24 results about "Atomic data" patented technology

The invention belongs to the technical field of data management and intelligent analysis, and particularly relates to a data loading and conversion processing method under a lake-warehouse fusion architecture, which comprises the following steps of: after an externally uploaded file is received, performing compatibility verification and content verification on the externally uploaded file in sequence; identifying that the tables and the partitions which are influenced by data loading and need to be synchronously updated are added, executing atomic data loading operation, synchronously updating the tables and the partitions in the table and the partitions, and generating corresponding version numbers for each table and each partition at the same time; for a data block set under the lake-warehouse fusion architecture, performing hierarchical adjustment according to the access popularity of the data block set; income-cost evaluation is carried out on each data block, and the data blocks needing to be subjected to Z-sequence clustering rearrangement are recognized and added into a requeuing column; and performing Z-sequence clustering rearrangement on each data block in the requeuing column.

The present invention relates to an EDA verification method and device for a FlexE subsystem, belonging to the technical field of chip verification, and solves the problems of difficult data traceability, low problem location efficiency, and abnormal resource consumption in the prior art. It includes splitting each service packet into multiple first atomic data packets in the proxy component at each client level, and putting them into their respective queues and scoreboards; the driver at the channel level obtains the tx output signal of the DUT, calculates the proxy component identifier corresponding to each channel, takes out a first atomic data packet from the corresponding queue, and drives it to the DUT through the interface instance at each channel level; the monitor at the channel level samples the rx output signal of the DUT, calculates the proxy component identifier corresponding to each channel, encapsulates the received data into a second atomic data packet, and transfers it to the scoreboard of the corresponding proxy component according to the output port for comparison between the second atomic data packet and the first atomic data packet. The efficient and flexible verification of the FlexE subsystem is realized.

A method (100) of analysing a material comprises obtaining atomic data relating to the location of atoms within the material (110); performing a calculation on the atomic data to generate a plurality of mathematical functions relating to the spatial distribution of the atoms according to one or more predefined parameters (120); calculating a statistical distribution of the generated mathematical functions (130); and determining the detected microstructure of the material based on the statistical distribution (140). An alternative analysis method (500) uses a plurality of k-Nearest Neighbour (kNN) distributions as the mathematical functions and calculates one or more Short Range Order (SRO) values from the plurality of kNN distributions. A method (300) of manufacturing a product using the analysis method (100) and related system (400) are also provided.

According to the atomic data storage method and device, the equipment and the storage medium provided by the invention, whether the data type of the to-be-stored data is the atomic data type or not is judged by responding to the database storage instruction; if the to-be-stored data is an atomic data type, converting the data type of the to-be-stored data into a preset data type through a type processor to obtain target stored data; and storing the target storage data in a database. According to the method, the value of the atomic data type is automatically extracted and converted into the proper common data type, so that the problems of human errors and type mismatching are avoided, the consistency and integrity of the data are ensured, the requirement of a developer for manually writing a conversion code is reduced, and the development efficiency is improved.

Data path elements implemented using a plurality of logic primitives are provided. The plurality of logic primitives are connected in one or more topologies to perform an atomic operation on at least two atomic input data of a pre-defined bit-size. The atomic operation is split into a plurality of sub-atomic operations and the at least two atomic input data is split into a plurality of sub-atomic data fragments. Each of the plurality of logic primitives perform a sub-atomic operation from the plurality of sub-atomic operations on at least two sub-atomic data fragments from the plurality of sub-atomic data fragments to generate at least one partial sub-atomic output data. The at least one partial sub-atomic output data is generated based on a partial arithmetic operation, a shift operation, or a logical operation performed by each of the plurality of logic primitives in each clock-cycle. The architectures of a plurality of data-path elements comprised of a plurality of logic primitives in a plurality of connection topologies are provided.

The invention provides a document content changing method, electronic equipment, a storage medium and a program product. The change method comprises the following steps: acquiring a first content change operation of a first version number submitted by a client; when the first version number is not matched with a second version number of a local target document of the server, splitting the first content changed by the first content change operation into a plurality of atomic data which cannot be re-divided; determining atomic data in an operation range of a second content historical change operation applied to the target document of the second version number as conflict data; determining an operation priority between a first data operation acting on the conflict data in the first content change operation and a second data operation acting on the conflict data in the second content historical change operation; when the operation priority of the first data is larger than the operation priority of the second data operation, the first data operation is applied to a local target document of the server.

