2164 results about "Data buffer" patented technology

The invention discloses an optical fiber data storage management system and method based on big data, and relates to the technical field of storage management. According to the optical fiber data storage management system and method based on big data, the spatial-temporal characteristics of the historical access records are extracted through the LSTM network, the data heat value is calculated in combination with the time decay function, and the thermal distribution diagram of the data blocks is generated. And based on the thermal distribution map, constructing a storage resource allocation model by using a deep reinforcement learning algorithm, and dynamically adjusting the optical path priority and copy distribution. A data prefetching strategy is optimized through the spatio-temporal joint index and the vector similarity index, and a high-frequency data cache index distribution diagram is generated. And comprehensively considering the data access delay, the index hit rate and the copy migration frequency, obtaining an optical fiber storage efficiency index, and adjusting a storage strategy according to the index. According to the method, the dynamic scheduling and utilization efficiency of data storage resources is effectively improved, the data access delay is reduced, the copy management is optimized, and the overall performance of a storage system is remarkably improved.

The invention discloses a method for automatically drawing an OpenGL (Open Graphics Library) program by using Vulkan. The method comprises the following steps of: creating a context used by the Vulkan, initializing each module, processing an OpenGL instruction related to texture and data buffering, and managing storage of texture and data buffering resources in a video memory; a shader program used by the OpenGL is preprocessed into a format acceptable to Vulkan, and an OpenGL shader program instruction is created and destroyed; processing an OpenGL (Open Graphics Library) instruction related to frame buffering to generate structural body information required by Vulkan dynamic rendering; an OpenGL instruction of the sampler is also created; processing an OpenGL (Open Graphics Library) instruction for creating a vertex input format and managing a vertex data buffer area, and maintaining vertex input information, a vertex buffer area and an index buffer area required by Vulkan; and finally, drawing or calculating, distributing and calling Vulkan on the basis of all the instructions.

The invention discloses a large model data distributed management method and device, equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: segmenting large model training data to obtain a plurality of data blocks, and determining a predicted access frequency based on a long short-term memory network model and the historical access frequency of the data blocks; caching the large model training data corresponding to the data block to a corresponding data cache layer by utilizing the predicted access frequency; constructing a resource portrait by using the static attribute and the dynamic index of the GPU node, and allocating the large model training task to a target GPU node by using a preset hybrid strategy and the resource portrait based on the predicted access frequency and the storage position corresponding to the data block in the data cache layer; when it is monitored that the large model training task on the target GPU node is executed, periodic snapshot is conducted on the large model training task through a distributed snapshot algorithm, and the obtained complete data state is stored in a distributed storage center. And the resource vacancy rate is reduced.

The invention relates to the technical field of big data processing, and provides a mass data storage optimization method which comprises the following steps: analyzing target data according to access frequency and / or access time of the data, and dividing the target data into hot data, warm data and cold data; aiming at the hot data, the temperature data and the cold data, performing compression processing by adopting corresponding compression algorithms; before the target data is stored, performing duplicate removal on the target data according to the fingerprint of the target data; monitoring the use condition of the memory, the access frequency of the target data and the performance of the compression algorithm in real time, and deploying system resources according to a monitoring result; and setting a multi-level cache, and caching different types of target data to the multi-level cache according to the divided types of the target data. According to the technical scheme, mass data can be efficiently stored and rapidly accessed, and the storage space utilization rate and the overall system performance are remarkably improved.

An intelligent power monitoring management system based on Internet of Things belongs to the technical field of power supervision and comprises a data acquisition module, a communication transmission module, a data processing and analysis module, an edge calculation module, an intelligent control module, an early warning management module and an authority control module. According to the invention, by deploying various types of sensors, real-time acquisition and dynamic monitoring of key parameters of the power system are realized. The system can obtain and analyze data such as voltage, current and power in time, ensures the accuracy and high efficiency of operation of the power system, and effectively avoids energy consumption waste and equipment faults. The edge computing technology is adopted, preprocessing and preliminary analysis are carried out at a data acquisition end, the data processing pressure of a central server is relieved, the bandwidth requirement for data transmission is lowered, and the response speed is increased. Even if the network is interrupted, the edge device can realize short-term data caching, and data continuity is guaranteed. And performing anomaly detection on the power system, identifying potential risks and giving an alarm.

