167 results about "Memory performance" patented technology

The invention relates to a method for storing data, a computing device, a storage medium and a program product. The method comprises the following steps: generating a data acquisition instruction in response to a predetermined condition; the method further comprises the steps that in response to the data collection instruction, data collection is carried out so as to obtain target data. And determining a storage strategy corresponding to the target data based on the data attribute of the target data and the storage state corresponding to the memory. In addition, the method further comprises the step of storing the target data based on the storage strategy. Through the mode, the optimal storage strategy can be selected for the to-be-stored data according to the real-time data characteristics and the state of the memory, so that the performance and the capacity of the memory can be fully utilized, and the storage efficiency is improved.

The embodiment of the invention provides a memory voltage processing method and device, a storage medium and electronic equipment, and relates to the field of computers.The memory voltage processing method comprises the steps that based on a substrate management controller integrated on a server mainboard, first standard voltage output by a target power supply chip is obtained, the first standard voltage provides memory voltage for a group of memory modules of the server; transmitting the first standard voltage to a target operating system in response to a first triggering operation on the voltage adjusting instruction; determining N preset voltages based on the first standard voltage; based on the N preset voltages, memory performance testing is executed, a target testing result is obtained, and the target testing result comprises N performance indexes corresponding to the N preset voltages; determining a target preset voltage from the N preset voltages based on the N performance indexes; and modifying the power supply voltage output by the target power supply chip from the first standard voltage to the target preset voltage.

Techniques are provided for determining a qualitative, quantitative and / or categorical assessment of one or more users and / or images with respect to one or more populations. The eye movement data of the user may be obtained with respect to each image of the one or more images displayed for a period of time. One or more memory performance measures and / or one or more salience performance measures may be determined using the eye movement data with respect to the one or more regions of the one or more images for one or more of predetermined time ranges of the period of time. The quantitative, qualitative and / or categorical assessment of the user and / or images presented may be determined with respect to one or more populations, using the one or more memory performance measures and / or one or more salience performance measures.

The invention provides a computing power evaluation method and device, equipment, a medium and a program product. The method comprises the following steps: dividing the running time of target equipment into a plurality of sub-time regions; collecting performance data of the target equipment in each sub-time region; calculating a performance evaluation value of each sub-time region based on the performance data in each sub-time region; the performance evaluation values comprise a processor performance evaluation value, a memory performance evaluation value and a storage performance evaluation value; collecting system monitoring data of the target equipment in each sub-time region; based on the system monitoring data of the target equipment in each sub-time region, calculating an infrastructure comprehensive quality evaluation value of each sub-time region; and based on the infrastructure comprehensive quality evaluation value, the processor performance evaluation value, the memory performance evaluation value and the storage performance evaluation value in each sub-time region, calculating a comprehensive calculation power evaluation value of the target equipment in the operation time. By adopting the method provided by the embodiment of the invention, the accuracy of the computing power evaluation method can be improved.

The invention provides a memory performance monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of performance monitoring. The method comprises the following steps: collecting a plurality of pre-selected performance events; dividing the performance events into different signal categories based on the physical signal characteristics corresponding to the performance events; assigning the performance events to a predefined event group; and based on the signal category of each performance event, performing statistical operation corresponding to the signal category on the performance events in the event group. According to the scheme, classification processing of the performance events can be realized, and grouping statistical operation is performed by using the signal categories, so that the accuracy of memory performance monitoring and the resource utilization efficiency are improved.

The invention discloses a memory performance detection method, device and equipment and a memory medium, and relates to the technical field of memory performance detection. Memory with the same capacity of a data path port of a memory box is mapped to an endpoint port, the mapped memory is converted into an extended memory which can be identified by a host node, and then the memory performance of the extended memory is subjected to a consistency test, so that a memory mapping relationship can be quickly and effectively established; according to the embodiment of the invention, the host nodes can schedule the memory capacity required by the host nodes in the memory box, and the inconsistency caused by different mapped memory spaces is eliminated by configuring extended memories with the same capacity for the host nodes, so that the memory performance of the plurality of host nodes tends to be consistent on the premise, and the effectiveness of the consistency test is improved.