The present invention provides a method, system, and related equipment for determining data with a multi-level structure. The method comprises the following steps: upon detecting that a user has invoked a target determination rule, obtaining multiple atomic data values ​​input by the user for determination; expanding the atomic data values ​​according to the multi-level data definition table corresponding to the atomic data values ​​to obtain corresponding input data sets; sequentially filtering the determination entries in the determination function rule table corresponding to the target determination rule according to the input data sets corresponding to each atomic data value to obtain target determination entries; and determining a final determination result based on the target determination entries. This solution can process data with complex hierarchical relationships through pre-set multi-level data definition tables and determination function rule tables, thereby meeting ever-growing business needs.

The invention discloses a supervision data processing method and device, equipment, a storage medium and a product, and relates to the technical field of data processing, and the supervision data processing method comprises the steps: obtaining process basic data and instance operation data of a process business during the processing of the process business, and obtaining the process basic data and instance operation data of the process business based on a preset data specification; and cleaning abnormal data in the instance operation data, and processing the instance operation data and the process basic data based on service element configuration and preset processing rule configuration in a register book of a process service to obtain scene atomic data. The instance operation data is business data corresponding to the process basic data, and the process data and the business data can be associated through processing. And the service element configuration corresponds to the service scene, so that the scene atomic data can comprise the corresponding service scene through processing. Therefore, when supervision analysis is carried out based on the scene atomic data, the quality supervision analysis effect can be improved.

A system includes modules for DFT dataset generation, AGAT training, high-throughput prediction, CGAN generation, validation and augmentation, composition classification, and coordination. The DFT module generates and updates atomic data via spin-polarized DFT. The AGAT module trains attention-based models with translational, rotational, and permutational invariance. The prediction module estimates HER activity and ΔG(H) for new compositions. The CGAN module learns from predicted results and generates hypothetical compositions. The validation module runs DFT on selected candidates to update training data. The classification module uses KNN to group validated compositions and updates the formula list. The coordination module manages module interactions and iteration control.

Subscalar digital arithmetic computing paradigm is disclosed. The atomic data and atomic operations thereon are broken down into sub-atomic data fragments and sub-atomic partial operations. Such a break-up exposes hitherto unexploited levels of parallelism by way of allowing overlap of operations even if data-dependent. It is found that this improved exploitation of latent parallelism to enhance processing throughputs comes with a favourable impact on the area-power characteristics of corresponding computing structures. The present invention may be implemented through synthesized circuits and may result in an enhanced improvement in their area-throughput figure-of-merit (FOM).

A method (100) of additively manufacturing a product comprises performing one or more additive manufacturing steps on a material to build the product having a target microstructure (110); obtaining atomic data relating to the location of atoms within the material during the additive manufacturing steps (130); performing an analysis of the material (140) and adjusting the additive manufacturing steps in response to a detected microstructure being substantially different to at least the target microstructure (150). The analysis (140) comprises performing a calculation on the atomic data to generate a plurality of mathematical functions relating to the spatial distribution of the atoms according to one or more predefined parameters (320); calculating a statistical distribution of the generated mathematical functions (330); determining the detected microstructure of the material based on the statistical distribution (340); and comparing the detected microstructure to the target microstructure (150). A system (600) is also provided.

The invention relates to an ICU (Intensive Care Unit) severe illness quality control system data dynamic acquisition and intelligent analysis method, which specifically comprises the following steps of quality control data acquisition, data preprocessing, quality control index intelligent calculation, intelligent analysis and quality control related chart output, and specifically comprises the following steps: receiving patient data information sent by a multi-source data system based on a data acquisition module; the method comprises the following steps: acquiring patient data information, sending the patient data information to a data preprocessing module for preprocessing, storing the patient data information in an original data database, calling the patient data information in the original database through a quality control index calculation module, calculating to obtain a quality control index result, and based on an intelligent analysis module, taking the quality control index result as a core analysis object. And atomic data in an original database is combined as an auxiliary and traceability object for analysis, data-driven intelligent support is provided for clinical decision making, and finally a chart and a formatted report are generated by a chart output module. Data sources can be integrated in a centralized mode, real-time updating of quality control indexes is achieved, and management pertinence and effectiveness are improved.