The invention relates to the technical field of geographic information systems, in particular to a map tile data efficient access method and system based on hybrid storage and intelligent layering, and the method comprises the following steps: constructing a multi-level storage architecture, carrying out dynamic heat analysis, carrying out intelligent layering scheduling, preloading and space prediction, and carrying out transmission and access optimization. The method has the beneficial effects that the multi-level storage pool is constructed by combining the advantages of object storage and a distributed file system; adopting a dynamic tile popularity analysis model to realize hot data cache acceleration and cold data hierarchical archiving; and meanwhile, a tile request preloading mechanism is introduced, and an access path is optimized in combination with a spatial locality prediction algorithm. According to the method, the storage cost can be remarkably reduced, the tile request delay is reduced, quick response in a high-concurrency scene is supported, and the method is suitable for application scenes such as Internet map services and smart cities.

The invention discloses a computer network security monitoring system and method. The system comprises a quantum encryption traffic acquisition module, a biological recognition feature extraction module, a block chain detection traceability analysis module and a visual management module. The quantum encryption flow collection module generates and distributes a secure quantum key through a quantum key distribution unit, encrypts a collected data packet through an encryption transmission unit, and generates a flow data segment through a flow collection subunit and a data cache statistical analysis subunit. The biological recognition feature extraction module verifies the identity of a user through a biological recognition unit, and extracts a multi-dimensional feature vector by using a feature extraction subunit. And the block chain detection traceability analysis module performs detection and traceability analysis on the abnormal traffic through the anomaly detection subunit and the traceability analysis subunit, and stores a result in the block chain storage unit. The visual management module provides visual network state display and user identity verification functions through a visual display subunit and an identity verification and access control subunit. According to the invention, quantum encryption, biological recognition and block chain technologies are combined, so that the accuracy, security and traceability of network security monitoring are improved.

The invention provides a switching station control method and system of a subway station. The system comprises a subsystem control unit, a main control unit, a communication module and a data caching module, the subsystem control unit transmits an equipment on-off state, a fault signal and an environment parameter to the main control unit in a hybrid networking mode, and a first cooperative control instruction set is generated in combination with a linkage rule base; a target priority is distributed for the operation instruction to obtain a second cooperative control instruction set, and the communication module adopts a multi-channel parallel distribution mechanism for pushing; in the process of executing the switching station operation, the data caching module stores running state data, identifies a time sequence mode by using a machine learning model, pre-judges a switching station linkage scene and loads a control strategy; and the main control unit detects the response delay of the subsystem control unit and generates a third cooperative control instruction set according to the control strategy so as to optimize the switching station control time sequence. According to the invention, intelligent cooperative control of multiple electromechanical devices can be realized.

The invention discloses an equipment temperature adjusting method fusing a long short-term memory network, and particularly relates to the technical field of temperature control, which comprises the following steps: determining the deployment position of a sensor through thermal simulation, collecting multi-source heterogeneous data, dynamically adjusting the sampling frequency in combination with the temperature and the load current change rate, and adjusting the temperature of the sensor; after data preprocessing, an attention mechanism enhanced LSTM prediction model is constructed, a time sequence sample data set is divided according to equipment thermal response characteristics, training is carried out, and an optimal model is obtained through early stop mechanism optimization; predictive feedback double-closed-loop regulation and control is achieved based on the optimal model, outer loop PI control is combined with an integral separation mechanism to generate a basic control quantity, an inner loop outputs a correction quantity through fuzzification, reasoning and defuzzification, an actuator is driven after superposition, and safety linkage is triggered synchronously; constructing an incremental data buffer pool to screen effective samples, and adaptively updating model parameters by adopting a layered fine tuning strategy; the temperature regulation and control precision and the long-term self-adaptive capability are obviously improved, and the over-temperature risk of equipment is reduced.

The invention discloses a solid state disk data processing method and device, a storage medium and a program product, and relates to the field of electrical digital data processing.The method comprises the steps that a network data transmission request is obtained, a network bandwidth state corresponding to the network data transmission request is detected, and bandwidth state parameters are generated according to the network bandwidth state; calculating a data transmission time consumption predicted value, and determining a buffer capacity threshold according to the data transmission time consumption predicted value; adjusting the capacity of the data buffer area according to the buffer area capacity threshold, and adjusting the data buffer area; monitoring the data occupancy rate of the adjusted data buffer area, and when the data occupancy rate is lower than a preset occupancy rate threshold value, calculating an idle time window of the target solid state disk according to the network bandwidth state; determining a target power consumption mode of the target solid state disk according to the duration of the idle time window; and controlling the target solid state disk to enter the target power consumption mode in the idle time window. By implementing the application, the energy consumption of the solid state disk can be reduced.

