29 results about "Arbitrary-precision arithmetic" patented technology

The invention relates to the technical field of digital twinning, in particular to a high-performance digital twinning system rendering method based on dual-grid and neural network mapping, and the method comprises the steps: constructing a high-precision calculation grid and a low-precision rendering grid, and building a space mapping relation between the two grids; executing multi-working-condition numerical simulation to obtain a high-dimensional simulation result snapshot matrix; the dimension reduction projection operator is used for reducing the dimension of a high-dimensional simulation result of any working condition into an r-dimensional feature vector; generating low-dimensional reference field data by using the space mapping relation; training the neural network until a mapping network parameter is obtained through convergence; obtaining current working condition parameters of the equipment in real time, and obtaining a current r-dimensional feature vector by using the dimensionality reduction projection operator; and quickly generating physical field prediction distribution on the low-precision rendering grid and performing pseudo-color rendering. According to the scheme, the problem that a traditional method is low in rendering efficiency is solved, and the method has the advantages of reducing computing resource consumption and keeping visualization precision.

The invention provides a comprehensive pipe gallery safety state evaluation method and system, and relates to the technical field of comprehensive pipe gallery safety state evaluation methods, and the method comprises the steps: employing a steady-state heat release method to calculate the simulation temperature of each three-dimensional grid node; a finite difference method is adopted to calculate a temperature field distribution coefficient of each three-dimensional grid node, and a temperature distribution coefficient of a three-dimensional grid center point is obtained through an arithmetic average method; a coupling damage method is adopted to construct a coupling coefficient matrix of any grid position, equivalent damage energy of any grid position is calculated through an inner product method, and the equivalent damage energy is mapped into a safety coefficient of any grid center point through normalization. By adopting three-dimensional grid discretization, complex geometric characteristics of the pipe gallery structure can be more accurately captured, the position of a potential fire source is clearly marked, the hidden danger recognition efficiency is improved through targeted monitoring, high-precision calculation of a simulated temperature field under the complex boundary condition is achieved, equivalent damage energy is mapped into a dimensionless safety coefficient, and cross-regional risk comparability is achieved.

The invention belongs to the technical field of in-memory computing, and discloses a multi-precision in-memory computing circuit with balanced output bit width, a memory and a chip, which are characterized in that through the collaborative change of a broadcast mode of an input side and an accumulation mode of an output side, under different computing precisions, the multi-precision in-memory computing circuit with balanced output bit width is obtained; the external interface bandwidth (the number of ADCs / the number of adders) of the physical array is kept constant. According to the invention, the contradiction between high bandwidth demand in a low-precision mode and low bandwidth demand in a high-precision mode in a multi-precision in-memory computing architecture is solved, the idle waste of the output bandwidth during high-precision computing is avoided, the relatively balanced bit width of an output interface is realized, and the area cost of a chip can be greatly reduced.

The application discloses a lightweight method of river surface flow velocity field depth reconstruction model, relates to the computer science and fluid mechanics cross technical field, collects river surface PTV and PIV data, and constructs a flow velocity field matrix of the target river surface; based on the matrix block calculation strategy and the flow velocity field matrix, the target river surface is divided into a plurality of sub-matrix regions; based on the pattern recognition technology and the flow velocity gradient characteristics, each sub-matrix region is distinguished. The application divides the global flow velocity field into a plurality of sub-matrix regions through the matrix block strategy, adaptively determines the optimal block size according to the GPU parallel thread number, memory bandwidth and other constraints, maximizes the hardware utilization rate, and in the calculation process, adopts a differentiated resource allocation mechanism, concentrates high-precision calculation in a high-error clustering area, and adopts a simplified model in a low-error clustering area, significantly reduces the overall calculation load, and realizes efficient balance between calculation efficiency improvement and resource dynamic scheduling.