The invention discloses a method for observing spatial distribution characteristics of deuterium and impurities of a lower divertor by using hyperspectral imaging, which comprises the following steps of: when a magnetic confinement fusion device runs, realizing multiband 2D image observation of a lower divertor region through a hyperspectral camera, and realizing continuous recording of emission spectral lines of deuterium and impurity elements of the lower divertor; arranging the obtained multiband spectral intensity data in the 2D space, establishing a corresponding database according to corresponding shot numbers, and carrying out calibration analysis on spectral information intensity recorded by a camera through an integrating sphere standard light source to obtain absolute intensity data of emission spectral lines in the multiband; and determining corresponding element information by combining the special emission spectral line wavelengths of different elements recorded in the ADAS atom database. Multiband spectral information data recorded by hyperspectral imaging can provide a basis for research on spatial 2D profile distribution of boundary plasma parameters and tungsten impurity spectral lines, and provide data support for evaluation of first wall tungsten impurity source distribution and tungsten impurity sputtering conditions.

The invention relates to the technical field of large models, in particular to a thinking processing method and system based on a large model.The method comprises the steps that a large model atomic agent database is established, and basic parameters, operation scenes, thinking strategy design and performance feedback information of atomic agents are covered; the operation scenarios include user interaction and system resource scenarios, based on which streaming monitoring risk levels are evaluated. And constructing a streaming monitoring simulation environment through the basic parameters and thinking strategy design, and performing streaming simulation on the thinking process of the atomic agent. And loading a streaming monitoring risk level in a simulation environment, setting a time sampling window, carrying out streaming simulation on a plurality of thinking stages of the atomic agent based on the window, and obtaining a monitoring evaluation result through a stage simulation result. According to the method, through transparent decision paths, real-time risk quantitative evaluation, high-compliance scene adaptation and dynamic strategy optimization, the problems that a traditional large model black box cannot be explained and dynamic risk monitoring is missing are solved.

The application relates to a thermal conductivity prediction method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining an initial structure file of a target crystal; a plurality of atomic data are included in the initial structure file; a plurality of perturbation structure files are generated based on the initial structure file and a preset supercell size; atomic information corresponding to each perturbation structure file is obtained based on a plurality of the perturbation structure files and a preset potential function model; and a thermal conductivity prediction result of the target crystal is obtained based on a plurality of the atomic information. The method can improve the thermal conductivity prediction efficiency.

The embodiment of the invention provides a cache operation method, a cache, computing equipment and a system, and relates to the technical field of chips. The cache operation method is applied to a cache, the cache comprises a shared cache and an atomic cache, the shared cache comprises a plurality of shared cache blocks used for storing data corresponding to different types of cache operation requests, and the atomic cache comprises a plurality of atomic data cache blocks used for storing atomic data corresponding to atomic operation requests; the cache operation method comprises the steps that according to a cache operation request sent by a computing unit, a first cache block used for storing target data is determined in a plurality of shared cache blocks, and the target data is data corresponding to the cache operation request; determining whether a second cache block corresponding to the first cache block exists in a plurality of atomic data cache blocks of the atomic cache, wherein partial data of the first cache block is stored in the second cache block; and if the second cache block exists in the atomic cache, executing the cache operation request at least according to the second cache block.

The present disclosure provides a method for changing document content, an electronic device, a storage medium, and a program product. The method includes: obtaining a first content change operation with a first version number submitted by a client; when the first version number does not match the second version number of a target document locally on a server, splitting the first content changed by the first content change operation into multiple indivisible atomic data; determining the atomic data within the operation scope of a second content history change operation applied to the target document with the second version number as conflicting data; determining the operation priority between a first data operation acting on the conflicting data in the first content change operation and a second data operation acting on the conflicting data in the second content history change operation; and applying the first data operation to the target document locally on the server when the operation priority of the first data is greater than the operation priority of the second data operation.

The invention relates to the technical field of heavy metal pollution prediction, in particular to a heavy metal pollution prediction method based on a molecular dynamics model, which comprises the following steps: collecting atomic data of copper tailing geopolymers, heavy metal ion types, initial concentration and environmental condition data, and constructing an influence factor reference data set; based on a molecular dynamics algorithm and an influence factor reference data set, a molecular dynamics model of interaction of the copper tailing geopolymer and the heavy metal ions is constructed, and based on acid rain leaching erosion, dry-wet freeze-thaw cycle and carbonization, dissolution, competitive adsorption and migration behaviors of the heavy metal ions in the copper tailing geopolymer are tested. Parameters of the molecular dynamics model are optimized on the basis of the test result, the currently obtained environmental conditions are input into the optimized molecular dynamics model, the pollution condition prediction result of the heavy metal in the copper tailing geopolymer is obtained, and the problems that in the prior art, the prediction result error is large, and the precision is low are solved.

