50 results about "Memory type" patented technology

The invention discloses a cross-host memory sharing method, system and device and a medium, the memory sharing system comprises a master node and a plurality of slave nodes, the memory sharing method is applied to the master node, and the method comprises the steps that a memory application request of a target slave node is received; applying for a target memory in a target memory sharing area according to a memory size requirement corresponding to the request, feeding back memory information of the target memory to a target slave node, so that the target slave node judges a corresponding memory type according to the memory information, and if a process corresponding to the target slave node executes a memory mapping method, sending the target memory to the target slave node. If yes, the target memory can be mapped to the proceeding virtual address space according to the target type and the offset corresponding to the target memory, so that the process can use the distributed target memory. Therefore, it can be guaranteed that when one node writes the memory, other nodes cannot synchronously write the memory, and then the data consistency of the shared memory accessed by multiple hosts is guaranteed.

The invention discloses a memory test method and device based on an AI technology and a medium, and the method comprises the following steps: 1) obtaining structure analysis data and memory type description information of a to-be-tested memory, and generating a test intention vector used for expressing a test target; 2) taking the test intention vector as an input to generate a test excitation sequence; 3) executing the test excitation sequence, and performing multi-cycle test on the storage array to form a multi-modal response feature set; 4) inputting the multi-modal response feature set into a graph neural network, performing fault type identification and causal path reasoning, and generating a fault tag sequence and a reasoning path graph; 5) based on the characteristic difference between the inference path diagram and the test excitation sequence, weight parameter updating of the depth generation model is carried out; and 6) generating a test excitation sequence based on the updated depth generation model to test the memory. The intelligent level and the test coverage rate of the memory test can be effectively improved.

The invention provides a storage type time-depth logging method, and relates to the technical field of logging control, and the method comprises the steps: obtaining an encoder, tension and acceleration data, and drawing an encoding curve, a tension curve and an acceleration curve. And receiving an effective movement time interval of single complete drilling rod operation intercepted by the user according to the curve characteristics. And for the original coding curve section of each interval, the total variation and the total duration of the coding value are kept unchanged, and the coding value and the time point are matched again according to the layered scale relationship between the encoder data and the actual displacement of the hook, so that a corrected target coding curve is obtained. And all the target coding curves are converted into time-depth curves according to the depth interval corresponding to each drill rod, and a time-depth file is generated through splicing according to the operation sequence of the drill rod operation event interval. According to the scheme, the technical problem of how to improve the precision of storage type time-depth logging depth measurement and the reliability of the whole system is solved.

The application relates to the technical fields of artificial intelligence and man-machine natural language dialogue, and provides a general memory management method and system based on a language model, which extracts memory information needing to be memorized from dialogue content with the language model, generates temporary memory, integrates the temporary memory to obtain persistent memory about a dialogue user, and is integrated into a dialogue process of the dialogue user and the language model to form memory of the dialogue user, so that the dialogue of the dialogue system is controlled, memory type classification management is performed according to the importance of the memory information in the persistent memory, so that the persistent memory contains short-term memory and long-term memory, the importance of the memory information in the persistent memory is updated and managed, and the short-term memory and the long-term memory are forgotten and upgraded, so that flexible and efficient storage and calling of user memory independent of the model type are realized, and the humanized, continuous and personalized dialogue experience in the man-machine dialogue process is improved.

A computer system includes physical memory devices of different types that store randomly-accessible data in a main memory of the computer system. In one approach, an operating system allocates memory from a namespace for use by an application. The namespace is a logical reference to physical memory devices in which physical addresses are defined. The namespace is bound to a memory type. In response to binding the namespace to the memory type, the operating system adjusts a page table to map a logical memory address in the namespace to a memory device of the memory type.