The invention provides a slow action generation method based on motion focus area analysis. The method comprises the following steps: determining a video of a slow action to be generated; detecting a motion focus area in the video, and grading the motion focus area; and for different grades of motion focus areas, different strategies are adopted to carry out motion modeling and differential interpolation processing, and a slow motion frame sequence is generated. According to the invention, through identification and grading processing of the motion focus area, high-precision calculation of the core motion object, simplified calculation of the secondary area and simplest processing of the static background, compared with a traditional scheme of uniform and dense calculation of the whole frame, the method has the advantages of high calculation complexity and lower calculation amount, and guarantees the visual effect of the core area.

The invention provides a multi-level virtual-real coordinate mapping and drift correction method, system and platform, a dynamic floating original point mechanism is established, the original point position of a virtual coordinate system is adjusted in real time, so that a scene around a user is always in a high-precision calculation range of a single-precision floating-point number, and the user experience is improved. The dynamic floating origin mechanism comprises a coordinate mapping engine, an origin decision module and a seamless switching manager. A multi-level real world-virtual-real space-virtual environment conversion link is directly opened, large-scale development of augmented reality XR contents of cities / parks / outdoor / indoor / temporary spaces, automatic driving, unmanned aerial vehicles, intelligent robot navigation and the like is promoted, and the problems of large-space rendering jitter, low development efficiency and the like in the prior art are solved. In order to achieve the purpose, the invention provides an underlying OS operating system, and provides a cross-multi-level real world coordinate system and virtual environment coordinate system mapping method, a drift correction system and a developer operating platform.

The invention discloses a multi-scale space target relative pose estimation method and system using parallel double encoders, and belongs to the technical field of space target pose estimation. The invention aims to solve the problems caused by distance change, illumination difference and insufficient multi-scale feature expression of a space target in a dynamic environment. According to the technical key points, a parallel double-encoder architecture is adopted, and local and global features of a space target are extracted; constructing a feature fusion module to fuse features extracted by the CNN and the Transform; multi-scale features are fused through FPN, and angular points are predicted; training and optimizing the network; and solving the pose by using a random consistency perspective n-point method. A plurality of non-coplanar control points are selected, other points are expressed as a linear combination of the control points, a linear equation set is constructed, and a rotation matrix and a translation vector between a target and a camera coordinate system are solved by using a singular value decomposition method. The deep learning network algorithm provides an efficient and accurate solution for space target pose estimation, the algorithm can deeply mine rich information of image data by adopting an encoder-decoder structure, and finally high-precision calculation of the six-degree-of-freedom pose of the target is achieved.

The invention discloses a symmetric magnetic field calculation method, which comprises the following steps of: analyzing the symmetry of magnetic field source distribution, and selecting a reference source in a group of symmetric sources; calculating the magnetic field intensity of the reference source at any field point in the space; based on symmetry, mapping the field points to equivalent field points corresponding to the symmetric sources through a rotation matrix, and calculating magnetic fields of the symmetric sources at the equivalent field points; restoring the magnetic field at the equivalent field point to an original field point direction through an inverse matrix of the rotating matrix; and finally, superposing the magnetic field contributions of all symmetrical sources at the original field point to obtain the total magnetic field of the point. According to the method, the symmetry of a magnetic field source is fully utilized, a rotating group processing method in the group theory is adopted, accurate calculation is performed in combination with the Bios-Savart law, the symmetry and direction correctness of the magnetic field can be strictly ensured, and high-precision calculation of the extremely low-intensity magnetic field is realized; the problems of errors and direction errors existing in symmetrical field and weak field calculation of a traditional finite element method are solved.

The invention belongs to the technical field of hydraulic structure numerical analysis, and particularly relates to a two-dimensional temperature field adaptive grid merging method. The method is based on an independent coverage manifold method, an error estimator is constructed through the heat flow continuity degree between adjacent grids to replace an empirical formula, full-domain automatic error estimation is achieved, the accuracy of judging whether grid merging is carried out or not is enhanced, the method comprises the steps of error estimation, grid marking, grid shape judgment, grid merging and the like, and the method is suitable for large-scale popularization and application. And by merging the local grids, the calculation precision and the calculation efficiency are both considered, and local high-precision calculation is realized.