The application discloses a method and device for generating report data, electronic equipment and a computer readable medium, and relates to the technical field of big data intelligent analysis. A specific embodiment of the method comprises the following steps: obtaining an atomic data list from a database according to a query condition, and extracting a row element set and a column element set from the query condition; performing data completion on the atomic data list according to the row element set and the column element set; calculating a total result of the completed atomic data list, and merging the total result into the atomic data list; and converting the atomic data list into a report data list. The embodiment can solve the technical problems that low-quality codes are prone to appear and codes are difficult to reuse.

The present disclosure relates to methods, devices and program products for backing up data in an Internet of Things. An Internet of Things system includes an Internet of Things manager and a plurality of Internet of Things devices. In one method, in response to receiving a registration request to register an Internet of Things device of the plurality of Internet of Things devices with the Internet of Things manager, a signed public key is received from the Internet of Things device. Atomic data associated with the Internet of Things device is received, the atomic data including a signature generated with a signed private key corresponding to the signed public key. The signature is verified based on the signed public key. In response to the signature being verified, backup data packets for backup are generated based on the atomic data. Corresponding devices and computer program products are provided. With exemplary implementations of the present disclosure, data can be backed up in an Internet of Things with higher performance, thereby improving the security and reliability of the entire Internet of Things.

The invention discloses a machine learning force field molecular dynamics efficient parallel acceleration method, system and device based on a taftogen S60 chip architecture and a storage medium. The method comprises the following steps of: firstly, acquiring initial data of a molecular system, and converting the initial data into a structure array (SoA) format to be stored in a high-bandwidth memory (HBM) of a chip; then, the simulation space is divided into a plurality of local sub-domains based on a space decomposition strategy, and atomic data are efficiently transmitted to an on-chip temporary storage memory (SRAM) through a direct memory access (DMA) engine; then, constructing a neighbor list in an SRAM (Static Random Access Memory), generating a local environment descriptor, and executing forward reasoning of a machine learning force field model by calling a tensor calculation unit of a chip to obtain atomic energy or atomic force; and finally, finishing stress reduction summation on the chip, executing numerical integration by using a vector processing unit, and updating the speed and the position of the atom. According to the method, through SoA data layout and a DMA strategy, the memory bandwidth utilization rate is improved, non-bonding force calculation is accelerated, and the expandability of parallel simulation is improved; and through a mixed precision strategy, the calculation efficiency is improved while the precision is ensured, and the method is suitable for long-time-scale high-precision simulation.

The application discloses a kind of robustness evaluation method, device and equipment of neural network, and storage medium, belong to computer technical field.The method comprises: data in benchmark dataset is annotated according to target multi-level structure, and the annotation information of data is obtained;Target multi-level structure includes m levels, and the lowest level in m levels includes at least one leaf characteristic;Data is classified based on the annotation information of data, and at least one atomic dataset is obtained, and the data in atomic dataset has the same annotation information;At least one atomic dataset is used to test the neural network to be evaluated, and the evaluation index value of at least one leaf characteristic is obtained;Based on the evaluation index value of at least one leaf characteristic, the evaluation index value of the neural network to be evaluated is determined, and the evaluation index value of the neural network to be evaluated is used to indicate the robustness of the neural network to be evaluated.The present application helps to improve the robustness evaluation efficiency of neural network.

The invention provides a fund data detection method and device, equipment, a medium and a program product, and relates to the technical field of data processing. The method comprises the steps of obtaining target detection information in response to a received data detection request sent by client equipment; the data detection request comprises target detection information; the target detection information is detection demand data of the target fund data; the target fund data is to-be-detected fund data; obtaining a target atomic data model based on the target detection information; adopting the target atomic data model and constructing a target fund data detection model based on the target detection information; constructing a target task table based on the target detection information, and associating the target task table with the target fund data detection model; and determining target fund abnormal data based on the target task table by adopting the target fund data detection model.

The invention relates to a cross-system asset multiplexing method and device based on a unified standard and computer equipment. The method comprises the steps that original assets are received, the original assets comprise standard format assets of a first asset format, and the first asset format is any one of multiple standard formats; analyzing the standard format assets in the original assets by adopting an asset analysis mode corresponding to the first asset format, and forming shared assets according to each analyzed atomic data; displaying data items corresponding to the atomic data in the shared assets; and in response to at least one target data item selected from the displayed data items, generating a first target asset in the first asset format from the atomic data represented by the at least one target data item, and sharing the first target asset with a set external system. By adopting the method, the asset reuse efficiency can be improved.