The invention relates to the technical field of intelligent power supplies, in particular to an intelligent power supply for an unattended station. Comprising a multi-source power supply scheduling unit; an intelligent energy storage management unit; a double-link communication unit; the double-link communication unit is used for constructing a multi-redundancy communication link of wired, wireless and power line carriers, and the double-link communication unit is based on link quality data, adopts an automatic switching strategy to guarantee data transmission continuity, preprocesses monitoring data by using an edge side data clustering algorithm, and realizes offline data caching and transmission flow optimization. Through a multi-source energy dynamic scheduling strategy, according to photovoltaic real-time output, commercial power time-of-use electricity price and load electricity demand, power supply paths of photovoltaic, commercial power and a storage battery can be dynamically optimized, the consumption proportion of clean energy is improved, the dependency degree of high-cost commercial power is reduced, a complex energy structure of photovoltaic, commercial power and storage battery multi-energy complementation is effectively adapted, and the energy utilization rate is improved. And power supply flexibility is enhanced.

The invention belongs to the technical field of data caching and batch synchronization, and discloses a management system data caching and batch synchronization method and system.The method comprises the steps that caching processing is conducted on pre-obtained data through a caching strategy based on a pre-constructed caching architecture, operation data are extracted through the cached data, and the operation data are stored in a database; carrying out local operation processing and operation type judgment by combining a transaction engine and an operation classifier; acquiring storage state data of the cache architecture in real time, performing synchronization strategy optimization on a preset synchronization strategy by using a decision tree algorithm, and performing batch synchronization processing in combination with a chained version number mechanism; and acquiring operation state data of the cache architecture, constructing a cache performance index system by using the operation state data, and performing data storage alarm processing by combining an autoregression integral moving average model and an association rule. According to the method, the high-frequency operation response speed is obviously optimized, the load of a back-end server is effectively reduced, and efficient utilization of hardware resources is realized.

The invention provides a fusing processing method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps of performing current limiting on a system request based on a filter to obtain a target request; determining whether to trigger the fusing condition of the target service based on the real-time operation data of the target service corresponding to the target request and the fusing judgment rule; in response to the fact that the target service is the first service and a fusing condition of the first service is triggered, performing fusing operation on the first service; the first service is used for message transmission; in response to the fact that the target service is the second service and a fusing condition of the second service is triggered, performing degradation operation on the second service; the second service is used for data caching, and the type of the degradation operation is determined based on the dependency of the target request on the second service. According to the invention, intelligent degradation fusing processing can be realized, so that system overload and single-point fault diffusion can be effectively prevented.

The invention provides a cache architecture and method of an AXI interconnection module, electronic equipment and a storage medium, and relates to the technical field of storage, the cache architecture comprises an index cache region, a shared cache region and a shared cache access controller, the index cache region comprises an index entry list, and the shared cache region comprises an instruction cache region and a data cache region; each index cache region corresponds to one main device, the shared cache region corresponds to all the main devices, and the index entry list is used for recording index information of access transactions of the corresponding main devices; each index entry in the index entry list corresponds to one access transaction; and the shared cache access controller is used for storing instruction information corresponding to the access transaction in the instruction cache region based on the index information and storing data information corresponding to the access transaction in the data cache region. By applying the scheme of the invention, the utilization efficiency of on-chip resources can be improved on the basis of ensuring the transaction processing performance.

The invention discloses a data processing method and system, electronic equipment, a storage medium and a computer program product, and relates to the technical field of large model technology and key value caching. The method comprises the following steps: acquiring a plurality of visual marks, a plurality of text marks and initial key value data corresponding to a visual language model; determining a key text mark in the plurality of text marks by utilizing the initial key value data; according to the initial key value data and the distribution positions of the key text marks in the multiple text marks, importance evaluation is conducted on the multiple visual marks, an evaluation result is obtained, and the evaluation result is used for representing cross-modal attention weight distribution between the multiple visual marks and the key text marks; and according to an evaluation result, performing cache compression processing on the initial key value data to obtain target key value data. According to the method and the device, the technical problem that the model reasoning efficiency is influenced due to high key value data caching overhead of a visual language model in related technologies is solved.

