CN112068954A - Method and system for scheduling network computing resources - Google Patents
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- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/5038—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the execution order of a plurality of tasks, e.g. taking priority or time dependency constraints into consideration
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Abstract
The invention relates to a method and a system for scheduling network computing resources, wherein the method comprises the following steps: acquiring tasks and task sets on at least one client, and performing task scheduling on the tasks and task sets on all the clients to acquire system total task scheduling; according to the arrangement sequence of tasks to be calculated in the system master task scheduling, aiming at each task to be calculated in the system master task scheduling, judging whether each task in the tasks to be calculated is a calculation type with a scale larger than a preset scale or not, and obtaining a judgment result of the task; matching the task with the computer clusters or the personal computing resources in the network according to the judgment results of the task and the task, the pre-acquired information of the hard software environment provided by each computer cluster in the network and the pre-acquired information of the hard software environment provided by each personal computing resource, determining the computer clusters or the personal computing resources matched with the task, and calculating the task by the computer clusters or the personal computing resources matched with the task to acquire the processing result of the task.
Description
Technical Field
The invention relates to the technical field of management of network computing resources, in particular to a method and a system for scheduling network computing resources.
Background
Computer aided design, computer aided engineering simulation and scientific calculation are mainly completed by local resources or network computing resources, and the network computing resources comprise computer clusters specially used for large-scale calculation, and also comprise desktops, small workstations, notebook computers and other mobile office terminals and the like used by engineers personally. In general, small-scale computing tasks are placed on a local computer to complete computing work, and large-scale computing tasks are submitted to a large-scale computing cluster on a network to complete computing work.
However, the traditional network computing resource scheduling method is designed for a medium and large computer cluster at a far end of a network, computing tasks can only be completed on the computer cluster, or computing tasks can only be completed on the medium and large computer cluster fixed on the network, and computing resources used by various design developers in the network, including desktop computers, small workstations, notebook computers and other mobile office terminals, cannot be called. The method has the disadvantages that on one hand, a large number of computing tasks are queued up on a large-medium computer cluster, which wastes time; on the other hand, a large amount of computing resources on the local area network are idle, and resources are wasted.
Disclosure of Invention
Technical problem to be solved
In view of the above disadvantages and shortcomings of the prior art, the present invention provides a method and system for scheduling network computing resources, which solves the technical problem of idle computing resources.
(II) technical scheme
In order to achieve the purpose, the invention adopts the main technical scheme that:
in a first aspect, an embodiment of the present invention provides a method for scheduling network computing resources, including:
s1, acquiring tasks and task sets on at least one client, and performing task scheduling on all the tasks and task sets on the client to acquire the total task scheduling of the system;
the system general task scheduling comprises tasks to be calculated which are sequentially arranged, wherein the tasks to be calculated are one task or a plurality of tasks;
the task set comprises a plurality of tasks, and the tasks comprise information of hardware and software environments required by the tasks;
s2, according to the arrangement sequence of tasks to be calculated in the system overall task schedule, judging whether each task in the tasks to be calculated is a calculation type with a scale larger than a preset scale or not aiming at each task to be calculated in the system overall task schedule, and obtaining a judgment result of the task;
judging whether each task in the tasks to be calculated is a calculation type with a scale larger than a preset scale or not, specifically judging whether each task in the tasks to be calculated is a calculation type which needs to be processed by a processor core with a number larger than or equal to a preset core number or not;
s3, matching the task with the computer clusters or the personal computing resources in the network according to the task, the judgment result of the task, the acquired information of the hard software environment provided by each computer cluster in the network and the acquired information of the hard software environment provided by each personal computing resource, determining the computer clusters or the personal computing resources matched with the task, and calculating the task by the computer clusters or the personal computing resources matched with the task to acquire the processing result of the task.
Preferably, the step S2 specifically includes:
aiming at each task to be calculated in the system total task scheduling, when the task to be calculated is a task, judging whether the task is a calculation type with a scale larger than a preset scale or not, and obtaining a judgment result of the task;
aiming at each task to be calculated in the system total task schedule, when the task to be calculated has a plurality of tasks, sequentially judging whether each task in the task to be calculated is a calculation type with a scale larger than a preset scale according to a preset first sequence, and obtaining a judgment result of each task;
preferably, the step S3 includes:
if the judgment result of the task is a calculation type with a scale larger than a preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, determining the computer cluster matched with the task, and calculating the task by the computer cluster matched with the task to obtain the processing result of the task;
if the judgment result of the task is not the calculation type larger than the preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal calculation resource in the network, determining the personal calculation resource matched with the task, and calculating the task by the personal calculation resource matched with the task to obtain the processing result of the task;
the information of the hard software environment provided by the computer cluster comprises the following information provided by the computer cluster: the method comprises the following steps of (1) counting the CPU core number of a processor, the CPU master frequency of the processor, the RAM space of a memory, the storage space, network communication information and information of software tools installed in a computer cluster;
the information of the hardware and software environment provided by the personal computing resource comprises the following information provided by the personal computing resource: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory, a storage space, network communication information and information of installed software tools of personal computing resources.
