A control method and follow-up control device for a quantum and electronic hybrid computing power network

Abstract

The present invention discloses a control method and a follow-up control device for a quantum and electronic hybrid computing power network, which are applied to the technical field of computing power network, including determining the connection span of nodes based on the layers corresponding to each node of the hybrid computing power network topology structure; determining key nodes based on the connection spans of nodes belonging to the same layer; generating alternative strategy trees based on the blocks corresponding to each node in the hybrid computing power network topology structure and key nodes; determining the optimal strategy tree from the alternative strategy tree through an entropy measurement model and algorithm, and using the corresponding node determined by the optimal strategy tree as a control node; controlling the control node to perform hierarchical and block control on the target hybrid computing power network, realizing control of a small number of nodes to affect each node of the hybrid computing power network, and obtaining sufficient condition control for local synchronization of the load network. The follow-up control device is a software system embedded in the control node, which plays the role of the software system acting as hardware.

Description

Technical Field

[0001] The present invention relates to the field of computing power network technology, and in particular to a control method for a quantum and electronic hybrid computing power network, a follow-up control device for a quantum and electronic hybrid computing power network, a control device for a quantum and electronic hybrid computing power network, and a computer-readable storage medium. Background Art

[0002] The configuration of hybrid computing nodes based on quantum and electronic computers is a new computing network architecture problem. At present, the technology of "hybrid control" is still immature. It is necessary to open up a new technical path for the selection of computing nodes based on quantum and electronic hybrid computing networks. Faced with complex computing network systems, there are a large number of nodes in the corresponding computing network topology, such as quantum computer clusters and electronic computer clusters. Therefore, it is difficult to apply a controller to each node in the computing network. Therefore, how to achieve global control of the hybrid computing network is an urgent problem that technicians in this field need to solve. Summary of the invention

[0003] The purpose of the present invention is to provide a control method of a quantum and electronic hybrid computing power network, which can realize global control of the computing power network; another purpose of the present invention is to provide a follow-up control device of a quantum and electronic hybrid computing power network, a control device of a quantum and electronic hybrid computing power network, and a computer-readable storage medium. Global control of the computing power network can be realized.

[0004] In order to solve the above technical problems, the present invention provides a control method for a quantum and electronic hybrid computing power network, comprising:

[0005] Obtain the topological structure of the target hybrid computing network;

[0006] Determine the connection span of the nodes in the target hybrid computing network, and determine the key nodes from the nodes belonging to the same layer according to the connection span based on the layer corresponding to each node in the topological structure;

[0007] Generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes;

[0008] Determine an optimal strategy tree from the candidate strategy trees by using an entropy measurement model and algorithm, and use the corresponding node determined by the optimal strategy tree as a control node;

[0009] The control node is controlled according to the controller to globally control the target hybrid computing power network.

[0010] Optionally, the determining of the connection span of the nodes in the target hybrid computing power network, based on the layer corresponding to each node in the topological structure, and determining the key nodes from the nodes belonging to the same layer according to the connection span includes:

[0011] Determining the connection span of nodes in the target hybrid computing power network;

[0012] Based on the layers corresponding to the nodes in the topological structure, the node with the largest connection span among the nodes belonging to the same layer is selected as the key node.

[0013] Optionally, obtaining the topological structure of the target hybrid computing power network includes:

[0014] The target hybrid computing power network is scanned to obtain a label of each node in the target hybrid computing power network; the label is used to characterize that the corresponding node is a quantum computer node or an electronic computer node.

[0015] Optionally, before generating the candidate strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes, the method further includes:

[0016] The target hybrid computing power network is divided based on the label to determine the block corresponding to each node.

[0017] Optionally, controlling the control node according to the controller to control the target hybrid computing power network includes:

[0018] The control node is monitored according to the controller, and a node with computing power overflow in the target hybrid computing power network is determined based on the label.

[0019] Optionally, controlling the control node according to the controller to globally control the target hybrid computing power network includes:

[0020] The control node is controlled according to the controller, and the tasks corresponding to the node with overflowed computing power are migrated to the target node based on the label.

[0021] Optionally, determining the optimal strategy tree from the candidate strategy trees by using an entropy measurement model and an algorithm, and using the corresponding node determined by the optimal strategy tree as a control node includes:

[0022] Determining the total number of quality microstates of the alternative strategy tree;

[0023] Determine the quality microstate realization probability value of the alternative strategy tree according to the total number of quality microstates;

[0024] Determining the quality entropy of the alternative strategy tree according to the quality microstate realization probability value;

[0025] Determine the total mass entropy of the target hybrid computing power network according to the mass entropy;

[0026] Determining the quality of the candidate strategy tree according to the total quality entropy;

[0027] The candidate strategy tree corresponding to the maximum quality is determined from the qualities as the optimal strategy tree, and the corresponding node determined by the optimal strategy tree is used as the control node.

[0028] The present invention also provides a control device for a quantum and electronic hybrid computing power network, comprising:

[0029] A topology acquisition module is used to obtain the topology of the target hybrid computing network;

[0030] A key node determination module, used to determine the connection span of nodes in the target hybrid computing network, based on the layer corresponding to each node in the topological structure, and determine the key nodes from the nodes belonging to the same layer according to the connection span;

[0031] A strategy tree generation module, used to generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes;

[0032] A control node selection module is used to determine the optimal strategy tree from the candidate strategy trees through an entropy measurement model and an algorithm, and use the corresponding node determined by the optimal strategy tree as the control node;

[0033] A controller embedded module is used to control the control node according to the controller to control the target hybrid computing power network.

