12 results about "Memory working" patented technology

The application relates to the technical field of intelligent auditing, in particular to an artificial intelligence information auditing system and method based on a distributed micro-service architecture, which comprises the following steps: analyzing to-be-audited information at a gateway layer, extracting a lightweight decision context, the decision context comprising an information type, a semantic key frame and an emergency degree mark; binding a target micro-service instance according to the decision context, preloading the decision context to a memory work area of the target micro-service instance, triggering a distributed auditing engine to execute multi-modal analysis and generate an atomic auditing decision; and aggregating multiple atomic auditing decisions of the same information flow, generating a final global consistency decision through time window conflict resolution processing. The application improves the data volume compression ratio and reduces the bandwidth and storage pressure of the auditing system. Meanwhile, in combination with an information emergency degree dynamic calculation mechanism, the application realizes rapid and preferential response to emergent public opinion information.

The invention relates to a memory optimization method and device, a model training method and device, equipment and a vehicle, relates to the technical field of memories, and aims to solve the technical problem that a memory working state prediction result is inaccurate. The method comprises the following steps: acquiring memory state data of target equipment, wherein the memory state data comprises memory running state data and memory health state data of the target equipment; determining the working state of the memory according to the combined characteristics of the memory state data; the combined features are used for indicating the relevancy between the memory state data; the target optimization strategy of the memory is determined based on the working state of the memory, and the target optimization strategy is executed, so that the accuracy of the memory working state prediction result is improved.

The invention discloses a memory bank installation self-checking method, and belongs to the technical field of computer storage equipment detection. The method comprises the following steps of: separating a test signal adaptive to the working state of the memory to obtain an incident signal and a reflected signal, acquiring voltage of the incident signal and the reflected signal, converting the voltage into digital information, calculating a reflection coefficient and actual link impedance and deviation of each detection frequency point, comparing a set deviation threshold value to generate a detection result, analyzing abnormal information, and sending out a prompt of re-plugging or re-replacing. And meanwhile, synchronizing a result to a memory training process. According to the method, the installation state and the link impedance of the memory bank are accurately detected, the problem of poor contact caused by vibration or improper installation is timely checked, equipment operation faults are reduced, the memory training effect is optimized, and the equipment operation stability and the maintenance convenience are improved.

The present invention discloses a memory failure early warning method and device, which relates to the field of computer technology. The main purpose of the present invention is to describe the characteristics corresponding to the memory working state from multiple dimensions, so as to predict whether the memory has a failure risk. The main technical scheme of the present invention is: obtaining the abnormal log of the device; analyzing the time series change characteristics of the memory abnormal log according to a preset time period based on the memory abnormal log in the abnormal log; counting the operating state characteristics of the memory in the device based on the address information of the memory error in the abnormal log; fusing the time series change characteristics with the operating state characteristics into a memory failure early warning feature; using the early warning model to process the memory failure early warning feature to obtain the memory early warning information of the device.

The specification provides a memory power consumption configuration method, device and equipment and readable storage medium, the method comprises: in response to SMI interrupt, enter system management mode SMM, write function field for configuring memory power to memory power register;According to the target power parameter in the function field, configure the memory power consumption limit;If CPU usage is equal to or higher than the idle threshold, write the first power parameter as the target power parameter, and the memory runs at the first rated working frequency corresponding to the first power parameter;The idle threshold is pre-set;If the CPU usage is lower than the idle threshold, write the second power parameter as the target power parameter, and configure the memory working frequency to make the memory run at the second rated working frequency corresponding to the second power parameter;The second power is lower than the first power. Through the technical scheme of the specification, the power waste when the CPU usage is low can be effectively avoided.

This application proposes a method for adjusting memory operating parameters and a memory module, relating to the field of memory control technology. The method includes: performing at least one correction amount acquisition process on the memory module, and fitting all obtained single correction amounts to obtain a final correction amount, which is written to the storage medium associated with the memory module during the production phase, so as to be superimposed with the first operating parameters obtained from each initialization training during the runtime phase to determine the final operating parameters. The correction amount acquisition process includes: performing initialization training when the memory module is powered on to obtain a second operating parameter; testing the memory module with training code simulating target operating conditions to obtain error distribution information, and determining a third operating parameter accordingly; and determining the single correction amount based on the difference between the third operating parameter and the second operating parameter. This scheme can effectively obtain memory operating parameters with a larger operating margin during actual operation of the memory module without reducing memory startup efficiency.