Various embodiments may include a Package on Package (PoP) having a bottom package comprising a system-on-chip (SoC) and a bottom substrate, a top package comprising a top substrate, a first memory die, and a second memory die, wherein the first and second memory dies are different in at least one of: memory type, memory density, or memory capacity, an interposer electronically connecting the top package and the bottom package, and a heat sink covering at least a portion of the top package. The SoC may include a non-uniform memory access (NUMA) mechanism configured to manage data interleaving, memory write requests, memory access requests across the first and second memory dies.

The application is directed to memory management in an electronic device. The memory includes a plurality of super blocks and receives a plurality of access requests. The electronic device stores information of an ordered list of superblocks in a cache, and each of a first subset of superblocks has a hint value and is ordered based on the hint value. In response to the plurality of access requests, the electronic device accumulates respective cue values for a first subset of the super blocks, and dynamically determines a location of the first subset of the super blocks in the ordered list of super blocks based on the respective cue values for the first subset of the super blocks. The ordered list of superblocks is pruned to generate a pruned list of superblocks. Based on the pruned list of superblocks, the electronic device translates a second subset of superblocks from the first memory type to a second memory type.

The application discloses an electroencephalogram signal driven adaptive storage method and electronic equipment, and relates to the technical field of electronic equipment, in particular to an electroencephalogram signal driven adaptive storage method and electronic equipment. The method comprises the following steps: acquiring first electroencephalogram signal data and brain blood oxygen monitoring data of a user; identifying the cognitive state of the user based on the first electroencephalogram signal data by using a first electroencephalogram signal data identification model; when the cognitive state is a concentrated state, extracting a first feature vector of the first electroencephalogram signal data; extracting a second feature vector of the brain blood oxygen monitoring data; performing cross-modal fusion on the first feature vector and the second feature vector to obtain a fusion feature vector, and identifying the memory type of the user based on the fusion feature vector; and storing prompt data of the current first prompt device in a corresponding storage space based on the memory type and a preset corresponding relationship between memory types and storage spaces. The application can adaptively store data according to the memory type of the user, so that the prompt data storage is more in line with the cognitive characteristics and actual use requirements of the user, and the utilization rate of storage resources is improved.

The application provides a system and method for parsing PLC intermediate code based on compilation technology and automatically generating data bridge description. The system comprises: a preprocessing module for normalizing the C intermediate code generated by matIEC; a lexical analysis module for converting the code into a Token stream; a syntax analysis module for constructing an abstract syntax tree; an abstract syntax tree processing module for traversing the AST to extract type definitions, fields and memory layouts, and converting them into an internal data model; a code generation module for serializing the data model into a standardized JSON file, including data item name, type, size, offset, memory type and nested sub-items; a version management module for automatically updating the compiler version number and embedding the JSON based on CMake during building. The application realizes full-automatic extraction and standardized output of PLC data structure, eliminates manual parsing, ensures accurate memory layout, supports cross-platform integration and version consistency verification.

The invention discloses a memory processing method and device, equipment, a storage medium and a program product. The method comprises the following steps: receiving a query request of a user, and identifying a query intention type of the query request; determining target weight configuration of a plurality of memory types based on the query intention type, wherein the plurality of memory types comprise plot memory, semantic memory, programmed memory and emotion memory; determining a semantic similarity score of the candidate memory data according to the semantic similarity and the target weight configuration, and determining a comprehensive score of the candidate memory data according to the semantic similarity score and the semantic strength score; and determining initial target memory from the candidate memory data according to the comprehensive score, determining associated memory data of the initial target memory based on a co-activation association relationship among the memory data, and taking the initial target memory and the associated memory data as target memory data.

The present application discloses a cross-host memory sharing method, system, device and medium. The memory sharing system includes a master node and several slave nodes. The memory sharing method is applied to the master node and relates to the field of memory sharing technology, including: receiving a memory application request from a target slave node; applying for a target memory in a target memory shared area according to the memory size requirement corresponding to the request, feeding back the memory information of the target memory to the target slave node so that the target slave node can determine the corresponding memory type according to the memory information. If the process corresponding to the target slave node executes a memory mapping method, the target memory can be mapped to the virtual address space according to the target type and the offset corresponding to the target memory so that the process can use the allocated target memory. In this way, it can be ensured that when one node writes to the memory, other nodes will not write to the memory synchronously, thereby ensuring the data consistency of multiple hosts accessing the shared memory.