The invention relates to the technical field of artificial intelligence accelerators, in particular to a configurable mixing precision calculation array circuit based on an outer product. According to the method, the basic int4 multiplier is taken as a reference, the results of the basic multiplier are fused according to different configuration modes to support high-precision calculation, calculation of 12 different specifications can be supported at most, the resource utilization rate of the multiplier is increased, and the resource utilization rate of the multiplier reaches 100%; by expanding a 1-bit sign bit, the array supports multiplying a signed number by a signed number, multiplying an unsigned number by a signed number and multiplying an unsigned number by an unsigned number, and various calculation requirements of the neural network are flexibly adapted; a matrix transposition switch is built in, so that the overhead of external transposition is reduced; the bit width of output data is limited through functions such as saturation truncation, and storage overhead is reduced. According to the method, the calculation efficiency is improved, at most four kinds of calculation precision and 12 kinds of calculation modes are supported, and the resource utilization rate is improved by 2-4 times; and application scene extension, perfect signed / unsigned calculation support and dynamic reconfiguration during operation are supported.

The invention discloses a high-precision calculation method and device for a normalized arc tangent function. The method comprises the steps that S1, input floating point data is decomposed and preprocessed; the symbol, the order code and the mantissa of the input floating point data are obtained through data conversion, and the order code is compared with the single-precision offset code to obtain a shift code; obtaining input data for second-order polynomial calculation by using the shift code; s2, simplifying a calculation interval by using the characteristics of an odd function; s3, layering and segmenting the effective interval and selecting a polynomial coefficient; s4, carrying out second-order polynomial and fifth-order Taylor dual-path parallel calculation; step S5: result formatting; and S6, dynamically selecting and outputting. The device is used for executing the method. The invention has the advantages of high precision, low time delay, small area, low cost and the like.

The invention discloses an automatic CFD solving method for an internal flow field of a bimodal scramjet engine, and the method comprises the steps: constructing an AnsysFluent automatic solving environment through employing a Python script, loading a grid file of a bimodal scramjet engine model, configuring a physical model and boundary conditions of the bimodal scramjet engine through employing the Python script, and carrying out the automatic solving of the internal flow field of the bimodal scramjet engine. A Python script is utilized to complete setting of a numerical discrete format and a solving method and construction of a flow field initial value of a computational domain; taking the flow field initial value as an iteration starting point, and executing dynamic climbing calculation under first-order precision by utilizing a Python script to obtain stable initial flow field distribution; the stable initial flow field distribution is used as an initial calculation value, and a Python script is used for switching second-order high-precision calculation and carrying out convergence judgment. According to the method, the problems of tedious manual intervention, difficulty in shock wave capture and subjective convergence judgment in high-Mach-number strong compressible flow calculation are effectively solved.

The present disclosure relates to an information processing apparatus, an information processing method, and a computer-readable storage medium. The information processing apparatus according to the present disclosure includes processing circuitry configured to: obtain a sound field in a virtual space, by using a sound field synthesis model, based on sound source information about a sound source in a real space and virtual space information indicating an object present in a virtual space. The sound field synthesis model is pre-obtained through machine learning by using a sound field in a virtual space obtained from high-precision calculation as learning data.

The application provides a construction safety visual calculation and resource scheduling method, system and electronic equipment, which comprises the following steps: deploying and initializing the calculation and resource scheduling system; the edge end collects video streams in real time and performs preprocessing, light-weight model inference and local alarm; the edge end performs three-level screening on the video data, intelligent compression of the region of interest (ROI) and end-to-end encryption before uploading to the cloud; a multi-objective optimization decision model is constructed based on FAHP, and the allocation strategy of the task in the edge end and the cloud is dynamically adjusted according to the real-time collected network state parameters, computing power state parameters and event characteristic parameters; the cloud adopts a high-precision model for inference, links a knowledge base to generate a rectification scheme, and realizes full-process closed-loop management; an incremental data set is constructed to fine-tune the light-weight model and the high-precision model. The scheme provided by the application can balance the contradiction between the real-time alarm demand of the construction site and the high-precision calculation demand of the complex model.