Automated memory overclocking is described. In accordance with the described techniques, one or more sets of overclocked memory settings of a memory are automatically selected for performance testing and stability testing of the memory. The one or more sets of the overclocked memory settings are tested for performance of the memory and a performance indication is output for each of the one or more sets of the overclocked memory settings. The one or more sets of the overclocked memory settings are tested for stability of the memory and a stability indication is output for each of the one or more sets of the overclocked memory settings. One of the one or more sets of the overclocked memory settings are selected as optimized overclocked memory settings for the memory.

Logic to provide improved endurance, performance, and power optimizing capabilities for a resistive memory, ferro-electric RAM (FeRAM) memory, or embedded flash memory is disclosed herein. In one embodiment, a memory subsystem comprises a resistive memory array; an adaptive aggregation memory buffer that has configurable settings for optimizing endurance, power, or performance of the memory subsystem; an endurance management and control logic (EMCL) coupled to the adaptive aggregation memory buffer; and an integrated processor coupled to the EMCL. At least one of the integrated processor and EMCL is configured to determine whether memory requests to a particular memory region during a time window can be aggregated into an aggregate memory request and to optimize memory settings, and to cause the aggregate memory request and memory settings to be sent to the resistive memory array, FeRAM memory, or embedded flash memory to optimize parameters including memory performance and memory endurance.

The invention provides an advanced memory performance monitoring and anomaly detection method, system and device, and relates to the technical field of memory monitoring, and the method comprises the steps: capturing a current memory operation executed by a monitored kernel and corresponding operation data through a memory delay monitoring module based on a kernel tracking point mechanism, the memory delay alarm module is used for judging whether memory delay alarm is performed for a monitored kernel; under the condition that the judgment result is yes, constructing a memory delay diagnosis event corresponding to the monitored kernel based on the operation data through a diagnosis event generation module; and through a diagnosis event distribution module, the memory delay diagnosis event is added to the to-be-processed diagnosis event queue, so that the memory diagnosis framework processes the memory delay diagnosis event contained in the to-be-processed diagnosis event queue, and a performance monitoring and anomaly detection result corresponding to the monitored kernel is obtained. According to the method, the monitoring fine granularity can be remarkably improved, and the false alarm and missing alarm conditions in the performance monitoring and abnormity monitoring process are reduced.

The invention provides an AR (Augmented Reality) adaptive scene memory training system and method based on electroencephalogram neural feedback. The system comprises head display equipment and an EEG (Electroencephalogram) data acquisition module, the data processing and prediction module is used for outputting a memory state prediction result of the current test EEG to the self-adaptive adjustment and feedback module; the self-adaptive adjustment and feedback module is used for judging the memory performance of the user based on the familiarity and recall index in the memory state prediction result of the current test round, determining the required task scene difficulty parameter and the mnemonic strategy according to the memory performance of the user, and finally generating an adjustment instruction according to the task scene difficulty parameter and the mnemonic strategy; and a Unity 3D engine platform. According to the invention, a set of self-adaptive scene memory training system is constructed based on EEG (electroencephalogram) and AR (augmented reality) technologies, and the defects of low ecological efficiency, lack of real-time feedback and difficulty in personalized adjustment of an existing scene memory intervention system are effectively overcome.