[0034] The present invention also provides a control device for a quantum and electronic hybrid computing power network, the device comprising:

[0035] Memory: used to store computer programs;

[0036] Processor: used to implement the steps of the control method of the quantum and electronic hybrid computing power network as described in any of the above items when executing the computer program.

[0037] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the control method of the quantum and electronic hybrid computing power network as described in any of the above items are implemented.

[0038] A control method for a quantum and electronic hybrid computing power network provided by the present invention comprises: obtaining a topological structure of a target hybrid computing power network; determining a connection span of nodes in the target hybrid computing power network, and determining key nodes from nodes belonging to the same layer according to the connection span based on the layer corresponding to each node in the topological structure; generating an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes; determining an optimal strategy tree from the alternative strategy trees through an entropy measurement model and algorithm, and using the corresponding node determined by the optimal strategy tree as a control node; and controlling the control node according to a controller to globally control the target hybrid computing power network.

[0039] First, the target hybrid computing power network is divided into layers and blocks, and the key nodes of each layer in the layered structure are determined based on the connection span, so that the nodes with higher importance in the same layer can be determined; then, a strategy tree spanning each block is generated based on the block structure, so that the strategy tree is the backbone path in the communication path of the entire hybrid computing power network; thus, the control node finally determined based on the entropy measurement model and algorithm has a very high radiation range, and the control node can affect each node of the entire target hybrid computing power network. Based on the global control of the control node, each node in the entire target hybrid computing power network can be controlled, and a single linear control can be applied to a small number of nodes in the target hybrid computing power network, so as to obtain sufficient condition control to ensure local synchronization or feedback control of the complex network.

[0040] Another object of the present invention is to provide a control device for a quantum and electronic hybrid computing power network, a control equipment for a quantum and electronic hybrid computing power network, and a computer-readable storage medium, which also have the above-mentioned beneficial effects and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A flow chart of a control method for a quantum and electronic hybrid computing power network provided by an embodiment of the present invention;

[0043] Figure 2 A flowchart of a specific method for controlling a quantum and electronic hybrid computing power network provided by an embodiment of the present invention;

[0044] Figure 3A flowchart of another specific method for controlling a quantum and electronic hybrid computing power network provided by an embodiment of the present invention;

[0045] Figure 4 It is a schematic diagram of the topological structure of a specific target hybrid computing network;

[0046] Figure 5 A structural block diagram of a control device for a quantum and electronic hybrid computing network provided by an embodiment of the present invention;

[0047] Figure 6 A block diagram of the control device structure of a quantum and electronic hybrid computing power network provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The core of the present invention is to provide a control method and a follow-up control device for a quantum and electronic hybrid computing power network. In the prior art, facing a complex computing power network system, there are a large number of nodes in the corresponding computing power network topology, such as a quantum computer cluster and an electronic computer cluster. Therefore, it is difficult to apply a controller to each node in the computing power network.

[0049] The present invention provides a control method for a quantum and electronic hybrid computing power network, comprising: obtaining a topological structure of a target hybrid computing power network; determining the connection span of nodes in the target hybrid computing power network, and determining key nodes from nodes belonging to the same layer according to the connection span based on the layer corresponding to each node in the topological structure; generating an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes; determining an optimal strategy tree from the alternative strategy trees through an entropy measurement model and algorithm, and using the corresponding node determined by the optimal strategy tree as a control node; and controlling the control node according to a controller to globally control the target hybrid computing power network.

[0050] First, the target hybrid computing power network is divided into layers and blocks, and the key nodes of each layer in the layered structure are determined based on the connection span, so that the nodes with higher importance in the same layer can be determined; then, a strategy tree spanning each block is generated based on the block structure, so that the strategy tree is the backbone path in the communication path of the entire hybrid computing power network; thus, the control node finally determined based on the entropy measurement model and algorithm has a very high radiation range, and the control node can affect each node of the entire target hybrid computing power network. Based on the global control of the control node, each node in the entire target hybrid computing power network can be controlled, and a single linear control can be applied to a small number of nodes in the target hybrid computing power network, so as to obtain sufficient condition control to ensure local synchronization or feedback control of the complex network.

[0051] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0052] Please refer to Figure 1 , Figure 1 A flowchart of a control method for a quantum and electronic hybrid computing power network provided in an embodiment of the present invention.

[0053] See also Figure 1 In an embodiment of the present invention, a control method of a quantum and electronic hybrid computing power network includes:

[0054] S101: Obtain the topological structure of the target hybrid computing power network.

[0055] In the dynamic operation of complex network systems, various factors interact intricately, and it is difficult to derive the precise rules of system changes and give a hybrid group control mechanism for computing nodes with a computing network topology. Group control refers to the control of sufficient conditions for ensuring local synchronization of complex networks by applying a single linear control to a node in the network. Hybrid group control refers to the group control of computing nodes in a computing network that has both quantum computer computing nodes and electronic computer computing nodes. In order to reduce the number of controllers, applying a single linear control to a node in a complex network will obtain sufficient conditions for ensuring local synchronization control of the computing network. In other words, only a small number of nodes in the computing network called control nodes need to be subject to local linear feedback control to achieve hybrid control of computing nodes in the entire network, and ultimately achieve hybrid control based on the feedback control mechanism to manipulate hybrid computing nodes based on quantum computers and electronic computers in the computing network. The follow-up control device is a software system that is embedded in the control node to transform a physical system into a processor from the software perspective, playing the role of the software system acting as hardware.