The invention relates to the technical field of advertisement putting, and discloses an advertisement putting method and system for a network novel platform, and the method comprises the steps: extracting chapter texts, and generating a labeling sequence and a boundary point set through recalling marking words, tenses and visual angle conversion features, recognizing a main line and recalling narrative levels; according to the narrative direction, marking entry or exit memory type labels for the boundary points; intercepting text segments before and after the boundary, calculating an emotion intensity value, generating an emotion feature pair and obtaining an emotion fall value; screening boundary points of which the fall exceeds a threshold value and of which the types are entering recall, and forming a preferable set; according to the memory narrative emotion characteristics, matching advertisements with coordinated colors and lower intensity from an advertisement library, and formulating a boundary-advertisement scheme; monitoring the reading position of the user, and triggering advertisement display when entering the target interval; according to the invention, the collaborative unification of the narrative structure breakpoint, the emotion recovery opportunity and the advertisement content emotion is realized.

The present application relates to the technical field of terminals. Provided are an information recording method and an electronic device. The method comprises: acquiring first memory information, wherein the first memory information is information extracted on the basis of display content of a first interface and matching a preset memory type, and the memory type corresponds to at least one attribute item; and displaying the first memory information on an intelligent assistant. According to the solution, users do not need to memorize large amounts of information themselves, and desired information can be acquired by means of the intelligent assistant at any time according to requirements, thereby reducing the operation complexity of information acquisition and improving the user experience.

The application discloses a memory information monitoring method and device, electronic equipment and a storage medium. The method comprises the following steps: monitoring memory information update in a resource management service through a central processing unit temperature monitoring service; if it is determined that the memory information in the resource management service is updated, obtaining the updated memory information; and if it is determined that the memory type of the updated memory information is different from a default memory type, modifying the memory name of the updated memory information to distinguish the memory type of the updated memory information. The technical scheme of the application can monitor different types of memory information without affecting the system running efficiency.

The application relates to a radio frequency power amplifier linearity improvement method, satisfies the requirement of a high-order modulation communication system on the linearity of a memory type power amplifier, effectively solves the problem of signal distortion caused by the nonlinearity of a radio frequency power amplifier, first, a modeling method is designed to effectively reflect the memory effect of the power amplifier and accurately describe the input-output relationship of the power amplifier, thereby providing support for subsequent predistortion design; then, a predistortion scheme is applied to adjust the input signal on the basis of the accurate model, and the predistortion scheme has the advantages of simple structure, fast calculation speed and relatively easy realization process; in addition, considering the aging and other problems in the actual use process of the device, a real-time updating measure for the predistortion adjustment scheme is designed, the adaptability of the whole system is increased, and the shortcoming that the memory type power amplifier model is only a mathematical model and cannot describe the changes in actual application is made up.

Provided are systems, methods, and apparatuses for secure in-memory data prefetch for wide-IO NAND memory. In one or more examples, the systems, devices, and methods include allocating a memory region of a first memory type based on an allocation command; receiving, at a controller of the first memory type and from an application of a host, a load instruction configured for a second memory type different from the first memory type; converting a memory address, of the second memory type, from the second memory type to a converted memory address of the first memory type; determining the converted memory address matches a memory address of the memory region; fetching prefetch data from the memory region based on predicting that the application will use the data based on the load instruction; and providing the prefetch data to the application of the host based on the load instruction.

The invention provides an information recording method and electronic equipment, and relates to the technical field of terminals. The method comprises the steps that first memory information is obtained, the first memory information is extracted according to display content of a first interface and matched with a preset memory type, and the memory type corresponds to at least one attribute item; and displaying the first memory information on the intelligent assistant. According to the scheme, the user does not need to memorize a large amount of information by himself / herself and can acquire the required information through the intelligent assistant at any time according to requirements, so that the operation complexity of information acquisition can be reduced, and the user experience is improved.