Preferably, the step S3 includes:
if the judgment result of the task is a calculation type with a scale larger than a preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, and determining the computer cluster matched with the task;
submitting the task to a computer cluster matched with the task; the computer cluster matched with the task receives the task, and performs task scheduling according to a preset rule aiming at the task and the task received in advance to obtain local task scheduling of the computer cluster;
the local task schedule of the computer cluster comprises the tasks and the tasks which are received in advance and are arranged according to a preset second sequence;
according to the local task scheduling of the computer cluster, the computer cluster drives hardware and software corresponding to the computer cluster to calculate the tasks and the tasks received in advance, and a processing result of each task in the local task scheduling of the computer cluster is obtained;
the processing result of the task comprises: a calculation result of the task or error information of the task.
Preferably, the step S3, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, and determining the computer cluster matched with the task specifically includes:
acquiring a first computer cluster according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network;
the first computer cluster is a computer cluster in which the hardware and software environment information provided in the network meets the hardware and software environment information required in the task;
when the number of the first computer clusters is one, determining that the first computer clusters are the computer clusters matched with the task;
when the number of the first computer clusters is multiple, determining the computer clusters matched with the tasks according to the hardware environment information provided by the first computer clusters;
the hardware environment information provided by the first computer cluster comprises: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory and a storage space.
Preferably, when the number of the first computer clusters is multiple, determining the computer cluster matched with the task according to the hardware environment information provided by the first computer cluster, specifically including:
when the number of the first computer clusters is multiple, acquiring the first computer cluster with the maximum number of CPU cores of the provided processor;
when the number of the first computer clusters with the largest number of CPU cores of the provided processors is one, determining that the first computer clusters with the largest number of CPU cores of the provided processors are the computer clusters matched with the task;
when the number of the first computer clusters with the largest number of the CPU cores of the provided processors is multiple, acquiring a second computer cluster with the highest CPU dominant frequency of the provided processors;
the second computer cluster is the first computer cluster with the largest number of CPU cores of the provided processors;
when the number of the second computer clusters with the highest CPU main frequency of the provided processor is one, determining the second computer clusters with the highest CPU main frequency of the provided processor as the computer clusters matched with the task;
when the number of the second computer clusters with the highest CPU main frequency of the provided processor is multiple, acquiring a third computer cluster with the largest RAM space of the provided memory;
the third computer cluster is a second computer cluster which provides the highest CPU main frequency of the processor;
when the number of the third computer clusters with the maximum provided memory RAM space is one, determining the third computer clusters with the maximum provided memory RAM space as the computer clusters matched with the task;
when the number of the third computer clusters with the largest RAM space of the provided memory is multiple, acquiring a fourth computer cluster with the largest storage space of the provided memory;
the fourth computer cluster is a third computer cluster with the largest space of the provided RAM;
when the number of the fourth computer clusters with the largest provided storage space is one, determining that the fourth computer clusters with the largest provided storage space are the computer clusters matched with the task;
when the number of the fourth computer clusters with the largest provided storage space is multiple, one fourth computer cluster with the largest provided storage space is determined as the computer cluster matched with the task in the fourth computer clusters with the largest provided storage space.
Preferably, the step S3 includes:
if the judgment result of the task is not the calculation type larger than the preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal calculation resource in the network, and determining the personal calculation resource matched with the task;
submitting the task to a personal computing resource that matches the task; receiving the task by the personal computing resource matched with the task, and scheduling the task according to a preset rule aiming at the task and the task received in advance to obtain the local task scheduling of the personal computing resource;
the local task schedule of the personal computing resource comprises the tasks and the tasks received in advance according to a preset third sequence;
according to the local task scheduling of the personal computing resource, the personal computing resource drives hardware and software corresponding to the personal computing resource to calculate the task and the pre-received task, and a processing result of each task in the local task scheduling of the personal computing resource is obtained;
the processing result of the task comprises: a calculation result of the task or error information of the task.