Verbal memory impairment is a common symptom of temporal lobe epilepsy (“TLE”). The ability to encode and recall verbal memories can be probed with the classic free recall task. This study had three overarching hypotheses: 1) increased seizure frequency will lead to decreased verbal memory, 2) stimulation will modulate memory performance, and 3) stimulation will modulate the underlying neural correlates of memory. The study investigated these hypotheses in patients receiving chronic DBS to bilateral ANT. Recordings were obtained from individuals with drug resistant mesial TLE implanted with an investigational MEDTRONIC SUMMIT RC+S™ sensing and stimulation device. As patient seizure diaries are notoriously inaccurate, the patient's continuous local field potential (“cLFP”) was scored for seizures using a validated seizure classifier with trained epileptologist review, resulting in a reliable seizure diary. The subjects completed free recall memory tasks in their home environment with cLFP and behavioral data streamed to a handheld device and cloud repository.Through implementation of generalized linear mixed models (GLMM), the study was able to determine that ANT stimulation modulates memory performance, but changes in the seizure rate were not predictive of changes in memory performance. Analyzing the continuous local field potential recordings from these tasks, the study found that spectral power in the theta frequency band in the left ANT and hippocampus correlated with acute memory performance and chronic therapeutic stimulation frequency received.Not all patients are candidates for devices with chronic sensing capabilities, and this study indicates that changes in verbal memory performance can provide a suitable metric of therapy effectiveness in lieu of a reliable, objective seizure diary. But for those who do receive these and similar devices, thalamic-hippocampal spectral activities can be used to track and predict memory performance acutely and chronically, as well as predict the effect of therapeutic deep brain stimulation. Our study demonstrates chronic improvement of verbal memory with a new biomarker-based technology for remote task administration and modulation of the associated neural activities.

The invention provides a front-end memory optimization method and system, electronic equipment and a storage medium. The front-end memory optimization method comprises the steps that in the page initialization stage, multiple pieces of first data needing to be rendered are acquired; determining a label of each piece of rendered first data; the first data of which the label is a first type label is taken as second data, and the first type label is a label for automatically performing event monitoring; and rendering the second data into third data with a second type label according to a preset front-end framework, and displaying the third data on the page, the second type label being a label which does not perform event monitoring. According to the method and the device, the memory performance bottleneck caused by page rendering is solved, such as the problems of large memory usage, page lagging, white screen and long page rendering time.

The invention discloses a garbage collection method, system and device for a multi-core CPU (Central Processing Unit) memory and a medium. The method comprises the following steps: acquiring a request instruction of a host; controlling a protocol layer CPU to apply for a target cache interval according to the request instruction; writing the target data into the target cache interval, and recording the target write-in data volume through the protocol layer CPU; under the condition that the target write-in data volume is greater than or equal to a write-in threshold value, the protocol layer CPU generates a garbage collection trigger signal, garbage target collection time and a target cache interval for stopping application; the garbage collection trigger signal is sent to an FTL layer CPU to start garbage collection and monitor the garbage collection state in real time; and when the garbage recycling state represents that the garbage recycling number is larger than or equal to the garbage target recycling number or the garbage recycling time is larger than or equal to the garbage target recycling time, garbage recycling is quitted. The timeliness and accuracy of garbage collection can be ensured, and the performance of a memory is improved.

A memory includes a local control circuitry that manages refresh transactions using a set of sense amplifiers separate from those used for access (read and write) transactions. The local control circuitry interrupts refresh transactions to prioritize access requests, thereby offering improved memory performance. The local control circuitry also divides refresh transactions into phases and periods based on whether the refresh transaction requires access to bitlines used for read and write access. This division allows the local control circuitry to interleave and interrupt refresh transactions with access transactions in a manner that minimizes access interference.

The invention provides a memory configuration method and device, electronic equipment and a storage medium, and is applied to the technical field of computers, the method configures a memory based on a pressure test result of the memory, if the memory passes a pressure test, a DM function of the memory is enabled, the influence of a non-aligned write request on memory performance is reduced, and on the contrary, the memory performance is improved. If the memory does not pass the pressure test, the DBI function of the memory is enabled, the influence of the high-speed signal crosstalk of the bus on the stability of the memory is reduced by utilizing the characteristics of the DBI function, and meanwhile, the power consumption of the memory is reduced, so that the memory configuration method provided by the invention flexibly adjusts the configuration mode of the memory based on the pressure test result of the memory; the memory is ensured to be matched with the application environment, and the influence of the application environment is overcome, so that the electronic equipment is in a performance optimal state in the application environment, the overall performance of the electronic equipment is ensured to meet the use requirement of a user, and the use experience of the user is improved.