The invention provides a memory type determination method, device and equipment, and belongs to the field of data processing.The method comprises the steps that a target server and a target running program are determined, the target server adopts a non-uniform memory access architecture, the non-uniform memory access architecture comprises a plurality of nodes, and each node comprises a central processing unit (CPU) and a memory; first access performance of a target CPU executing the target running program in a first simulation scene and second access performance of the target CPU in a second simulation scene are determined, the first simulation scene indicates that the target CPU accesses memories of other nodes, the second simulation scene indicates that the target CPU accesses a memory of a local node, and the target CPU belongs to CPUs included in the multiple nodes; and determining a memory type corresponding to the target running program according to the first access performance and the second access performance, wherein the memory type comprises a small page memory or a large page memory. Therefore, the access performance of the CPU can be improved.

A system includes a camera sensor; a first memory component comprising a first memory type; a second memory component comprising a second memory type, wherein the second memory type has a higher access latency than the first memory component; a memory sub-system comprising a third memory component of a third memory type, wherein the third memory component has a higher access latency than the first memory component; and a processing device, operatively coupled with the first memory component, the second memory component, and the memory sub-system, to perform operations including: monitoring a capacity usage status of the first memory component; monitoring a dirty level of the second memory component; determining whether a combination of the capacity usage status and the dirty level satisfies a threshold criterion; and responsive to determining that the combination satisfies the threshold criterion, switching from sending data from the first memory component to the second memory component to sending the data from the first memory component to the memory sub-system, the data comprising frames received from the camera sensor.

The embodiment of the invention provides a memory recall and task processing method, electronic equipment and a storage medium, and relates to the technical field of computers, a plurality of pre-stored memory fragments related to a user are obtained, and the memory fragments comprise content in a historical text input by the user; for any memory fragment in the plurality of memory fragments, determining a memory type to which the memory fragment belongs, and determining first recall evaluation information corresponding to the memory fragment based on the memory type corresponding to the memory fragment, the first recall evaluation information comprising at least one of a target timeliness value and a target importance value; and recalling the target memory fragment from the plurality of memory fragments based on the first recall evaluation information corresponding to the plurality of memory fragments, so that the recall accuracy of the memory fragments can be improved.

A computer system includes physical memory devices of different types that store randomly-accessible data in a main memory of the computer system. In one approach, an operating system allocates memory from a namespace for use by an application. The namespace is a logical reference to physical memory devices in which physical addresses are defined. The namespace is bound to a memory type. In response to binding the namespace to the memory type, the operating system adjusts a page table to map a logical memory address in the namespace to a memory device of the memory type.

The invention discloses a multi-modal information hierarchical compression and memory type retrieval method based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of video data, image data, audio data and text data of each piece of sample data; then clustering analysis is carried out on the preprocessed video data, the preprocessed image data, the preprocessed audio data and the preprocessed text data to obtain a clustering analysis result of each kind of data, and different data compression is carried out on each piece of data based on the clustering analysis result of each kind of data; therefore, parts with different importance degrees in each type of data can be better stored, and the storage effectiveness of important data is improved while the storage efficiency is improved. And meanwhile, the clustering process can also be used as an index element when the data is retrieved, so that the accuracy and the retrieval efficiency when the data is retrieved are improved.

The embodiment of the invention provides a memory allocation method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps of obtaining algorithm complexity of a current data processing task and a pre-applied memory size, determining a target memory type used for executing the current data processing task according to a matching relation between the algorithm complexity and a preset memory type threshold value, and executing the current data processing task if residual memory space of the target memory type is larger than or equal to the pre-applied memory size. And if not, allocating the target memory type to the current data processing task. Therefore, in the execution process of the data processing task, the memory type required by the data processing task can be dynamically adapted, the performance advantages of different types of memories are fully played, and the task execution efficiency is further improved.