Preferably, the step S3, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal computing resource in the network, and determining the personal computing resource matched with the task specifically includes:
acquiring a first personal computing resource according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal computing resource in the network;
the first personal computing resource is a personal computing resource in a network that meets the hardware and software environment information required in the task;
when the number of the first personal computing resources is one, determining that the first personal computing resources are personal computing resources matched with the task;
when the number of the first personal computing resources is more than one, determining the personal computing resources matched with the task according to the hardware environment information provided by the first personal computing resources;
the hardware environment information provided by the first personal computing resource includes: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory and a storage space.
Preferably, when the number of the first personal computing resources is multiple, determining the personal computing resources matched with the task according to the hardware environment information provided by the first personal computing resources specifically includes:
when the number of the first personal computing resources is multiple, acquiring the first personal computing resources with the maximum number of CPU cores of the provided processor;
when the number of the first personal computing resources with the largest number of the CPU cores of the provided processors is one, determining the first personal computing resources with the largest number of the CPU cores of the provided processors as the personal computing resources matched with the task;
when the number of the first personal computing resources with the largest number of available CPU cores of the processor is multiple, acquiring second personal computing resources providing the highest dominant frequency of the CPU of the processor;
the second personal computing resource is the first personal computing resource which provides the most CPU cores of the processor;
when the number of the second person computing resource providing the highest CPU main frequency of the processor is one, determining the second person computing resource providing the highest CPU main frequency of the processor as the personal computing resource matched with the task;
when the number of the second personal computing resources providing the highest CPU main frequency of the processor is multiple, obtaining the third personal computing resources providing the largest RAM space;
the third personal computing resource is a second personal computing resource which provides the highest CPU dominant frequency of the processor;
when the number of the third personal computing resource with the maximum space of the provided RAM is one, determining that the third personal computing resource with the maximum space of the provided RAM is the personal computing resource matched with the task;
when the number of the third person computing resources with the largest available RAM space is multiple, the fourth person computing resources with the largest storage space are obtained;
the fourth personal computing resource is a third personal computing resource which provides the largest RAM space;
when the number of the fourth personal computing resource with the largest storage space is one, determining that the fourth personal computing resource with the largest storage space is the personal computing resource matched with the task;
and when the number of the fourth person computing resources providing the largest storage space is more than one, determining one fourth person computing resource providing the largest storage space as the personal computing resource matched with the task according to the fourth person computing resource providing the largest storage space.
On the other hand, this embodiment further provides a system for scheduling network computing resources, including:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein the memory stores program instructions executable by the processor to invoke a method by which the program instructions are capable of performing any of the above described network computing resource scheduling methods.
(III) advantageous effects
The invention has the beneficial effects that: the invention relates to a method for scheduling network computing resources, which receives tasks and task sets input by each client on one hand, and then schedules the tasks, namely the system total task scheduling based on tasks input by users; on the other hand, the hardware and software environment of each computing resource is detected, and the hardware and software environment is matched and compared with the current task sent by the overall task scheduling system, so that compared with the prior art, the network computing resource scheduling method can achieve balanced utilization of all computing resource loads in a network system, and achieve maximization of utilization efficiency.
Drawings
FIG. 1 is a flow chart of a method for network computing resource scheduling in accordance with the present invention;
FIG. 2 is a diagram illustrating a method for scheduling network computing resources according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating task scheduling in a method for scheduling network computing resources according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating task matching in a method for scheduling network computing resources according to an embodiment of the present invention.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
In order to better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Referring to fig. 1 and fig. 2, the present embodiment provides a method for scheduling network computing resources, including:
and S1, acquiring tasks and task sets on at least one client, and performing task scheduling on all the tasks and task sets on the client according to a preset rule to acquire the total task scheduling of the system.
The system general task scheduling comprises tasks to be calculated which are arranged in sequence.
The task to be calculated is one task or a plurality of tasks.
The task set includes a plurality of tasks.
The tasks include information of the hardware and software environment required for computing the tasks.
The client in this embodiment includes: intelligent terminal equipment such as personal workstations, notebook computers, mobile phones and the like.
Boundary of task in this embodiment: including input conditions and output result definitions.
Task set in this embodiment: and arranging the tasks into a serial task set, a parallel task set or a serial-parallel mixed task set according to a certain logic sequence.
In this embodiment, task scheduling is performed on all the tasks and task sets on the client according to a preset rule to obtain a system total task schedule, and the system total task schedule may be obtained by scheduling all the tasks and task sets on the client according to a preset logical relationship, such as a time sequence, a priority sequence, and the like.
