103 results about "Precomputation" patented technology

The invention belongs to the technical field of storage and calculation integration, and particularly relates to a low-bit-width and high-energy-efficiency floating point storage and calculation integrated circuit based on a partial pre-alignment framework. The circuit comprises a memory array, a pre-calculation unit, an adder tree, a configurable arithmetic unit and a normalization unit, and supports mixed precision operation of FP8MACFP4 and FP8MACFP8. The method is characterized in that a partial pre-alignment strategy dominated by an activation value is adopted, the maximum index of the activation value is dynamically counted, the mantissa of the maximum index is aligned, and multiple partial pre-alignment intermediate results are pre-calculated and latched for reuse; in combination with a customized lookup table and a multiplexer, a pre-calculation result is directly selected to replace real-time multiplication and displacement; and through the reconfigurable hardware, the FP8MACFP8 high-precision operation is realized by utilizing the FP8MACFP4 unit combination. According to the method, complete online floating point multiplication and addition operation is realized, and excellent energy efficiency ratio and operation speed are obtained while high precision is kept.

The invention provides a generative intelligent optimization method and device, and relates to the technical field of generative artificial intelligence optimization computation.The method comprises the steps that a mathematical model containing decision variables, an objective function and constraint conditions is established for a target optimization problem, and scene parameters are pre-calculated through a traditional optimization algorithm to obtain a theoretical optimal solution; constructing a training data set containing scene parameters and a theoretical optimal solution; training the data set through a conditional generation type artificial intelligence model, minimizing the difference between a generation decision and a theoretical optimal solution, and establishing a mapping relation from scene parameters to an optimal decision, so that the mapping relation implicitly learns a constraint condition satisfaction mode; current scene parameters are collected in real time and input into the trained model, a near-optimal decision scheme is generated through reverse denoising or hidden variable decoding, and the near-optimal decision scheme is applied to real-time scenes such as industrial control. According to the method, a high-quality solution close to theoretical optimum is realized, the online solution time consumption is remarkably reduced, and the real-time requirement is met.

The invention provides a communication optimization method for topological table persistent storage in efficient parallel computing, belongs to the technical field of storage communication, and aims to avoid pseudo sharing by aligning memory allocation through cache lines, expand local topological coverage through a topological entropy increment driven prefetching mechanism, and improve the reliability of the topological table persistent storage. Boundary processing is accelerated through a pre-calculation period mapping lookup table and a frequency domain transfer function vector, synchronization overhead is optimized through a concurrency control mechanism perceived by a read-write ratio, targeted cache preloading is achieved through stability and jitter degree two-dimensional evaluation, bandwidth consumption is reduced through an increment synchronization mechanism, and the stability of the cache is improved. The communication template is selected or the communication parameters are generated through adaptive conversion by matching the matching degree decision, and the technical problem that the parallel computing performance is reduced due to the fact that the communication overhead is too large in the topological table persistent storage process is solved.

The invention discloses a resource allocation method and device based on bit map pre-calculation, and the method comprises the steps: generating a global resource state bitmap according to the CORESET configuration in a PDCCH, and carrying out the pre-calculation of each possible candidate PDCCH to form a candidate pre-allocation bit map set; extracting a corresponding pre-allocation bitmap from the candidate pre-allocation bitmap set as a candidate set bitmap; and comparing the candidate set bitmap with the global resource state bitmap, judging whether the resources are conflicted or not, and if the resources are not conflicted, determining that the resources are available and further occupying the resources. Complex function calculation at the scheduling moment is transferred to pre-calculation at the initialization stage, only simple bitmap retrieval and bit operation are needed during scheduling, the PDCCH resource allocation time consumption is greatly shortened, real-time intensive calculation is replaced with pre-stored bitmaps, the CPU load is remarkably reduced, a processor focuses on a core scheduling algorithm, resource redundancy consumption is reduced, and the scheduling efficiency is improved. And the overall capacity and the energy utilization efficiency of the communication system are effectively improved.

The invention provides an NoC low-delay data transmission method based on a dynamic routing algorithm, relates to the technical field of data transmission, and aims to solve the technical problems that an existing NoC routing algorithm cannot adapt to a link dynamic load, is lack of congestion trend prejudgment, is slow in path search convergence and is insufficient in QoS differential scheduling. The method comprises the following steps: constructing a dynamic sensing module containing a double-branch LSTM time sequence prediction model, collecting states such as link bandwidth and queue length in real time, and predicting a congestion trend in 50-100ms in the future; constructing a multi-objective evaluation function taking delay as a core, and dynamically adjusting the weight according to the QoS level; solving an optimal path by adopting an improved ant colony algorithm which introduces a congestion penalty and pruning strategy; during transmission, dynamic reselection is triggered through a pre-calculation + fast matching mechanism; and iteratively optimizing the prediction model based on incremental learning. According to the method, congestion is avoided in advance, the path search efficiency and the transmission reliability are improved, the delay is remarkably reduced compared with a traditional algorithm, and the method is adaptive to delay sensitive scenes such as a high-performance processor and an AI chip.

A system and method for adaptive ideation and innovation management using graph-based similarity computation and real-time social facilitation are disclosed, and the system may include a plurality of client devices operated by a human user and one or more AI Agents. The system may further include a computing platform running a Precompute Similarity Engine that may be configured to embed and index idea objects, precompute similarity clusters, and generate candidate merge or purge operations together with diversity and novelty signals; and running a Social Physics Engine that may be configured to monitor human user and machine participant (AI agent) interactions, compute group metrics, and issue digital facilitation interventions. The Precompute Similarity Engine and the Social Physics Engine may operate in an interdependent feedback loop such that diversity and novelty signals guide the generation of digital facilitation interventions that are communicated via the network to the plurality of client devices and the one or more AI Agents.