The embodiment of the invention provides a verification data processing method and equipment of a memory and a storage medium. When data in a target cache line is written into a plurality of data chips in a memory, the data in the target cache line can be coded according to a corresponding channel (data queue, DQ) region when the data is written into the data chips by adopting a coding mode corresponding to a target data verification algorithm, so that the data in the target cache line can be coded. And obtaining the first number of verification units and a plurality of information data units corresponding to the plurality of data chips. Wherein the target cache line is integrally coded, so that the data volume of the verification data can be effectively reduced. In the data reading stage, the information data units in the single channel area in any target data chip can be verified and / or corrected according to the first number of verification units, verification and / or correction of bounded errors in the isolation boundary are / is achieved under the condition that verification data is less, the cost of the memory is reduced, and meanwhile the memory performance is improved. The stability of the memory is ensured.

As part of the erase operation for a memory block, one or more post-erase tests can be incorporated into the erase operation to see whether the block has grown any defects. After erasing a block and verifying the erase, the post-erase tests can be performed on the block. As these test involve biasing the block and performing a sensing operation, these post erase tests come with a time penalty. To reduce the associated time penalty and improve memory performance while incorporating the defect tests into the erase process, when biasing the memory array for the post-erase defect tests different ramp rates can be used. In particular, faster ramp rates for bias levels, such those applied to the word lines of the block, are used for the post-erase tests than are used for the same bias level when performing the standard read, program verify, or read verify operations.

The embodiment of the invention provides a multi-channel differential pressure real-time measurement method and system, through cooperative interaction of a PS end and a PL end, the PS end receives and identifies an instruction of an upper computer, the PL end is responsible for instruction execution, corresponding closed-loop communication logic is formed, and the accuracy and reliability of data are improved. Besides, read-write parallelization is realized, two ports of the memory are controlled to perform independent data read-write through switching of identification values, read-write operations of the first port and the second port are completely separated, throughput is greatly improved, the two ports adopt a write priority mode and an independent address space design, read-write conflict risks are eliminated, and the memory performance is improved. And the number of concurrent detection channels and the detection frequency are improved.

The present invention relates to the technical field of deep learning. Provided are a tensor program optimization method and apparatus. The method comprises: acquiring a computation graph corresponding to a tensor program to be optimized; using a performance model to obtain a computation performance limitation operator and an access and storage performance limitation operator in the computation graph; calling a hardware operator library to compute the computation performance limitation operator, so as to generate a first code; using a graph intermediate representation to optimize the access and storage performance limitation operator, so as to generate a second code, wherein an edge in the graph intermediate representation represents a data slice on a specified memory hierarchy, and a node in the graph intermediate representation represents a hardware instruction or a group of hardware instructions and is used for executing a specified operation; and merging the first code with the second code, so as to generate an optimized tensor program. The tensor program optimization method and apparatus provided in the present invention can optimize memory performance, and the optimization effect thereof is more efficient than that of the prior art.

The invention discloses a memory performance test method and device, a readable storage medium and electronic equipment, and the method comprises the steps: obtaining a function script selected by a user, controlling first equipment to carry out user simulation operation according to the function script, and collecting a system debugging log; analyzing the system debugging log to obtain a log command group set; converting all the log command groups in the log command group set into test commands to obtain a test command set; and sequentially sending the test commands of the test command set to at least one to-be-tested device, and indicating the to-be-tested device to complete the test. The corresponding system debugging log is collected after the user operation is simulated on the first equipment through the function script, the system debugging log is converted into the test command for equipment testing, the test command can be automatically distributed to the corresponding to-be-tested equipment, the labor cost is reduced, meanwhile, the uncertainty caused by manual testing is reduced, and the test efficiency is improved. Therefore, the test efficiency and precision are improved.