S2, according to the arrangement sequence of the tasks to be calculated in the system total task schedule, judging whether each task in the tasks to be calculated is a calculation type larger than a preset scale or not aiming at each task to be calculated in the system total task schedule, and obtaining the judgment result of the tasks.
The method comprises the steps of judging whether each task in the tasks to be calculated is a calculation type with a scale larger than a preset scale or not, and specifically judging whether each task in the tasks to be calculated is a calculation type which needs to be processed by a processor core with a number larger than or equal to a preset core number or not.
For example, if the preset scale calculation type is a calculation type in which the preset number of cores is 64, it is determined whether each task in the tasks to be calculated is a calculation type larger than the preset scale, specifically, it is determined whether the task needs a processor core with a number of 64 cores or more than 64 cores for processing, and if the minimum number of processor cores needed by the task is larger than or equal to 64 cores, the system may define that the task is a calculation type larger than the preset scale; in this embodiment, the number of processor cores required by the calculation type with the preset scale is not limited, that is, if the preset scale calculation type is a calculation type in which the preset number of cores is 128 cores, it is determined whether each task in the tasks to be calculated is a calculation type with a larger scale than the preset scale, specifically, it is determined whether the task needs 128 cores or more than 128 cores for processing, and if the minimum number of processor cores required by the task is larger than or equal to 128 cores, the system may define that the task is a calculation type with a larger scale than the preset scale.
In this embodiment, the task to be calculated may be a single task; in this embodiment, the task to be calculated may also be a plurality of tasks satisfying parallel processing.
S3, matching the task with the computer clusters or the personal computing resources in the network according to the task, the judgment result of the task, the pre-acquired information of the hard software environment provided by each computer cluster in the network and the pre-acquired information of the hard software environment provided by each personal computing resource, determining the computer clusters or the personal computing resources matched with the task, and calculating the task by the computer clusters or the personal computing resources matched with the task to acquire the processing result of the task.
Preferably, the step S2 specifically includes:
and aiming at each task to be calculated in the system total task scheduling, when the task to be calculated is one task, judging whether the task is a calculation type with a scale larger than a preset scale, and acquiring a task judgment result.
Aiming at each task to be calculated in the system total task schedule, when the task to be calculated has a plurality of tasks, sequentially judging whether each task in the task to be calculated is a calculation type with a scale larger than a preset scale according to a preset first sequence, and obtaining a judgment result of each task.
The preset first order in this embodiment is the default specified order.
Preferably, the first and second liquid crystal materials are,
the information of the hard software environment provided by the computer cluster comprises the following information provided by the computer cluster: the system comprises a CPU core number of a processor, a CPU master frequency of the processor, a RAM space of a memory, a storage space, network communication information and information of software tools installed in a computer cluster.
The information of the hardware and software environment provided by the personal computing resource comprises the following information provided by the personal computing resource: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory, a storage space, network communication information and information of installed software tools of personal computing resources.
Preferably, the step S3 includes:
and if the judgment result of the task is the calculation type with the scale larger than the preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, and determining the computer cluster matched with the task.
In this embodiment, the personal computing resources in the network and the software types and hardware performances included in the computer cluster are different, and the tasks submitted by the user are more various, as shown in fig. 4, by detecting the hardware and software environments of each computing resource and performing matching comparison with the current task sent by the overall task scheduling system, if matching is successful, the computing resource is used as one of the task and the candidate computing resource, and then the upper software automatically driving the computing resource performs solution calculation on the task received in the local computer.
Submitting the task to a computer cluster matched with the task; and the computer cluster matched with the task receives the task, and performs task scheduling according to a preset rule aiming at the task and the task received in advance to obtain the local task scheduling of the computer cluster.
Referring to fig. 3, in this embodiment, not only tasks submitted by all users and task sets are scheduled, but also tasks received by a computer cluster in a network are scheduled, so that the local task scheduling of the computer cluster and the overall system scheduling system are unified, and thus, the load of all computing resources in the network system is utilized in a balanced manner, and the utilization efficiency is maximized.
The local task schedule of the computer cluster comprises the tasks and the pre-received tasks arranged according to a preset second sequence.
And driving hardware and software corresponding to the computer cluster to calculate the tasks and the tasks received in advance by the computer cluster according to the local task scheduling of the computer cluster, and acquiring a processing result of each task in the local task scheduling of the computer cluster.
The processing result of the task comprises: a calculation result of the task or error information of the task.