The invention discloses an SSD (Solid State Disk) cache management method, which relates to the technical field of SSDs, and comprises the following steps: step 1, cache space division: the cache space of the SSD is divided into a plurality of different types of sub-cache regions, and each sub-cache region at least comprises a hot data cache region, a cold data cache region and an intermediate data cache region; 2, data popularity monitoring: monitoring the access frequency of the data stored in the SSD in real time, judging the popularity level of the data according to the access frequency, judging the data with the access frequency higher than a set threshold as hot data, judging the data with the access frequency lower than another set threshold as cold data, and judging the data between the hot data and the cold data as intermediate data; 3, data cache allocation: according to the heat level of the data, storing hot data into a hot data cache region, storing cold data into a cold data cache region, and storing intermediate data into an intermediate data cache region; the cache utilization rate and the read-write performance are comprehensively improved, and the delay is reduced.

The invention relates to the field of equipment safety verification, in particular to a wifi router on-line upgrading safety verification method and a wifi router on-line upgrading safety verification system. A wifi router online upgrade security verification system comprises a firmware package construction module, a firmware package verification module and a guarantee activation module. According to the method, a firmware packet header protection logic closed loop is formed through an innovatively designed multi-order composite verification structural body and an anti-offset signature positioning framework; the system can detect the nanoscale tampering of an attacker to the length identification field in real time, cuts off the power supply of the flash memory controller and erases the data buffer area at the hardware fusing level response speed when verification fails, and compared with a traditional scheme, the response efficiency is improved.

The invention relates to the technical field of data processing, can be applied to business scenes such as financial science and technology and medical health, and discloses a popup strategy task processing method which comprises the following steps: defining a life cycle node of a popup queue in a task queue processing center, dividing a popup task into an independent execution thread task and a shared execution thread task according to priority, binding to life cycle nodes respectively; creating an exclusive policy execution assembly line in the independent execution thread, and creating an interruptible policy execution assembly line in the shared execution thread; a strategy execution state judgment node is arranged in the two strategy execution assembly lines, and a standby strategy execution assembly line is triggered when strategy execution is abnormal; and uniformly storing output data generated by the three policy execution assembly lines through a public data cache region. By setting the priority-based thread task binding mechanism and the strategy execution state judgment node, decoupling and exception handling automation of the pop-up window strategy execution process are realized, and the strategy maintenance cost is reduced.

The invention discloses a parallel processor dynamic resource allocation system and method based on reconfigurable hardware, and relates to the technical field of computer chips, and the system comprises a workload monitoring module which is responsible for monitoring the workload type and the resource demand of a task processed by a parallel processor in real time, and determining the task type and the resource demand by identifying the task type and the resource demand; a monitoring result is fed back to the resource allocation control module; the resource allocation control module is responsible for generating a corresponding resource allocation control signal based on feedback information of the workload monitoring module and dynamically configuring the reconfigurable hardware module; the reconfigurable hardware module is responsible for realizing efficient adaptation to diversified tasks through a plurality of reconfigurable units formed by programmable logic devices according to different working load dynamic reconfiguration functions and connection modes; and the data caching and transmission module is responsible for cross-module data circulation and global data storage. Different task requirements can be accurately adapted, and the resource utilization rate is improved.

The invention relates to the technical field of data cache management, in particular to a multilayer data cache dynamic management method and system, and the method comprises the following steps: based on a data access path, extracting a data access path hierarchy identifier, analyzing path hierarchy depth, recording access continuity, classifying the path to be stable or unstable, and obtaining path hierarchy distribution information. In the invention, through hierarchical analysis and stability classification of the data access paths, the cache resource allocation efficiency, the stable paths and the unstable paths are improved, the access delay is reduced, the access continuity is improved, the cache waste caused by hopping is reduced, the space utilization rate is improved, the cache pollution is avoided, the storage sequence is optimized, and the hit rate is improved; through dynamic elimination, resource competition is reduced, storage medium I / O load is monitored, medium load is balanced, throughput capacity is improved, data flow is optimized, cache coordination capacity is improved, cache levels can flexibly adapt to access mode changes, and data storage stability and load balance are enhanced.