The invention discloses a training and reasoning system, a training method and a reasoning method, and relates to the technical field of artificial intelligence, the training and reasoning system comprises a resistive random access memory storage layer, a dynamic random access memory storage layer and a data scheduling module; the resistive random access memory storage layer and the dynamic random access memory storage layer are heterogeneously integrated; the resistive random access memory storage layer is used for storing the weight after training stabilization and executing multiplication and addition operation; the dynamic random access memory storage layer is used for storing intermediate results obtained in training and reasoning processes; and the data scheduling module is used for storing the weight to be updated in the storage layer of the dynamic random access memory, storing the weight after training stabilization in the storage layer of the resistive random access memory, and storing an intermediate result obtained based on multiplication and addition operation in the training and reasoning process in the storage layer of the dynamic random access memory. The system can meet the requirements of high bandwidth, low power consumption, high capacity and high-precision calculation at the same time.

Apparatuses, systesms, and techniques to simulate high-precision calculations with a series expansion of lower precision tensor cores. In at least one embodiment, one or more multiplication operands of a first precision are represented by a sum of two or more operands of a different precision.

This application relates to the field of intelligent transportation technology, and discloses a method, device, system, and storage medium for real-time collaborative optimization of traffic emissions. The method includes collecting vehicle operation data to calculate vehicle power, constructing a two-dimensional bin-structured index of the instantaneous emission rate as a baseline, and correcting it in real-time using pre-fixed rules to output single-vehicle, single-step emissions at the microscopic level; aggregating emission data according to spatial hierarchical logic and simultaneously calculating performance indicators such as average commuting time; calling templates to generate strategies when indicators exceed limits; compiling the strategies into a set of six-tuple standard actions and performing fairness and conflict checks; using an exactly-once mechanism and consistency window to ensure atomic execution across devices; and evaluating strategies based on in-loop monitoring, combined with a third-generation non-dominated sorting genetic algorithm and a conditional risk-value risk term, outputting a Pareto optimal solution set that is continuously updated. This invention balances traffic efficiency, environmental benefits, and system execution stability through a high-precision calculation model and robust optimization algorithm.

The application discloses a kind of dual-mode scramjet internal flow field automation CFD solving method, comprising: using Python script to build AnsysFluent automation solving environment, load the grid file of dual-mode scramjet model, using Python script to configure the physical model and boundary condition of dual-mode scramjet, using Python script to complete the setting of numerical discrete format, solving method and the flow field initial value construction of calculation domain;Flow field initial value is used as the starting point of iteration, using Python script to execute the dynamic climbing calculation under first-order accuracy, obtain stable initial flow field distribution;Stable initial flow field distribution is used as the initial value of calculation, using Python script to switch second-order high-precision calculation and carry out convergence determination.This method effectively solves the problems of artificial intervention tedious, shock capturing difficulty and convergence determination subject in high Mach number strong compressible flow calculation.

The invention discloses a precision-power consumption parallel processing method and system for extreme environment segmentation, and belongs to the technical field of lunar exploration. Constructing an image segmentation neural network model based on a coding-decoding structure, and hierarchically dividing the model operation into a full-precision calculation layer and an approximate calculation layer according to the error tolerance of different semantic regions; acquiring an extreme environment image and evaluating the scene complexity of the extreme environment image in real time; an image is input into a model coding end for feature extraction, high-precision calculation is performed on a high-precision calculation layer, an approximation strategy is dynamically selected for an approximation calculation layer according to scene complexity and semantic distribution, and a segmentation result is output after feature fusion. The system comprises a self-adaptive approximation control unit and a parallel hardware platform, and real-time interaction of control parameters and calculation tasks is achieved through a hardware interface. On the premise of ensuring the segmentation precision of the key region, the average power consumption of the system is remarkably reduced, the energy efficiency ratio is improved, and the method is suitable for extreme environment detection platforms with limited resources such as lunar rovers.