In this embodiment, the tasks received by the computer cluster in the network are arranged according to a preset second sequence, the hardware and software corresponding to the computing resource are sequentially driven, the computing task is successively completed, and when the solution fails, the error information corresponding to the task is returned. And the calculation result or the error information is stored in a file server designated by the user, and corresponding feedback information is sent back to the client.
Preferably, the step S3, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, and determining the computer cluster matched with the task specifically includes:
and acquiring a first computer cluster according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network.
The first computer cluster is a computer cluster in which the hardware and software environment information provided in the network meets the hardware and software environment information required in the task.
When the number of the first computer clusters is one, determining that the first computer cluster is a computer cluster matched with the task.
And when the number of the first computer clusters is multiple, determining the computer clusters matched with the task according to the hardware environment information provided by the first computer clusters.
The hardware environment information provided by the first computer cluster comprises: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory and a storage space.
Preferably, when the number of the first computer clusters is multiple, determining the computer cluster matched with the task according to the hardware environment information provided by the first computer cluster, specifically including:
and when the number of the first computer clusters is multiple, acquiring the first computer cluster with the maximum number of the CPU cores of the provided processors.
When the number of the first computer clusters with the largest number of CPU cores of the provided processors is one, determining that the first computer clusters with the largest number of CPU cores of the provided processors are the computer clusters matched with the task.
And when the number of the first computer clusters with the largest number of the cores of the provided CPU is multiple, acquiring a second computer cluster with the highest main frequency of the provided CPU.
The second computer cluster is the first computer cluster with the largest number of CPU cores of the provided processors.
And when the number of the second computer clusters with the highest CPU main frequency of the provided processor is one, determining the second computer clusters with the highest CPU main frequency of the provided processor as the computer clusters matched with the task.
And when the number of the second computer clusters with the highest CPU main frequency of the provided processor is multiple, acquiring a third computer cluster with the largest space of the provided memory RAM.
And the third computer cluster is a second computer cluster providing the highest CPU main frequency of the processor.
And when the number of the third computer clusters with the maximum provided memory RAM space is one, determining the third computer clusters with the maximum provided memory RAM space as the computer clusters matched with the task.
And when the number of the third computer clusters with the maximum space of the provided memory RAM is multiple, acquiring a fourth computer cluster with the maximum space of the provided memory RAM.
The fourth computer cluster is a third computer cluster with the largest provided memory RAM space.
When the number of the fourth computer clusters with the largest provided storage space is one, determining that the fourth computer clusters with the largest provided storage space are the computer clusters matched with the task.
When the number of the fourth computer clusters with the largest provided storage space is multiple, one fourth computer cluster with the largest provided storage space is determined as the computer cluster matched with the task in the fourth computer clusters with the largest provided storage space.
Preferably, the step S3 includes:
and if the judgment result is that the calculation type is not larger than the preset scale, matching the task according to the hardware and software environment information required by the task and the hardware and software environment information provided by each personal calculation resource in the network, and determining the personal calculation resource matched with the task.
In this embodiment, the personal computing resources in the network and the software types and hardware performances included in the computer cluster are different, and the tasks submitted by the users are more various, as shown in fig. 4. By detecting the hardware and software environment of each computing resource, matching and comparing the hardware and software environment with the current task sent by the overall task scheduling system, if the matching is successful, the computing resource is taken as one of the task and the candidate computing resource, and then the upper software of the computing resource is automatically driven to solve and calculate the task received in the computer.
Submitting the task to a personal computing resource that matches the task; and the personal computing resource matched with the task receives the task, and performs task scheduling according to a preset rule aiming at the task and the task received in advance to obtain local task scheduling of the personal computing resource.
Referring to fig. 3, in this embodiment, not only tasks submitted by all users and task sets are scheduled, but also tasks received by personal computing resources in a network are scheduled, so that the local task scheduling of the personal computing resources and the system master scheduling system are unified, and thus, the load of all computing resources in the network system is utilized in a balanced manner, and the utilization efficiency is maximized.
The local task schedule of the personal computing resource includes the tasks and the pre-received tasks arranged in a predetermined third order.
And according to the local task scheduling of the personal computing resource, the personal computing resource drives hardware and software corresponding to the personal computing resource to calculate the task and the pre-received task, and a processing result of each task in the local task scheduling of the personal computing resource is obtained.
The processing result of the task comprises: a calculation result of the task or error information of the task.