[0056] In order to achieve hybrid group control of the target hybrid computing network, in this step, the target hybrid computing network can be searched to obtain information about each node in the target hybrid computing network to obtain the topology of the target hybrid computing network. In subsequent steps, the control node will be calculated based on the above topology.

[0057] The hybrid computing network based on quantum and electronic nodes is a complex network system. The complex network system can usually be regarded as a layered and block system. Its bottom-level tasks are relatively fixed, and the upper-level tasks are relatively flexible; at each layer, the tasks and subsystems or modules, that is, the nodes have interactive relationships or interactions. Therefore, the entire complex network system is both layered and block-based. This structure of the computing network can be called a layered and block-based structure. Therefore, the hybrid group control of the hybrid computing network requires both layered control and block control.

[0058] S102: Determine the connection span of nodes in the target hybrid computing network, based on the layer corresponding to each node in the topological structure, and determine the key nodes according to the connection span of nodes belonging to the same layer.

[0059] Network connection strength refers to a measure of how much two or more edges in a network model depend on each other. The connection span of a node v refers to the total number of elements that are directly connected to the element v in the topology, that is, the number of nodes connected to the node v. Hierarchical control means focusing on controlling external information. Any node v in the hybrid computing network topology is regarded as an independent node controlled by a group. The topology is composed of a collection of node groups and presents a hierarchical structure, so that the j (j=1, 2, ..., m) layers will be regarded as the search addressing of the key node v. j (j=1, 2, ..., N j ) decision units; the optimization information consists of multiple groups i (i = 1, 2, ..., n), each group n j Information flows from the bottom nodes to the top nodes, or from the top nodes to the bottom nodes. The connection span is used to quantify the connection strength of the hybrid computing network. In the same layer, the key node is selected according to the connection span. Usually, the node with the largest connection span is selected as the key node, that is, node v j Nodes whose changes will affect changes in multiple other nodes are considered key nodes. After searching the nodes at the bottom level, the "decision maker" searches the layer once and then "reviews" it. Usually, the maximum value of the connection span is used as an indicator for the preferred node to find out the important nodes, which are used as the key nodes for determining the layer. The "review" power of the layered control search process gradually increases from the bottom to the top until the search results are given at the top level. The key nodes at the top level have the greatest group control "decision-making power".

[0060] Accordingly, this step usually specifically includes: determining the connection span of the nodes in the target hybrid computing network; based on the layer corresponding to each node in the topological structure, selecting the node with the largest connection span among the nodes belonging to the same layer as the key node. By first calculating the connection span of each node, and then determining the node with the largest connection span in the same layer as the key node, it can be ensured that the key node can involve the most affected nodes.

[0061] S103: Generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes.

[0062] In the embodiment of the present invention, the nodes of the hybrid computing power network are divided into block structures based on the topological structure of the hybrid computing power network to obtain blocks. Each node corresponds to a block, and the block can span the above layers.

[0063] Block control means focusing on controlling internal information. The key node selection for controlling the hybrid computing network is regarded as searching multiple groups, that is, block search, that is, the hierarchical structure is regarded as composed of multiple groups, further divided into blocks according to the groups, searching multiple groups, accepting the "review" of a certain plan, and then sending it to the adjacent upper layer for secondary search, otherwise, it will be abandoned.

[0064] In hierarchical control, the source of information is considered to be external control information; in block control, the source of information is considered to be internal control information. The entropy decision method of group control is used to implement hierarchical and block control, that is, internal control information and external control information are considered in a unified manner. The set of "group" key nodes and control information is called a search scheme, or a search strategy. In this way, each search path is different, and there are different search schemes or search strategies. The search strategy formed is called the topology structure strategy tree of the computing power network system. Determine the optimal solution of the topology structure strategy tree, whose nodes are the layout nodes of the follow-up control devices of group control, so as to realize the global control of "point to surface".

[0065] Specifically, in this step, an alternative strategy tree is generated based on the blocks corresponding to each node in the topological structure and the key nodes. The above strategy tree is based on the paths in the topological structure as lines and the key nodes as the basis, and each cross-block path is selected as the alternative strategy tree.

[0066] In the strategy tree of the hybrid computing network, the nodes for group control are selected as follows: start searching from the bottom layer of the topology structure and select the key nodes for group control, that is, select the nodes with the largest span in the same layer as the key nodes; regard several search strategies or search schemes as strategy trees of several computing nodes, and then use the "optimal quality" of the strategy tree as a metric to obtain a measurement indicator of the synchronization control effect.

[0067] The reason why the "optimal quality" of the strategy tree in the hybrid computing network is used as a measurement indicator is that, based on the basic goal of the controller to achieve consistency, the usual quality measures are fast process execution, less "rework" and reduced costs. For this reason, we use the "optimal quality" of the strategy tree in the hybrid computing network as an indicator to measure the quality of the hybrid control strategy of the computing node.