The invention discloses a circuit breaker stroke high-precision calculation method based on multi-connecting-rod kinematics analysis. The circuit breaker stroke high-precision calculation method comprises the steps that a non-intrusive mechanical characteristic sensor arranged in a main shaft of a vacuum circuit breaker is used for collecting the initial rotation angle of the main shaft of the circuit breaker in real time; establishing a multi-link motion model of the circuit breaker transmission mechanism; inputting the collected main shaft initial rotation angle of the circuit breaker into the multi-connecting-rod motion model, and calculating a first moving point coordinate; establishing and solving a quadratic equation based on a double-circle intersection point principle, and obtaining coordinates of a second moving point; and calculating the stroke of the contact through vector rotation according to the coordinates of the second moving point and the coordinates of the fixed point. A complex multi-connecting-rod kinematics problem is innovatively converted into a quadratic equation rooting problem, so that the calculation efficiency and precision are greatly improved, and nondestructive acquisition and high-precision analysis of mechanical characteristics of the circuit breaker are realized.

The application discloses a high-precision calculation method and device for a normalized arctangent function, and the method comprises the following steps: step S1: input floating-point data decomposition and preprocessing; the sign, the order code and the mantissa of the input floating-point data are obtained through data transformation, the order code is compared with a single-precision offset code to obtain a shift code; the input data used for a second-order polynomial calculation is obtained by using the shift code; step S2: simplifying the calculation interval by using the characteristics of an odd function; step S3: layering and segmenting the effective interval and selecting polynomial coefficients; step S4: second-order polynomial and fifth-order Taylor double-path parallel calculation; step S5: result formatting; and step S6: dynamically selecting output. The device is used for executing the above method. The application has the advantages of high precision, low delay, small area, low cost and the like.

This invention relates to a method for weight quantization of large language models based on statistical distribution, belonging to the field of artificial intelligence technology. This method adaptively selects the quantization threshold by analyzing the skewness, kurtosis, and dynamic range of the statistical weight distribution, achieving high-precision sparse preservation of important weights and low-bit compression of minor weights. Simultaneously, it introduces mean error compensation and variance alignment mechanisms, as well as a block-level parallel quantization strategy, to further reduce quantization errors and improve efficiency. This invention addresses the challenges of existing large language models with their massive parameter scale, requiring high-precision computation and substantial resources for inference, making them difficult to deploy on resource-constrained edge devices; and traditional quantization compression techniques suffer from significant accuracy loss, high computational overhead, and poor adaptability. This method achieves 8-bit and 4-bit quantization without retraining, achieving performance close to FP16 accuracy, significantly reducing model storage space and computational resource consumption, making it suitable for efficient deployment of large language models at edge devices.

Apparatuses, systems, and techniques to simulate high-precision calculations with a series expansion of lower precision tensor cores. In at least one embodiment, one or more multiplication operands of a first precision are represented by a sum of two or more operands of a different precision.

The invention belongs to the technical field of in-memory computing, and discloses a high-precision floating-point in-memory computing system and method based on outlier separation, and the method comprises the steps: analyzing the index distribution of an input data group, and judging that an outlier extreme value exists and starting an outlier mode when a difference value between a maximum index and an in-group average or second maximum index is detected to exceed a preset threshold value; in the in-memory calculation main body path, mask processing is carried out on the detected extreme maximum value at the input end, pre-alignment and displacement are carried out on the remaining normal data again according to the local maximum index of the normal data, and parallel mantissa multiply-accumulate calculation is completed in the array; meanwhile, in the digital bypass path, an external digital multiplier is used for independently calculating the product of the outlier; the calculation results of the two paths are aligned and added in a digital domain, and a final high-precision calculation result is output. Through the design of dynamic outlier detection and a hybrid calculation path, the precision of floating point in-memory calculation is remarkably improved.