In this embodiment, the hardware and software corresponding to the computing resource are sequentially driven according to a preset third sequence order of the tasks received by the personal computing resource in the network, the computing task is successively completed, and when the solution fails, the error information corresponding to the task is returned. And the calculation result or the error information is stored in a file server designated by the user, and corresponding feedback information is sent back to the client.
Preferably, the step S3, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal computing resource in the network, and determining the personal computing resource matched with the task specifically includes:
and acquiring the first personal computing resource according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal computing resource in the network.
The first personal computing resource is a personal computing resource in a network that satisfies the hardware and software environment information required in the task.
When the number of first personal computing resources is one, determining that the first personal computing resources are personal computing resources matched with the task.
And when the number of the first personal computing resources is more than one, determining the personal computing resources matched with the task according to the hardware environment information provided by the first personal computing resources.
The hardware environment information provided by the first personal computing resource includes: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory and a storage space.
Preferably, when the number of the first personal computing resources is multiple, determining the personal computing resources matched with the task according to the hardware environment information provided by the first personal computing resources specifically includes:
when the number of the first personal computing resources is multiple, the first personal computing resource with the largest number of the provided CPU cores is obtained.
When the number of the first personal computing resources with the largest number of the provided processor CPU cores is one, determining the first personal computing resources with the largest number of the provided processor CPU cores as the personal computing resources matched with the task.
When the number of the first personal computing resources with the largest number of available CPU cores is multiple, the second personal computing resources with the highest dominant frequency of the CPU are obtained.
The second personal computing resource is the first personal computing resource that provides the most number of processor CPU cores.
And when the number of the second personal computing resource providing the highest CPU main frequency of the processor is one, determining that the second personal computing resource providing the highest CPU main frequency of the processor is the personal computing resource matched with the task.
And when the number of the second personal computing resources providing the highest CPU main frequency of the processor is multiple, acquiring the third personal computing resources providing the largest RAM space.
The third personal computing resource is the second personal computing resource which provides the highest main frequency of the CPU of the processor.
And when the number of the third personal computing resource with the maximum provided memory RAM space is one, determining that the third personal computing resource with the maximum provided memory RAM space is the personal computing resource matched with the task.
And when the number of the third personal computing resources with the largest available memory RAM space is more than one, acquiring the fourth personal computing resources with the largest storage space.
The fourth human computing resource provides a third human computing resource with the largest RAM space.
When the number of the fourth personal computing resource providing the largest storage space is one, determining the fourth personal computing resource providing the largest storage space as the personal computing resource matched with the task.
And when the number of the fourth person computing resources providing the largest storage space is more than one, determining one fourth person computing resource providing the largest storage space as the personal computing resource matched with the task according to the fourth person computing resource providing the largest storage space.
The embodiment automatically allocates the computing tasks submitted by the users to the available computing resources on the network, completes the solving tasks and the result calling, and realizes the maximization of the utilization of the network computing resources.
In the embodiment, not only are tasks submitted by all users and tasks of a task set scheduled, but also tasks of the computer clusters in the network are scheduled, so that the local task scheduling of the computer clusters and the overall scheduling system of the system are unified, the load of all computing resources in the network system is utilized in a balanced manner, and the utilization efficiency is maximized.
In the embodiment, all the engineering design software, scientific computing software, data analysis software, physical and chemical simulation software, office document software and other software supporting scripts can be driven.
On the other hand, this embodiment further provides a system for scheduling network computing resources, including:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein the memory stores program instructions executable by the processor to invoke a method by which the program instructions are capable of performing any of the above described network computing resource scheduling methods.
Since the system described in the above embodiment of the present invention is a system used for implementing the method of the above embodiment of the present invention, a person skilled in the art can understand the specific structure and the modification of the system based on the method described in the above embodiment of the present invention, and thus the detailed description is omitted here. All systems adopted by the method of the above embodiments of the present invention are within the intended scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third and the like are for convenience only and do not denote any order. These words are to be understood as part of the name of the component.
Furthermore, it should be noted that in the description of the present specification, the description of the term "one embodiment", "some embodiments", "examples", "specific examples" or "some examples", etc., means that a specific feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, the claims should be construed to include preferred embodiments and all changes and modifications that fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include such modifications and variations.