[0068] Specifically, before this step, it may also include: scanning the target hybrid computing power network to obtain the label of each node in the target hybrid computing power network; the label is used to characterize the corresponding node as a quantum computing power node or an electronic computing power node. That is, in the embodiment of the present invention, when obtaining the topological structure of the target hybrid computing power network, the label of each node can be obtained at the same time to determine the attributes of each node, including determining whether each node is a quantum computer computing power node or an electronic computer computing power node. After this step, before this step, it may also include: dividing the target hybrid computing power network based on the label to determine the block corresponding to each node. That is, the computing power network is divided according to the above-mentioned "label", and adjacent nodes belonging to the same quantum node or the same electronic node are divided into the same block. Of course, different nodes can also be divided into the same block according to other standards, which depends on the specific situation and is not specifically limited here. It should be noted that the above-mentioned label, in addition to characterizing each node as a quantum computer node or an electronic computer node, is also equivalent to characterizing the computing power of the node, so that in the subsequent monitoring and control of each node, specific computing power allocation control can be performed based on the label. The specific contents of the controller will be described in detail in the following embodiments of the invention and will not be elaborated here.

[0069] S104: Determine an optimal strategy tree from the candidate strategy trees through an entropy measurement model and algorithm, and use the corresponding node determined by the optimal strategy tree as a control node.

[0070] The so-called entropy measurement model and algorithm is a model constructed based on the entropy measurement algorithm, which is equivalent to the entropy measurement algorithm. The algorithm is an entropy algorithm constructed for the structural form of the above-mentioned topological structure. The quality corresponding to each of the above-mentioned alternative strategy trees can be calculated by the entropy measurement algorithm, and then the alternative strategy tree corresponding to the optimal quality is selected as the optimal strategy tree, and the corresponding node determined by the optimal strategy tree is used as the control node. The specific content of the entropy measurement model and algorithm will be described in detail in the following invention embodiments, and will not be repeated here.

[0071] S105: Control the control node according to the controller to control the target hybrid computing power network.

[0072] In the embodiment of the present invention, a controller may be set only at the control node, and the control node may be directly controlled by the controller, thereby realizing control of the entire target hybrid computing network. The specific content of the control process will be described in detail in the following invention embodiments, and will not be repeated here.

[0073] A control method for a quantum and electronic hybrid computing power network provided by an embodiment of the present invention first divides the target hybrid computing power network into layers and blocks, determines the key nodes of each layer in the layered structure based on the connection span, and can determine the nodes with higher importance in the same layer; generates a strategy tree spanning each block based on the block structure, so that the strategy tree is the trunk path in the communication path of the entire hybrid computing power network; the control node finally determined based on the entropy measurement model and algorithm has a very high radiation range, and can affect each node of the entire target hybrid computing power network based on the control node. Based on the control of the control node, global control of each node in the entire target hybrid computing power network can be achieved, and single linear control can be applied to a small number of nodes in the target hybrid computing power network, so as to obtain sufficient condition control to ensure local synchronization or feedback control of the complex network.

[0074] The specific contents of the control method of a quantum and electronic hybrid computing power network provided by the present invention will be introduced in detail in the following invention embodiments.

[0075] Please refer to Figure 2 , Figure 2 A flowchart of a specific method for controlling a quantum and electronic hybrid computing power network provided in an embodiment of the present invention.

[0076] See also Figure 2 In an embodiment of the present invention, a control method of a quantum and electronic hybrid computing network includes:

[0077] S201: Obtain the topological structure of the target hybrid computing power network.

[0078] S202: Determine the connection span of the nodes in the target hybrid computing network, and based on the layer corresponding to each node in the topological structure, determine the key nodes from the nodes belonging to the same layer according to the connection span.

[0079] S203: Generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes.

[0080] The above S201 to S203 are basically the same as S101 to S103 in the above invention embodiment, and the details have been described in detail in the above invention embodiment, which will not be repeated here.

[0081] S204: Determine the total number of quality microstates of the candidate strategy tree.

[0082] In the embodiment of the present invention, the quality entropy is used to define the size of the quality uncertainty of each strategy tree in the hybrid computing power network. The smaller the entropy value, the better the quality.

[0083] In this step, based on the topological structure of the hybrid computing network, the corresponding i-th strategy tree is the candidate strategy tree; the j-th level is the corresponding layer; the maximum span node set v j (v j =1,2,...,N j ), that is, the key node set, v j The corresponding span value is There may be several nodes with the same span in the same layer, so the total number of quality microstates of the above alternative strategy tree is:

[0084]

[0085] S205: Determine the quality microstate realization probability value of the alternative strategy tree according to the total number of quality microstates.

[0086] In this step, the i-th candidate strategy tree of the hybrid computing network is defined. In the j-th layer, the key node v j The span value is The probability of realizing the mass microstate is:

[0087]

[0088] S206: Determine the quality entropy of the candidate strategy tree according to the quality micro-state realization probability value.

[0089] In this step, the measure of the quality uncertainty of the candidate strategy tree is called the quality entropy of the strategy tree, and the measurement value is:

[0090]

[0091] Combining the above two formulas, we can get:

[0092]

[0093] S207: Determine the total mass entropy of the target hybrid computing power network according to the mass entropy.

[0094] Therefore, the total mass entropy measure of the i-th candidate strategy tree in the above hybrid computing network is:

[0095]

[0096] At this time, the maximum mass entropy of the jth layer of the alternative strategy tree is:

[0097]

[0098] That is, the quality microstate of the candidate strategy tree in the hybrid computing network The maximum mass entropy measure of the strategy tree is:

[0099]

[0100] S208: Determine the quality of the candidate strategy tree according to the total quality entropy.