The invention relates to an intelligent metering box monitoring method, system and device and a storage medium, and the method comprises the steps: continuously collecting the operation data of an intelligent metering box in an offline state of the intelligent metering box, carrying out the abnormal trend recognition of the operation data through combining with a pre-trained edge side abnormality recognition model, and obtaining a local judgment result; abnormal record data are generated according to the local judgment result, the abnormal record data are cached in a local storage unit, and the abnormal record data comprise fault types, timestamps and index values; generating a communication connection request signal under the condition that the communication connection condition is met, and controlling the communication channel to establish network connection according to the communication connection request signal; and after the communication response is received, collecting the network signal strength, and uploading the abnormal record data to a remote management platform based on the network signal strength. The intelligent metering box has the effect of improving the monitoring reliability of the intelligent metering box.

The invention relates to the technical field of audio control, and discloses a low-delay audio input switching method and system, a storage medium and equipment, and the method comprises the steps: carrying out the parallel pre-initialization of a plurality of pieces of audio input equipment, and building an independent parallel audio data cache for each piece of equipment; monitoring the state of each audio input device and the audio stream quality in real time, and judging whether switching is triggered or not based on a multi-factor decision model; after the switching decision is triggered, seamless audio data stream switching is executed, and format unification processing and cross fade-in and fade-out transition are included; a unified equipment operation interface is provided through the hardware abstraction layer, and system resources are optimized and managed; a delay sensing closed-loop control mechanism is constructed, processing delay of each link is monitored in real time, a caching strategy, a processing algorithm and resource allocation parameters are dynamically adjusted, self-adaptive balance of low delay and high tone quality is achieved, and through the method, quick and smooth switching of audio input equipment is achieved, delay is remarkably reduced, and real-time audio experience is improved.

The invention relates to the technical field of communication, and discloses a flow control method, electronic equipment and a storage medium, and the method comprises the steps: responding to data transmission of a target node, configuring a first-level cache of the target node, and configuring a data cache position corresponding to the target node as the first-level cache; under the condition that the data volume in the first-level cache reaches a preset back pressure threshold value, switching a data cache position corresponding to the target node to a second-level cache, and performing flow control on the target node; wherein the second-level cache is configured to be a shared cache of all nodes transmitting data to the local node. According to the invention, the problem of cache overflow caused by traffic burst of the switching network node can be solved.

The invention discloses a data interaction self-adaptive method for a photovoltaic protocol converter, and particularly relates to the technical field of power grid dispatching cooperative control. The method comprises the following steps: monitoring and calculating a voltage instantaneous change rate of a grid-connected point of a power grid in real time, and comparing the voltage instantaneous change rate with a threshold value; when a threshold value is exceeded, synchronously collecting a current phase and generating a voltage and current phase difference change direction; extracting a voltage high-frequency component, analyzing frequency band energy distribution through wavelet packet decomposition, and calculating a Shannon entropy representing an energy concentration ratio; when the phase difference change direction accords with a preset power grid short-circuit fault feature and the Shannon entropy value is lower than a preset entropy threshold value, determining that a power grid transient event occurs; at the moment, a data caching mechanism of the protocol converter is stopped immediately, and a real-time stream transmission channel is activated; an emergency control instruction issued by a power grid dispatching system is directly transmitted to the photovoltaic inverter through the channel; and when the voltage instantaneous change rate is continuously lower than the preset threshold value for a preset duration, recovering the data caching mechanism of the protocol converter.

The invention discloses a depth operation implementation method and device for parallel pixels in the vertical direction, a medium, equipment and a product. The method comprises the following steps: mapping each channel group with a thread bundle containing NT threads; acquiring jumping step length of vertical direction access and parameter configuration of a sliding window operator; performing register resource allocation for each thread to form a sliding window data cache region; determining NH row starting point coordinates of the current scanning round; when the current scanning round is executed, in each column slice participating in calculation, pixel groups at NT row and column positions are scanned from each row starting point coordinate with the jump step length as the span, and the pixel groups are loaded to register groups of all threads in corresponding thread bundles in sequence, so that each thread can process the calculation task of the corresponding local sliding window view. According to the method, thread-level independent calculation task allocation is realized through a pixel parallel strategy among threads, and allocated hardware resources can be utilized to the maximum extent.