Claims (10)
1. A method for network computing resource scheduling, comprising:
s1, acquiring tasks and task sets on at least one client, and performing task scheduling on all the tasks and task sets on the client to acquire the total task scheduling of the system;
the system general task scheduling comprises tasks to be calculated which are sequentially arranged, wherein the tasks to be calculated are one task or a plurality of tasks;
the task set comprises a plurality of tasks, and the tasks comprise information of hardware and software environments required by the tasks;
s2, according to the arrangement sequence of tasks to be calculated in the system overall task schedule, judging whether each task in the tasks to be calculated is a calculation type larger than a preset scale or not aiming at each task to be calculated in the system overall task schedule, and obtaining a judgment result of the tasks;
s3, matching the task with the computer clusters or the personal computing resources in the network according to the task, the judgment result of the task, the acquired information of the hard software environment provided by each computer cluster in the network and the acquired information of the hard software environment provided by each personal computing resource, determining the computer clusters or the personal computing resources matched with the task, and calculating the task by the computer clusters or the personal computing resources matched with the task to acquire the processing result of the task.
2. The method according to claim 1, wherein the step S2 specifically includes:
aiming at each task to be calculated in the system total task scheduling, when the task to be calculated is a task, judging whether the task is a calculation type with a scale larger than a preset scale or not, and obtaining a judgment result of the task;
aiming at each task to be calculated in the system total task schedule, when the task to be calculated has a plurality of tasks, sequentially judging whether each task in the task to be calculated is a calculation type with a scale larger than a preset scale according to a preset first sequence, and obtaining a judgment result of each task.
3. The method according to claim 2, wherein the step S3 includes:
if the judgment result of the task is a calculation type with a scale larger than a preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, determining the computer cluster matched with the task, and calculating the task by the computer cluster matched with the task to obtain the processing result of the task;
if the judgment result of the task is not the calculation type larger than the preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal calculation resource in the network, determining the personal calculation resource matched with the task, and calculating the task by the personal calculation resource matched with the task to obtain the processing result of the task;
the information of the hard software environment provided by the computer cluster comprises the following information provided by the computer cluster: the method comprises the following steps of (1) counting the CPU core number of a processor, the CPU master frequency of the processor, the RAM space of a memory, the storage space, network communication information and information of software tools installed in a computer cluster;
the information of the hardware and software environment provided by the personal computing resource comprises the following information provided by the personal computing resource: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory, a storage space, network communication information and information of installed software tools of personal computing resources.
4. The method according to claim 3, wherein the step S3 includes:
if the judgment result of the task is a calculation type with a scale larger than a preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, and determining the computer cluster matched with the task;
submitting the task to a computer cluster matched with the task; the computer cluster matched with the task receives the task, and performs task scheduling according to a preset rule aiming at the task and the task received in advance to obtain local task scheduling of the computer cluster;
the local task schedule of the computer cluster comprises the tasks and the tasks which are received in advance and are arranged according to a preset second sequence;
according to the local task scheduling of the computer cluster, the computer cluster drives hardware and software corresponding to the computer cluster to calculate the tasks and the tasks received in advance, and a processing result of each task in the local task scheduling of the computer cluster is obtained;
the processing result of the task comprises: a calculation result of the task or error information of the task.
5. The method according to claim 4, wherein the step S3 of matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network, and determining the computer cluster matching the task specifically includes:
acquiring a first computer cluster according to the hardware and software environment information required in the task and the hardware and software environment information provided by each computer cluster in the network;
the first computer cluster is a computer cluster in which the hardware and software environment information provided in the network meets the hardware and software environment information required in the task;
when the number of the first computer clusters is one, determining that the first computer clusters are the computer clusters matched with the task;
when the number of the first computer clusters is multiple, determining the computer clusters matched with the tasks according to the hardware environment information provided by the first computer clusters;
the hardware environment information provided by the first computer cluster comprises: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory and a storage space.
6. The method according to claim 5, wherein when the number of the first computer clusters is multiple, determining the computer cluster matched with the task according to the hardware environment information provided by the first computer cluster specifically comprises:
when the number of the first computer clusters is multiple, acquiring the first computer cluster with the maximum number of CPU cores of the provided processor;
when the number of the first computer clusters with the largest number of CPU cores of the provided processors is one, determining that the first computer clusters with the largest number of CPU cores of the provided processors are the computer clusters matched with the task;
when the number of the first computer clusters with the largest number of the CPU cores of the provided processors is multiple, acquiring a second computer cluster with the highest CPU dominant frequency of the provided processors;
the second computer cluster is the first computer cluster with the largest number of CPU cores of the provided processors;
when the number of the second computer clusters with the highest CPU main frequency of the provided processor is one, determining the second computer clusters with the highest CPU main frequency of the provided processor as the computer clusters matched with the task;
when the number of the second computer clusters with the highest CPU main frequency of the provided processor is multiple, acquiring a third computer cluster with the largest RAM space of the provided memory;
the third computer cluster is a second computer cluster which provides the highest CPU main frequency of the processor;
when the number of the third computer clusters with the maximum provided memory RAM space is one, determining the third computer clusters with the maximum provided memory RAM space as the computer clusters matched with the task;
when the number of the third computer clusters with the largest RAM space of the provided memory is multiple, acquiring a fourth computer cluster with the largest storage space of the provided memory;
the fourth computer cluster is a third computer cluster with the largest space of the provided RAM;
when the number of the fourth computer clusters with the largest provided storage space is one, determining that the fourth computer clusters with the largest provided storage space are the computer clusters matched with the task;
when the number of the fourth computer clusters with the largest provided storage space is multiple, one fourth computer cluster with the largest provided storage space is determined as the computer cluster matched with the task in the fourth computer clusters with the largest provided storage space.