[0101] In this step, the quality of the candidate strategy tree in the hybrid computing network is recorded as The definition is as follows:

[0102]

[0103] S209: Determine from the qualities the candidate strategy tree corresponding to the maximum quality as the optimal strategy tree, and use the corresponding node determined by the optimal strategy tree as the control node.

[0104] In this step, the quality of n candidate strategy trees in the hybrid computing network will be compared, and the The strategy corresponding to the maximum value is the optimal strategy, that is, choose The alternative strategy tree corresponding to the maximum value is the optimal strategy tree, that is:

[0105]

[0106] That is, The key node set composed of the optimal strategy tree corresponding to the maximum value is the "control device set" of the layout controller. In this step, the nodes in the key node set will be used as control nodes to set the controller.

[0107] Taking the maximum quality value of the strategy tree As a measure of the optimal quality of the control strategy tree of the computing power node. That is, the maximum quality value The larger the value, the better the computing power network strategy tree is, and vice versa.

[0108] exist Implement group control and deploy follow-up controllers at key nodes of the strategy tree corresponding to the computing power nodes to achieve “point-to-surface” synchronous group control.

[0109] S210: Control the control node according to the follow-up controller to globally control the target hybrid computing power network.

[0110] This step is basically the same as S105 in the above-mentioned embodiment of the invention. Please refer to the above-mentioned embodiment of the invention for details, and will not be described again here.

[0111] A control method for a quantum and electronic hybrid computing power network provided in an embodiment of the present invention can accurately obtain the control nodes that can affect the global situation in the target hybrid computing power network through the above-mentioned entropy measurement model and algorithm. By controlling a small number of control nodes, a single linear control can be applied to a small number of nodes in the target hybrid computing power network, thereby obtaining sufficient conditional control to ensure local synchronization or feedback control of the complex network.

[0112] The specific contents of the control method of a quantum and electronic hybrid computing power network provided by the present invention will be introduced in detail in the following invention embodiments.

[0113] Please refer to Figure 3 , Figure 3 A flowchart of another specific method for controlling a quantum and electronic hybrid computing power network provided by an embodiment of the present invention.

[0114] See also Figure 3 In an embodiment of the present invention, a control method of a quantum and electronic hybrid computing network includes:

[0115] S301: Scan the target hybrid computing power network to obtain the label of each node in the target hybrid computing power network.

[0116] In the embodiment of the present invention, the label is used to characterize the corresponding node as a quantum node or an electronic node. In the embodiment of the present invention, the characteristic value of the quantum computer and the electronic computer interface can be set, the quantum computer node corresponds to <0, 1>, and the electronic computer node corresponds to {0, 1}; then the label of each node is determined according to the characteristic value.

[0117] S302: Determine the connection span of the nodes in the target hybrid computing network, and based on the layer corresponding to each node in the topological structure, determine the key nodes from the nodes belonging to the same layer according to the connection span.

[0118] S303: Generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes.

[0119] S304: Determine an optimal strategy tree from the candidate strategy trees through an entropy measurement model and algorithm, and use the corresponding node determined by the optimal strategy tree as a control node.

[0120] The above S302 to S304 are basically the same as S102 to S104 in the above invention embodiment. Please refer to the above invention embodiment for details, which will not be repeated here.

[0121] S305: Monitor the control node according to the controller, and determine the node with computing power overflow in the target hybrid computing power network based on the label.

[0122] Arithmetic overflow refers to the situation where the result of arithmetic operations performed by a computer exceeds the range that the machine can represent. That is, arithmetic overflow means that the computing power node does not support the implementation of its corresponding computing power operation. In this step, each control node can be monitored based on the controller. When the node performs an operation, its state will change. By monitoring each node, it can be determined whether the node has a computing power overflow based on the label corresponding to each node. Since the computing power overflow conditions corresponding to the computing power nodes of quantum computers and electronic computers are significantly different, when determining whether each node has a computing power overflow, it will be judged in combination with the type represented by its label, and it needs to be set in the follow-up control device according to the actual situation.

[0123] When a computing power overflow occurs in a control node, it can be directly detected by the follow-up control device, thereby determining the node with computing power overflow in the target hybrid computing power network. When a computing power overflow occurs in a non-control node, it will specifically affect the above-mentioned control node, so the node with computing power overflow can be indirectly detected by the controller, thereby determining the node with computing power overflow in the target hybrid computing power network, and then an early warning can be issued. Therefore, in the embodiment of the present invention, real-time early warning control can be implemented, and the monitoring and control of abnormal conditions in the operation process of the hybrid computing power network only requires placing a controller on the control node. Once an abnormal condition occurs in a subnet or a node of the computing power network, including physical changes such as computing power overflow, the controller on the control node will issue an early warning.

[0124] S306: The controller controls the control node, and migrates the tasks corresponding to the node with overflowed computing power to the target node based on the label.

[0125] During the network computing and storage process, a node may overflow computing power, that is, it does not support the implementation of its corresponding computing power operations. The controller on the control node will use the allocation and scheduling system software to re-plan and allocate its computing entities.

[0126] In this step, based on the labels of each node, the tasks executed by the node with computing power overflow can be migrated and assigned to the target node. The target node can be the same type of node as the node with computing power overflow, such as a quantum node or an electronic node; or it can be a different node, for example, migrating the tasks in the electronic node with computing power overflow to the quantum node, and the selection of the above target node usually depends on the above label. In this step, the tasks corresponding to the node with computing power overflow will be migrated and assigned to the target node through the controller to ensure the normal execution of the target task. The controller will directly act on the control node to achieve global control of the entire target hybrid computing power network.