The invention belongs to the technical field of Ethernet high-speed interconnection, and provides a high-speed low-delay 10-gigabit switching method and system based on an FPGA, and the method comprises the steps: receiving Ethernet data frames, storing effective data frames in a data caching module, and generating a caching write-in address and a control signal; reading a destination address, a source address and a type field of the analyzed data frame from the data caching module, and updating a forwarding address table through a dynamic learning mode or a preset mode; based on the updated forwarding address table, a three-level assembly line framework is adopted to complete address searching; reading the data frame from the cache according to the forwarding decision, repackaging the Ethernet header information and the check code, and controlling the sending standard rate; and meanwhile, the sending rate is dynamically adjusted, and VLAN division, port rate and queue scheduling parameters are optimized in combination with an external configuration command. According to the invention, the onboard processor is utilized to cooperate with the FGPA to realize the fast search of the forwarding table, the residence time of the data packet in the switching unit is reduced, and the operation efficiency of the side application is improved.

The invention provides a multi-core GPU cache division method, architecture and data access method, relates to the technical field of graphics processor design, and aims to realize cross-core access performance system-level optimization and improve the performance of processing large-scale image data by introducing a cache allocation mechanism based on topology awareness. The method comprises the steps that a multi-core-grain GPU topological structure comprising a target computing core grain and at least one associated computing core grain is obtained, a to-be-divided far-end data cache of the target computing core grain is used for caching image data from a far-end video memory, and the to-be-divided far-end data cache is connected with the associated computing core grain through an inter-core-grain interconnection network; if the number of the calculation core particles contained in the multi-core-particle GPU does not exceed a first preset threshold value, the inter-core-particle hop count between each associated calculation core particle and a target calculation core particle is determined based on the topological structure, and then the corresponding capacity of the associated calculation core particles in the to-be-divided cache of the target calculation core particle is determined; and dividing the to-be-divided cache according to the capacity corresponding to each associated calculation core particle.

The invention belongs to the technical field of semiconductors, and discloses a multi-core GPU interconnection architecture and a self-adaptive cache allocation method thereof.The multi-core GPU interconnection architecture comprises a plurality of GPU clusters and a global cluster, the global cluster comprises a global router, a global scheduler, a directory, a memory and a plurality of GPU clusters, each GPU cluster is composed of a plurality of GPU cores, and the GPU cores are arranged in the global router. Each GPU core grain comprises a plurality of independent primary data caches, secondary data caches, a local router and a network interface, and the network interface judges whether a current request is processed by the GPU core grains in a GPU cluster or not according to whether a target address in a target node belongs to the GPU cluster or not, so that a high-level multi-core grain interconnection architecture supporting cross-cluster communication is formed. According to the method, performance is optimized by adapting to different access modes, private and shared cache modes are switched in real time, single data access delay is reduced, the overall system efficiency is improved, and the method is used for a multi-core-particle heterogeneous system with a plurality of GPUs.

The invention relates to the technical field of forest fire management, in particular to an integrated forest fire intelligent analysis method and system. The system comprises a background service system, a central intelligent analysis system and a mobile intelligent analysis system. The background service system is deployed in a cloud computing server cluster and is used for uniformly storing personnel information, fire scene information and geographic information data and realizing multi-source data fusion and authority management through a standardized API (Application Program Interface); the central intelligent analysis system is deployed in a high-performance computer, integrates a forest fire danger auxiliary decision-making model, a forest fire spreading trend prediction model, a force distribution dynamic display module and a collaborative plotting module, and supports fire spreading prediction and real-time decision-making instruction issuing based on multi-dimensional data such as weather, terrain and vegetation; the mobile intelligent analysis system realizes fire spreading trend analysis, mobile plotting and instruction receiving in an offline environment, supports offline data caching and calling in an emergency scene, and effectively improves forest fire emergency response efficiency and resource scheduling accuracy.

The invention discloses a multi-precision matrix calculation unit and a use method thereof, and relates to the technical field of integrated circuits, the multi-precision matrix calculation unit comprises a control logic unit, a cache module and a calculation array; wherein the control logic unit is used for configuring a computing array and controlling the cache module to read in and read out data; the cache module comprises three first cache sub-modules and one second cache sub-module; wherein the three first cache sub-modules are respectively used for caching a first to-be-processed matrix, a second to-be-processed matrix and a third to-be-processed matrix, and the second cache sub-module is used for caching a result matrix; and the calculation array is used for carrying out multiplication and addition operation on different types of to-be-processed matrixes to obtain a result matrix and writing the result matrix back to the cache module. The method can serve as a basic operation core for integrated processing of large-scale matrix multiplication and can also be integrated in processors such as RISC-V for matrix operation, universality is higher, and the method can adapt to fast and efficient calculation scenes.