7. The method according to claim 6, wherein the step S3 includes:
if the judgment result of the task is not the calculation type larger than the preset scale, matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal calculation resource in the network, and determining the personal calculation resource matched with the task;
submitting the task to a personal computing resource that matches the task; receiving the task by the personal computing resource matched with the task, and scheduling the task according to a preset rule aiming at the task and the task received in advance to obtain the local task scheduling of the personal computing resource;
the local task schedule of the personal computing resource comprises the tasks and the tasks received in advance according to a preset third sequence;
according to the local task scheduling of the personal computing resource, the personal computing resource drives hardware and software corresponding to the personal computing resource to calculate the task and the pre-received task, and a processing result of each task in the local task scheduling of the personal computing resource is obtained;
the processing result of the task comprises: a calculation result of the task or error information of the task.
8. The method according to claim 7, wherein the step S3 of matching the task according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal computing resource in the network, and determining the personal computing resource matching the task specifically includes:
acquiring a first personal computing resource according to the hardware and software environment information required in the task and the hardware and software environment information provided by each personal computing resource in the network;
the first personal computing resource is a personal computing resource in a network that meets the hardware and software environment information required in the task;
when the number of the first personal computing resources is one, determining that the first personal computing resources are personal computing resources matched with the task;
when the number of the first personal computing resources is more than one, determining the personal computing resources matched with the task according to the hardware environment information provided by the first personal computing resources;
the hardware environment information provided by the first personal computing resource includes: the system comprises a CPU core number of a processor, a CPU main frequency of the processor, a RAM space of a memory and a storage space.
9. The method according to claim 8, wherein when the number of the first personal computing resources is plural, determining the personal computing resource matching the task according to the hardware environment information provided by the first personal computing resource comprises:
when the number of the first personal computing resources is multiple, acquiring the first personal computing resources with the maximum number of CPU cores of the provided processor;
when the number of the first personal computing resources with the largest number of the CPU cores of the provided processors is one, determining the first personal computing resources with the largest number of the CPU cores of the provided processors as the personal computing resources matched with the task;
when the number of the first personal computing resources with the largest number of available CPU cores of the processor is multiple, acquiring second personal computing resources providing the highest dominant frequency of the CPU of the processor;
the second personal computing resource is the first personal computing resource which provides the most CPU cores of the processor;
when the number of the second person computing resource providing the highest CPU main frequency of the processor is one, determining the second person computing resource providing the highest CPU main frequency of the processor as the personal computing resource matched with the task;
when the number of the second personal computing resources providing the highest CPU main frequency of the processor is multiple, obtaining the third personal computing resources providing the largest RAM space;
the third personal computing resource is a second personal computing resource which provides the highest CPU dominant frequency of the processor;
when the number of the third personal computing resource with the maximum space of the provided RAM is one, determining that the third personal computing resource with the maximum space of the provided RAM is the personal computing resource matched with the task;
when the number of the third person computing resources with the largest available RAM space is multiple, the fourth person computing resources with the largest storage space are obtained;
the fourth personal computing resource is a third personal computing resource which provides the largest RAM space;
when the number of the fourth personal computing resource with the largest storage space is one, determining that the fourth personal computing resource with the largest storage space is the personal computing resource matched with the task;
and when the number of the fourth person computing resources providing the largest storage space is more than one, determining one fourth person computing resource providing the largest storage space as the personal computing resource matched with the task according to the fourth person computing resource providing the largest storage space.
10. A system for network computing resource scheduling, comprising:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein the memory stores program instructions executable by the processor to invoke the method by which the program instructions are capable of performing the network computing resource scheduling of any of claims 1 to 9.
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