[0127] A control method for a quantum and electronic hybrid computing power network provided by an embodiment of the present invention can realize real-time group control, that is, by applying a single linear control to a node in the network, sufficient condition control to ensure local synchronization or feedback control of a complex network is obtained; real-time early warning control, that is, monitoring and control of abnormal conditions in the operation process of the computing power network, only needs to place a control device on the control node. Once an abnormal situation occurs in a subnet or a node of the computing power network, such as physical changes, the device on the key node will issue an early warning; real-time scheduling control, that is, during the network calculation and storage process, a node may have a computing power overflow, that is, it does not support the implementation of its corresponding computing power operation. The control device on the control node will use the allocation scheduling system software to re-plan and allocate its computing subject.

[0128] Please refer to Figure 4 , Figure 4 FIG. 1 is a schematic diagram of a topological structure of a target hybrid computing network. Figure 4 For example, the final control node is determined through the process provided by the above embodiment of the invention.

[0129] According to a control method of a quantum and electronic hybrid computing power network provided by the above-mentioned embodiment of the invention, Figure 4 The nodes in the network are searched according to the hierarchical principle, and the following results are obtained:

[0130] The first layer: contains nodes 1-6, nodes 7-8;

[0131] Second layer: nodes 9-10, nodes 11-13, node 14;

[0132] The third layer: nodes 15-16, node 17, nodes 18-20, node 21, nodes 22-23, node 24.

[0133] According to the principle of block search, different blocks can be obtained, such as the following three blocks:

[0134] Block 1: Node 7 and nodes 1, 2, 3, 4, 5, 6;

[0135] Block 2: Node 8 and nodes 9, 10, 11, 12, 13, 14;

[0136] Block 3: Node 24 and nodes 15, 16, 17, 18, 19, 20, 21, 22, 23;

[0137] The final calculation results are shown in Table 1: Quality Summary of Strategy Tree of Key Node Sets for Local Control of Computing Network:

[0138] Table 1 Summary of the quality of the strategy tree of the key node set of the local control of the computing power network

[0139]

[0140] The analysis of the above Table 1 is as follows:

[0141] Based on the above steps of determining key nodes, we can get the key node set: {7, 8, 9, 10, 11, 12, 13, 14, 24}.

[0142] Calculate the quality values ​​of key nodes: Node 7 and Node 8 are both in the first layer, in different blocks, and have the same quality value; Node 9 and Node 10 are both in the second layer, in different blocks, and have the same quality value; Node 11, Node 12, and Node 13 are all in the second layer and have the same quality value.

[0143] The strategy tree quality value of the computing power node controls the strategy tree path analysis, and the candidate strategy tree set is: {7, 9, 24}, {7, 10, 24}, {8, 9, 24}, {8, 10, 24}, {7, 11, 24}, {7, 12, 24}, {7, 13, 24}, {7, 14, 24}, {8, 11, 24}, {8, 12, 24}, {8, 13, 24}, {8, 14, 24}.

[0144] The maximum quality set of computing power nodes is:

[0145] ={0.7515, 0.7905, 0.6972}

[0146] The optimal control node set corresponding to the above optimal strategy tree is {{7}, {9}, {24}} or {{7}, {10}, {24}}, or {{8}, {9}, {24}}, or {{8}, {10}, {24}}.

[0147] Therefore, we only need to select any group of the above-mentioned computing nodes and add a controller to achieve global control of "leading the whole by the point".

[0148] The following is an introduction to a follow-up control device for a quantum and electronic hybrid computing power network provided by an embodiment of the present invention. The follow-up control device for the quantum and electronic hybrid computing power network described below and the control method for the quantum and electronic hybrid computing power network described above can be referenced to each other.

[0149] In an embodiment of the present invention, the servo control device includes a hardware-based software control module, a memory for carrying the software control module, a processor, and a computer-readable storage medium for implementing the above-mentioned embodiments of the invention and storing a computer program. The servo control device is usually specifically embedded in the control node, and can realize global control of the hybrid computing network based on the linear control of the control node.

[0150] Please refer to Figure 5 , Figure 5 A structural block diagram of a control device for a quantum and electronic hybrid computing power network provided in an embodiment of the present invention.

[0151] See also Figure 5 In an embodiment of the present invention, the control device of the quantum and electronic hybrid computing power network may include:

[0152] The topology acquisition module 100 is used to acquire the topology of the target hybrid computing power network.

[0153] The key node determination module 200 is used to determine the connection span of the nodes in the target hybrid computing power network, based on the layer corresponding to each node in the topological structure, and determine the key nodes according to the connection span of the nodes belonging to the same layer.

[0154] The strategy tree generation module 300 is used to generate a candidate strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes.

[0155] The control node selection module 400 is used to determine the optimal strategy tree from the candidate strategy trees through an entropy measurement model and algorithm, and use the corresponding node determined by the optimal strategy tree as the control node.

[0156] The controller embedded module 500 is used to control the control node according to the controller to perform real-time control on the target hybrid computing power network.

[0157] Preferably, in the embodiment of the present invention, the key node determination module 200 includes:

[0158] The connection span unit is used to determine the connection span of the nodes in the target hybrid computing power network.