The invention discloses a DTM-based filling and excavation amount calculation method and electronic equipment. The method comprises the steps of obtaining an initial digital terrain model DTM, an end-of-period DTM, a calculation range of filling and excavation amount and an elevation interval for a target area; determining whether the coincident triangle pairs intersect in the space, if yes, determining a first intersecting line of the coincident triangle pairs, and splitting the initial polygon into a plurality of polygon units based on the first intersecting line, and if not, determining the initial polygon as a polygon unit; a polyhedron formed based on the initial polygon units and the final polygon units is defined as a right-like prism; based on the filling amount or the excavation amount of the right prism-like prism, determining the filling and excavation amount within the filling and excavation amount calculation range between the initial DTM and the end DTM; and based on the filling amount or the excavation amount of the at least one sub-elevation interval, determining the filling and excavation amount corresponding to the elevation interval. In this way, high-precision calculation of the filling and excavation volume and calculation of the filling and excavation volume in different elevation intervals are achieved.

The invention provides a distributed precision extraction method based on weight, and belongs to the technical field of circuit parasitic parameter extraction. The extraction method comprises the steps of collecting multi-source circuit data based on circuit attributes and a process modeling library, and performing structured preprocessing to generate a structured feature database; constructing a weight calculation model, calculating weight values of grid sub-modules in the structured feature database, and dividing precision regions according to the weight values; allocating a corresponding extraction engine for the precision area to perform precision extraction, and performing task scheduling for the extraction engine by utilizing a task allocation engine; and a hybrid grid coupling algorithm is adopted to eliminate circuit parasitic parameter jump between precision regions so as to realize distributed precision extraction of circuit parasitic parameters and generate a circuit parasitic parameter netlist. According to the method, the hardware utilization rate is maximized, the overhead of global high-precision calculation is avoided, the efficiency of a non-critical region is improved, the extraction result error is quantized and compensated, the problem of parameter drift is solved, and parasitic parameter jump is eliminated.

The application discloses a kind of nuclear fuel rod wear depth efficient high-precision calculation method, device, equipment and storage medium, it is related to computer technical field, the method includes: obtaining initial sample data set containing vibration parameter and corresponding wear depth;Based on initial sample data set, initial Kriging method Kriging prediction model is constructed;The predicted response value of sample point is calculated using initial prediction model, and the learning function value of sample point is calculated according to predicted response value and preset failure threshold value;Judge whether to meet iteration termination condition;If not, determine the least uncertain point according to learning function value, supplement simulation wear depth data to update training set sample or introduce new experimental wear depth data to update training set sample;According to the training set sample after updating, a new Kriging prediction model is constructed;If yes, output current prediction model as target prediction model.The method can improve the accuracy of nuclear fuel rod positioning grid wear prediction.

The invention relates to a transient electromagnetic field-circuit coupling high-precision calculation method based on an A-alpha formula, and the method comprises the steps: dividing grid data into a plurality of polyhedral smooth regions with corresponding edges as centers according to the edges in the grid data of a three-dimensional motor 1 / 8 periodic model; a smooth vector shape function of edges and a smooth shape function of nodes in the polyhedron smooth domain are calculated; constructing a transient field-circuit coupling equation set based on an A-alpha formula, transient eddy current and coulomb specifications, and rewriting the transient field-circuit coupling equation set according to the smooth vector shape function of each edge, the smooth shape function of each node and a Galerkin method to obtain a transient field-circuit coupling system equation; further rewriting the transient field-circuit coupled system equation into a Newton iteration linear equation; and iteratively solving the Newton iteration linear equation by adopting a Newton iteration method until the Newton iteration linear equation converges to obtain a magnetic vector bit in field-circuit coupling, thereby realizing high-precision numerical solution of the transient field-circuit coupling problem in the complex motor system.