This invention discloses a memory testing method, device, and medium based on AI technology, comprising the following steps: 1) obtaining structural analysis data and memory type description information of the memory to be tested, and generating a test intent vector for expressing the test target; 2) using the test intent vector as input, generating a test stimulus sequence; 3) executing the test stimulus sequence to perform multi-cycle testing on the memory array, forming a multimodal response feature set; 4) inputting the multimodal response feature set into a graph neural network to perform fault type identification and causal path reasoning, generating a fault label sequence and an inference path graph; 5) updating the weight parameters of a deep generative model based on the feature differences between the inference path graph and the test stimulus sequence; and 6) generating a test stimulus sequence based on the updated deep generative model for memory testing. This invention can effectively improve the intelligence level and test coverage of memory testing.

The invention discloses an agent memory management method based on a multi-level architecture, electronic equipment and a computer program product. The method comprises the following steps: constructing a context message containing a dialogue message pair; extracting a group of candidate memory sets from the context message; performing importance evaluation on each candidate memory in the candidate memory set to obtain an importance score of each candidate memory; determining a storage level of each candidate memory based on the importance score and the memory type of each candidate memory; generating a semantic vector and a time vector for each candidate memory, and fusing the generated semantic vector and time vector to obtain a multi-dimensional vector; for each candidate memory, calculating the relevancy between the candidate memory and the multi-dimensional vector of each memory in the candidate memory to obtain a similar memory subset; comparing the candidate memory with the similar memory subset by using a large language model, and determining a memory operation to be executed; and performing a memory operation on the new candidate memory.

Embodiments of the present application disclose a memory allocation method and electronic device, relating to the field of memory management technology, and providing a memory allocation solution for a CXL memory pool to improve the accuracy of memory allocation within the CXL memory pool. The method comprises: receiving a memory request from a computing device, wherein the memory request includes allocation request information and memory requirement information, wherein the allocation request information indicates attribute indicators of a memory expansion device requested by the computing device, wherein the attribute indicators are latency indicators or bandwidth indicators; the memory requirement information indicates memory indicators requested by the computing device, wherein the memory indicators include memory size and memory type; determining a target memory expansion device from the CXL memory pool whose category matches the attribute indicators; and allocating memory that meets the memory requirement information to the computing device from the target memory expansion device.

The application discloses a memory allocation management method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: in response to a page fault exception caused by a virtual machine process accessing a user space, allocating physical memory for the user space, and obtaining a memory type identifier of the physical memory; in the case that the memory type identifier is a preset identifier, judging whether the physical memory is idle memory, and in the case that the physical memory is not idle memory, performing a zero operation on the physical memory, so that the physical memory becomes idle memory; wherein the read bandwidth of the physical memory with the preset identifier is greater than the write bandwidth. The embodiment can greatly improve the creation and startup speed of a virtual machine based on a memory with a read bandwidth greater than a write bandwidth.

The application discloses a fuzzy wind power system robust control method based on a dynamic memory event triggering mechanism and belongs to the technical field of automatic control of wind power generation systems, which comprises the following steps: constructing a T-S fuzzy model of a multi-region DFIG wind power system considering random faults of a controller and state time delay; designing a proportional-integral type controller structure; introducing a memory type event triggering mechanism based on a dynamic threshold and a historical error variable; and constructing a robustness criterion by using a Lyapunov-Krasovskii functional and a linear matrix inequality method. The application realizes unified guarantee of system control performance, robustness and stability in a communication resource limited environment.

Various embodiments may include a Package on Package (PoP) having a bottom package comprising a system-on-chip (SoC) and a bottom substrate, a top package comprising a top substrate, a first memory die, and a second memory die, wherein the first and second memory dies are different in at least one of: memory type, memory density, or memory capacity, an interposer electronically connecting the top package and the bottom package, and a heat sink covering at least a portion of the top package. The SoC may include a non-uniform memory access (NUMA) mechanism configured to manage data interleaving, memory write requests, memory access requests across the first and second memory dies.