the memory.
9. A cloud host memory allocation device, comprising a processor, a memory coupled to the processor, wherein,
the memory has stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the cloud host memory allocation method of any of claims 1 to 5.
10. A storage medium storing computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the cloud host memory allocation method of any one of claims 1 to 5.
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| PCT/CN2020/123237 WO2021120843A1 (en) | 2020-07-21 | 2020-10-23 | Cloud host memory allocation method, cloud host, device, and storage medium |
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| CN113569137A (en) * | 2021-07-06 | 2021-10-29 | 北京汇钧科技有限公司 | Recommendation method and device for cloud host specification, storage medium and electronic device |
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| WO2021120843A1 (en) | 2021-06-24 |
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