The invention relates to the technical field of large models, in particular to a method and system for improving the memory amount of a large model, and the method comprises the steps: deploying a monitoring module in a training or reasoning process, carrying out the statistics of the number of memory errors and the total task amount of each component, and calculating the initial memory performance of the components; based on the performance evaluation result of each component, quantifying the overall initial memory amount of the model as an optimization starting point; utilizing a dynamic sensitivity analysis algorithm to mine the influence degree of each component parameter on the memory performance, and calculating a dynamic sensitivity factor; and in combination with the sensitivity factor, the current parameter state and the memory performance, model parameters are adaptively adjusted through dynamic parameter optimization and an iterative lifting algorithm, an iterative verification mechanism is introduced, and the memory ability of each component and the whole machine is subjected to closed-loop optimization. According to the method, fine quantization and parameter-level dynamic regulation and control on the memory performance of the model are realized, and the memory stability and long-term dependence processing capability of the large model in tasks such as knowledge keeping and context understanding are effectively improved.

The invention discloses a server memory installation detection method, device and equipment, and relates to the technical field of servers, the method comprises the following steps: obtaining memory slot information of a target central processing unit in a server; determining current memory insertion information of the target central processing unit according to the memory slot information; obtaining a memory interpolation detection result according to the target memory interpolation information of the target central processing unit and the current memory interpolation information; if the memory interpolation detection result is a non-target interpolation, outputting memory interpolation prompt information corresponding to the target memory interpolation information; therefore, the current installation state, obtained in real time, of the memory of the CPU can be compared with the preset optimal interpolation method corresponding to the memories, so that when the current installation state is not the optimal interpolation method, an optimization prompt suggestion of the memory interpolation method is provided for a user, the user is prompted to install the memory in the server in a better mode, and the user experience is improved. Therefore, the memory performance of the server is improved.

The invention provides a system for evaluating App memory performance, comprising: at least one first device having a memory and installed with an App, the first device being configured to generate and output first data, the first data being related to configuration parameters of the first device; a first server configured to pre-process the first data from the first device, and generate and output the processed first data; at least one second device having a memory and installed with an App, the second device configured to simulate a usage scenario of the App on the first device based on the processed first data, thereby generating and outputting second data, the second data being related to memory performance of the App on the second device; the second server is configured to be capable of generating performance evaluation data according to the second data and completing evaluation of the memory performance of the App on the first equipment; according to the system, the real environment of the user can be better simulated, and the accuracy of App memory performance evaluation is effectively improved.

Forming planar resistive memory devices on metal vias that are planed level with the surrounding insulating material may transfer dishing or other surface imperfections in the surface of the metal vias throughout the layers of the memory cell and degrade the performance of the device. A bottom electrode having a "hammerhead" shape may be formed by leaving a top portion of the metal layer over the insulating layer instead of polishing down to the insulating layer. The top portion of the electrode may be oxidized to form the switching layer for the memory cell itself. This hammerhead electrode may have a substantially flat surface on which to form the layers of the planar memory cell, resulting in better memory performance and heat dissipation. When oxidized, the hammerhead electrode also eliminates the metal / metal-oxide interface between the bottom electrode and the switching material.

Logic to provide improved endurance, performance, and power optimizing capabilities for a resistive memory, ferro-electric RAM (FeRAM) memory, or embedded flash memory is disclosed herein. In one embodiment, a memory subsystem comprises a resistive memory array; an adaptive aggregation memory buffer that has configurable settings for optimizing endurance, power, or performance of the memory subsystem; an endurance management and control logic (EMCL) coupled to the adaptive aggregation memory buffer; and an integrated processor coupled to the EMCL. At least one of the integrated processor and EMCL is configured to determine whether memory requests to a particular memory region during a time window can be aggregated into an aggregate memory request and to optimize memory settings, and to cause the aggregate memory request and memory settings to be sent to the resistive memory array, FeRAM memory, or embedded flash memory to optimize parameters including memory performance and memory endurance.