A system (100) for handling requests comprises a set of memory banks (109) coupled to a memory controller (103) which includes a set of read queues (105 and 107), including one read queue currently designated as the priority read queue (105 or 107). The memory controller (103) loads read requests from an associated processor (101) into the set of read queues (105 and 107). To process the read requests, the storage controller (103) is designed to allocate the read requests from the priority read queue (105 or 107) based on the availability of the allocated memory bank (109) and, if it is not in the priority read queue (105 or 107), also depending on whether the read requests conflict with a recently allocated read request from the priority read queue (105 or 107).When executing a read request from the priority read queue (105 or 107), the storage controller (103) designates a different one from the set of read queues (105 and 107) than the priority read queue (105 or 107) if the read request was first in the priority read queue (105 or 107).

The invention discloses a memory and a control method thereof. The memory is used for providing corresponding system data for a processor, the memory works in a normal mode or a low-power-consumption mode, and the memory comprises a first working unit which works in the normal mode and comprises a first storage module, and the first storage module provides the system data corresponding to the current function of the processor; and the second working unit works in the normal mode and the low-power-consumption mode and comprises a second storage module, and when the memory starts to be switched from the low-power-consumption mode to the normal mode, the second storage module provides system data corresponding to the preselected function of the processor. By arranging the second storage module which still works normally in the low-power-consumption mode, when the memory is switched to the normal mode from the low-power-consumption mode, the second storage module can provide the system data corresponding to the preselected function without waiting for restarting of other modules, and the response speed when the memory is switched to the normal mode is increased.

The invention relates to the technical field of intelligent auditing, in particular to an artificial intelligence information auditing system and method based on a distributed micro-service architecture, and the method comprises the following steps: analyzing to-be-audited information at a gateway layer, and extracting a lightweight decision context which comprises an information type, a semantic key frame and an emergency degree mark; binding a target micro-service instance according to the decision context, pre-loading the decision context to a memory working area of the target micro-service instance, and triggering a distributed auditing engine to execute multi-modal analysis and generate an atomic auditing decision; and aggregating a plurality of atomic auditing decisions of the same information flow, and generating a final global consistency decision through time window conflict resolution processing. According to the invention, the data volume compression ratio is improved, and the bandwidth and storage pressure of the auditing system are reduced. Meanwhile, in combination with an information urgency degree dynamic calculation mechanism, rapid priority response to sudden public opinion information is realized.

The application provides a memory working parameter adjustment method and a memory module, and relates to the technical field of memory control. The method comprises the following steps: performing at least one correction amount acquisition process on the memory module, and fitting all single correction amounts obtained to obtain a final correction amount, which is written into a storage medium associated with the memory module in a production stage, so as to be superimposed on a first working parameter obtained through initialization training each time in a running stage, so as to determine a final working parameter. The correction amount acquisition process comprises the following steps: performing initialization training when the memory module is powered on to start, so as to obtain a second working parameter; testing the memory module by using a training code simulating a target working condition to obtain error distribution information, and determining a third working parameter according to the error distribution information; and determining a single correction amount according to a difference between the third working parameter and the second working parameter. According to the scheme, the memory starting efficiency can be reduced in the actual running of the memory module, and the memory working parameter with a larger working margin can be effectively obtained.

The application relates to a memory optimization method, a model training method and device, equipment and a vehicle, relates to the technical field of memory, and aims to solve the technical problem of inaccurate memory working state prediction results. The method comprises the following steps: obtaining memory state data of a target device, wherein the memory state data comprises memory running state data and memory health state data of the target device; determining the working state of the memory according to the combined features of the memory state data; the combined features are used to indicate the correlation between the memory state data; a target optimization strategy of the memory is determined based on the working state of the memory, and the target optimization strategy is executed, so that the accuracy of the memory working state prediction result is improved.

The application discloses a memory bank installation self-checking method and belongs to the technical field of computer storage equipment detection. The method separates the test signal suitable for the working state of the memory, obtains incident signals and reflection signals, collects the voltage conversion of the incident signals and the reflection signals into digital information, calculates the reflection coefficient, the actual impedance of each detection frequency point and the deviation, sets the deviation threshold, compares and generates a detection result, analyzes abnormal information, issues a re-plugging or replacement prompt, and synchronizes the result to a memory training process. The method realizes accurate detection of the installation state of the memory bank and the link impedance, timely troubleshoots poor contact problems caused by vibration or improper installation, reduces equipment operation failures, optimizes the memory training effect, and improves the equipment operation stability and maintenance convenience.