[0159] The key node unit is used to select the node with the largest connection span among the nodes belonging to the same layer as the key node based on the layer corresponding to each node in the topological structure.

[0160] Preferably, in the embodiment of the present invention, the topology structure acquisition module 100 is specifically used for:

[0161] The target hybrid computing power network is scanned to obtain a label of each node in the target hybrid computing power network; the label is used to characterize that the corresponding node is a quantum node or an electronic node.

[0162] Preferably, in the embodiment of the present invention, it also includes:

[0163] The block module is used to divide the target hybrid computing power network based on the label and determine the block corresponding to each node.

[0164] Preferably, in the embodiment of the present invention, the controller embedded module 500 is used for:

[0165] The control node is monitored according to the controller, and a node with computing power overflow in the target hybrid computing power network is determined based on the label.

[0166] Preferably, in the embodiment of the present invention, the controller embedded module 500 is used for:

[0167] The control node is controlled according to the controller, and the tasks corresponding to the node with overflowed computing power are migrated and allocated to the target node based on the label.

[0168] Preferably, in the embodiment of the present invention, the control node selection module 400 includes:

[0169] The total number of quality microstates unit is used to determine the total number of quality microstates of the alternative strategy tree.

[0170] The quality micro-state realization probability value unit is used to determine the quality micro-state realization probability value of the alternative strategy tree according to the total number of quality micro-states.

[0171] The mass entropy unit is used to determine the mass entropy of the candidate strategy tree according to the mass microstate realization probability value.

[0172] A total mass entropy unit is used to determine the total mass entropy of the target hybrid computing power network according to the mass entropy.

[0173] A quality unit is used to determine the quality of the candidate strategy tree according to the total quality entropy.

[0174] The optimal strategy tree unit is used to determine the candidate strategy tree corresponding to the maximum quality from the qualities as the optimal strategy tree, and use the corresponding node determined by the optimal strategy tree as the control node.

[0175] The control device of the quantum and electronic hybrid computing power network of this embodiment is used to implement the control method of the quantum and electronic hybrid computing power network mentioned above. Therefore, the specific implementation method of the control device of the quantum and electronic hybrid computing power network can be seen in the embodiment part of the control method of the quantum and electronic hybrid computing power network in the previous text. For example, the topology acquisition module 100, the key node determination module 200, the strategy tree generation module 300, the control node selection module 400, and the controller embedding module 500 are respectively used to implement steps S101 to S105 in the control method of the quantum and electronic hybrid computing power network mentioned above. Therefore, its specific implementation method can refer to the description of the corresponding embodiments of each part, which will not be repeated here.

[0176] The following is an introduction to a control device of a quantum and electronic hybrid computing power network provided by an embodiment of the present invention. The control device of the quantum and electronic hybrid computing power network described below and the control method of the quantum and electronic hybrid computing power network and the follow-up control device of the quantum and electronic hybrid computing power network described above can be referenced to each other.

[0177] Please refer to Figure 6 , Figure 6 A block diagram of the control device structure of a quantum and electronic hybrid computing power network provided in an embodiment of the present invention.

[0178] Reference Figure 6 The control device of the quantum and electronic hybrid computing power network may include a processor 11 and a memory 12.

[0179] The memory 12 is used to store computer programs; the processor 11 is used to implement the control method of the quantum and electronic hybrid computing power network described in the above-mentioned embodiment of the invention when executing the computer program.

[0180] The processor 11 in the control device of the quantum and electronic hybrid computing power network of this embodiment is used to install the follow-up control device of the quantum and electronic hybrid computing power network described in the above-mentioned invention embodiment, and the processor 11 is combined with the memory 12 to realize the control method of the quantum and electronic hybrid computing power network described in any of the above-mentioned invention embodiments. Therefore, the specific implementation method of the control device of the quantum and electronic hybrid computing power network can be seen in the embodiment part of the control method of the quantum and electronic hybrid computing power network in the previous text, and its specific implementation method can refer to the description of the corresponding various partial embodiments, which will not be repeated here.

[0181] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, a control method for a quantum and electronic hybrid computing network introduced in any of the above-mentioned embodiments of the invention is implemented. The rest of the content can refer to the prior art and will not be described in detail here.

[0182] The present invention also provides a dynamic data management system for a quantum and electronic hybrid computing power network, which generally includes a user layer, an application server layer, a data layer, etc.

[0183] User layer S1: can simultaneously meet the data selection and scheduling in a control method of a quantum and electronic hybrid computing power network provided by any of the above-mentioned embodiments of the invention, as well as realize data layer data interaction. That is, in a control method of a quantum and electronic hybrid computing power network, the system realizes data exchange with each functional module during the optimization process of the control node to be selected.

[0184] Application server layer S2: The application server layer is the middle layer set between the data layer and the user layer. It realizes unified database management, knowledge base management, user access to the database, and protects database security and work efficiency. The user interface is connected to the data layer through the middle layer.

[0185] Database management, including user and permission management, assigning different permissions to different users.

[0186] Knowledge base management is the management and maintenance of the database of characteristic parameters of the control object, statistical database, etc., including the addition, deletion, editing and query of information.

[0187] Data layer S3: used to store or call data, including data that meets the control method optimization of a quantum and electronic hybrid computing network and the storage or call data of the strategy tree to be optimized in each link function module, part of the data communicated with the database, pre-set data, intermediate data that needs to be stored, etc. It plays the role of a data repository.