The application discloses a memory abnormality early warning method and device based on data mining and a medium, relates to the technical field of memory abnormality early warning, and comprises the following steps: performing semantic element mapping on memory running semantic data, and outputting a semantic state time sequence vector; performing cross-domain time sequence alignment and associated feature extraction on the semantic state time sequence vector and memory performance index data, and outputting memory associated rules; performing cause-effect analysis on the memory performance index data, constructing a graph structure on a cause-effect edge set through a PC algorithm, and outputting a memory index cause-effect graph; performing memory behavior deduction on real-time memory running semantic data according to the memory associated rules, outputting memory abnormality early warning data, performing cause-effect tracing and report integration on the memory abnormality early warning data through the memory index cause-effect graph, and outputting a memory abnormality early warning report. The application realizes interpretable early warning and root cause positioning of memory abnormality through the cooperation of semantic state time sequence vector construction and memory index cause-effect graph generation.

The present disclosure relates to the field of integrated circuits and discloses a command generation circuit and memory. The command generation circuit includes a command receiving module and a command decoding module. The command receiving module is configured to receive a first command address signal, a first chip select signal, and a clock signal, and sample and register the first command address signal and the first chip select signal based on the clock signal to obtain a second command address signal and a second chip select signal. The command decoding module is connected to the command receiving module and configured to receive and decode an on-chip termination command based on the second command address signal and the second chip select signal. The on-chip termination command is used to control on-chip termination in a non-target chip when the target chip is performing any one of at least two operations. The present disclosure can simplify circuits, reduce circuit power consumption and occupied area, and thus improve memory performance.

The application relates to the technical field of artificial intelligence chips, and discloses a data processing method and device, a processor and electronic equipment. First, in the case of loading the block data of input data to a thread private register, a first jump step required for rearranging the block data is determined based on the block size of the input data in the first dimension; second, the block data is read by jumping according to the first jump step, and the read input elements are rearranged and loaded into the thread private register, so that the block data is stored in the thread private register in a transposed manner, and the thread direction is mapped on the second dimension, thus obtaining the data basis of convolution-related calculation, and then performing convolution-related calculation based on the transposed data in the thread private register and the weight data in the thread private register, so that repeated data reading in the calculation process is reduced, and the operator is changed from a memory performance bottleneck operation to a calculation performance bottleneck operation.

A memory includes local control circuitry that manages refresh transactions using a set of sense amplifiers separate from the sense amplifiers used for access (read and write) transactions. The local control circuitry interrupts refresh transactions to prioritize access requests to provide improved memory performance. The local control circuitry also divides the refresh transaction into stages and periods based on whether the refresh transaction needs to access bit lines for read and write accesses. This partitioning allows local control circuitry to interleave and interrupt refresh transactions from access transactions in a manner that minimizes access disturbances.

An embodiment of the present disclosure provides a memory, which includes a buffer unit, and the buffer unit includes multiple sub-buffer units, wherein: the wiring layer of the memory includes at least a first wiring layer and a second wiring layer, and the second wiring layer is located above the first wiring layer, a first type of signal wiring is formed in the first wiring layer, and a second type of signal wiring is formed in the second wiring layer; the multiple sub-buffer units include multiple first sub-buffer units and multiple second sub-buffer units, and the multiple first sub-buffer units are connected to the first type of signal wiring, and the multiple second sub-buffer units are connected to the second type of signal wiring, wherein every two first sub-buffer units are distributed on both sides of a second sub-buffer unit, thereby making the connection of the first type of signal wiring and the second type of signal wiring more convenient and ensuring signal integrity, thereby improving memory performance and saving memory area.