[0188] The stored or called data includes a set of strategy trees corresponding to a control method of a hybrid computing power network based on a quantum and electronic hybrid computing power network, and the initial state data to be calculated, intermediate operation data, analysis process data, sub-item operation data, comprehensive operation data, etc. corresponding to its quality data.

[0189] Based on the control system of the above-mentioned quantum and electronic hybrid computing power network, a control method of a quantum and electronic hybrid computing power network provided by any of the above-mentioned invention embodiments can be specifically implemented. The specific content has been described in detail in the above-mentioned invention embodiments and will not be repeated here.

[0190] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the follow-up control device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0191] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0192] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0193] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0194] The above is a detailed introduction to the control method and follow-up control device of a quantum and electronic hybrid computing power network provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present invention, the present invention can also be improved and modified, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A control method for a quantum and electronic hybrid computing network, characterized in that: include: Obtain the topology of the target hybrid computing network; Determine the connection span of nodes in the target hybrid computing network, and determine the key nodes based on the layers corresponding to each node in the topological structure and the connection span of nodes belonging to the same layer; Generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes; Determine an optimal strategy tree from the candidate strategy trees by using an entropy measurement model and algorithm, and use the corresponding node determined by the optimal strategy tree as a control node; Controlling the control node according to the controller to perform synchronous hierarchical and block control on the target hybrid computing power network; The determining of the connection span of the nodes in the target hybrid computing power network, based on the layers corresponding to the nodes in the topological structure, and determining the key nodes from the nodes belonging to the same layer according to the connection span includes: Determining the connection span of nodes in the target hybrid computing power network; Based on the layers corresponding to the nodes in the topological structure, the node with the largest connection span among the nodes belonging to the same layer is selected as the key node; Determining the optimal strategy tree from the candidate strategy trees by using an entropy measurement model and an algorithm, and using the corresponding node determined by the optimal strategy tree as a control node comprises: Determining the total number of quality microstates of the alternative strategy tree; Determine the quality microstate realization probability value of the alternative strategy tree according to the total number of quality microstates; Determining the quality entropy of the alternative strategy tree according to the quality microstate realization probability value; Determine the total mass entropy of the target hybrid computing power network according to the mass entropy; Determining the quality of the candidate strategy tree according to the total quality entropy; The candidate strategy tree corresponding to the maximum quality is determined from the qualities as the optimal strategy tree, and the corresponding node determined by the optimal strategy tree is used as the control node.

2. The method according to claim 1, characterized in that The obtaining of the topological structure of the target hybrid computing power network includes: The target hybrid computing power network is scanned to obtain a label of each node in the target hybrid computing power network; the label is used to characterize that the corresponding node is a quantum computer node or an electronic computer node.

3. The method according to claim 2, characterized in that Before generating the candidate strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes, the method further includes: The target hybrid computing network is divided based on the label, and adjacent nodes of the same type are divided into the same block.

4. The method according to claim 2, characterized in that: The controlling the control node according to the controller to control the target hybrid computing power network includes: The control node is monitored according to the controller, and a node with computing power overflow in the target hybrid computing power network is determined based on the label.

5. The method according to claim 4, characterized in that The controlling the control node according to the controller to control the target hybrid computing power network includes: The control node is controlled according to the controller, and the tasks corresponding to the node with overflowed computing power are migrated to the target node based on the label.

6. A quantum and electronic hybrid computing power network follow-up control device, characterized in that: include: A topology acquisition module is used to obtain the topology of the target hybrid computing network; A key node determination module, used to determine the connection span of nodes in the target hybrid computing network, based on the layer corresponding to each node in the topological structure, and determine the key node according to the connection span of nodes belonging to the same layer; A strategy tree generation module, used to generate an alternative strategy tree based on the blocks corresponding to each node in the topological structure and the key nodes; A control node selection module is used to determine the optimal strategy tree from the candidate strategy trees through an entropy measurement model and algorithm, and use the corresponding node determined by the optimal strategy tree as the control node; A controller embedded module, used to control the control node according to the controller to globally control the target hybrid computing power network; The key node determination module includes: A connection span unit, used to determine the connection span of nodes in the target hybrid computing power network; A key node unit, for selecting a node with the largest connection span among nodes belonging to the same layer as a key node based on the layer corresponding to each node in the topological structure; The control node selection module includes: A total number of quality microstates unit, used to determine the total number of quality microstates of the candidate strategy tree; A quality micro-state realization probability value unit, used to determine the quality micro-state realization probability value of the alternative strategy tree according to the total number of quality micro-states; A mass entropy unit, used to determine the mass entropy of the candidate strategy tree according to the mass microstate realization probability value; A total mass entropy unit, used to determine the total mass entropy of the target hybrid computing power network according to the mass entropy; A quality unit, used to determine the quality of the candidate strategy tree according to the total mass entropy; The optimal strategy tree unit is used to determine the candidate strategy tree corresponding to the maximum quality from the qualities as the optimal strategy tree, and use the corresponding node determined by the optimal strategy tree as the control node.

7. A control device for a quantum and electronic hybrid computing network, characterized in that: The device comprises: Memory: used to store computer programs; Processor: used to implement the steps of the control method of the quantum and electronic hybrid computing power network as described in any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for controlling a quantum and electronic hybrid computing power network as claimed in any one of claims 1 to 5.

Images