The invention discloses an elliptic curve scalar multiplication optimization method, an elliptic curve scalar multiplication optimization device and elliptic curve scalar multiplication optimization equipment based on multiple windows and multiple base chains, which can be used for a communication system core network. The method comprises the steps that parameter sets arranged according to the window width in a descending order are configured, each parameter set comprises a cardinal number set and the window width w, and a corresponding candidate odd number set is generated; sliding recoding is carried out on an input scalar k, 0 is added to even-numbered bits and the even-numbered bits are shifted rightwards by k, a congruent recoding number with the minimum absolute value is searched for odd-numbered bits according to the priority of a parameter group, if the recoding number is not found, the wNAF rule is returned, and a sparse digital sequence D is obtained; according to a fast / ct mode, generating a pre-calculation lookup table by combining a power chain with a binary combination; and scanning D from a high order to a low order, sequentially executing point doubling operation by the accumulator, executing conditional point adding operation when meeting a non-zero number, and finally obtaining a scalar multiplication result. According to the method, the non-zero bit density and the side channel risk are reduced, the operation efficiency is improved, and the method is suitable for various security scenes.

The invention discloses a neutral atom quantum compiling method and system for off-line pre-calculation, and belongs to the field of quantum computation.The method comprises the two stages of off-line template construction and on-line compiling, specifically, in the off-line stage, a neutral atom array is abstracted into a two-dimensional grid, an effective gate candidate set is constructed based on the Rydberg blocking radius and the parallel execution limiting radius, and an effective gate candidate set is constructed based on the effective gate candidate set; generating a space template configured by the maximum parallel gate by using a satisfiability model theory solver, and expanding a template library through rotational symmetry; in the online stage, quantum circuits are layered, matching templates are retrieved, slot distribution, direction selection and conflict evaluation are carried out, and finally an executable operation sequence is generated through timing sequence routing coloring. According to the method, the compiling efficiency, the expandability and the circuit execution fidelity are remarkably improved, and the method is suitable for a large-scale neutral atom quantum computing platform.

The invention discloses a multi-machine four-dimensional cooperative path planning method for pre-calculating a deviation path and dynamically re-planning, and belongs to the field of cooperative control and path planning of unmanned aerial vehicle clusters. The method comprises the following steps: dividing a three-dimensional airspace into cubic empty blocks, constructing a directed connected graph, and removing the empty blocks and edges which do not meet a safe distance; generating an initial three-dimensional path of each unmanned aerial vehicle by using a dynamic priority fast expansion random tree algorithm; taking an end point empty block as a starting point, constructing a reverse reachable graph by means of breadth-first search, pre-calculating a plurality of deviation paths from a neighborhood empty block to an end point in an off-line manner, and storing the deviation paths into the empty block; when a dynamic threat is detected in the task, calling an improved heuristic artificial potential field algorithm to generate a local obstacle avoidance section; and retrieving a pre-stored deviation path after obstacle avoidance, and selecting an optimal path for splicing in combination with a cost function. According to the method, the calculation amount is moved forward to an offline stage, the dynamic environment re-planning time is shortened, simultaneous arrival of multiple machines and space safety are guaranteed, and the expansion capability and the real-time performance are improved.

The invention discloses a lens vignetting correction method and device, computer equipment and a storage medium, and the method comprises the steps: setting a reference data index according to a vignetting intensity parameter of a lens, and extracting a reference coefficient from pre-calibrated lens vignetting data; constructing a correction lookup table in combination with the vignetting intensity parameter, the reference data index and the reference coefficient; obtaining a target image collected by a lens, and calculating an optical center coordinate and a normalized radius reference value of the target image; obtaining a to-be-processed area of the target image, and performing area initialization on the to-be-processed area in combination with the optical center coordinate and the normalized radius reference value; and based on the initialized to-be-processed region, correcting the target image in combination with the correction lookup table. According to the vignetting correction method and device, the real-time complex mathematical operation is converted into the pre-calculated table query operation, efficient and accurate vignetting correction is achieved, and the problems that in the prior art, calculation complexity is high, and real-time performance is poor are solved.

This invention relates to the field of data processing technology, and in particular to a method, apparatus, device, and medium for processing multi-dimensional data. The method instantiates a template based on input tensor parameters to obtain an offset calculation instance. The offset calculation instance is initialized to determine the step size and shape of each input array in each output dimension, and these are recorded in a designated storage space. The offset calculation instance is then started to perform index calculations on the step size and shape of each input array recorded in the storage space in each output dimension to obtain the offset corresponding to the output array. The data corresponding to the offset is then processed according to a set calculation rule to obtain the output result. By pre-calculating the step size and shape of each input array in each output dimension, unnecessary memory accesses can be reduced. Constructing offset calculation instances simplifies the index calculation process, enabling efficient and accurate data storage, retrieval, and calculation.

The invention relates to the technical field of big data, and provides a transaction data processing method and device based on idle time, equipment and a medium, which can start a business thread to scan a market queue and a return queue in real time in a current transaction period so as to respond in time. In the continuous scanning process of preset times, when no new market information slice is scanned in the market information queue and no new return information is scanned in the return queue, calculating the current idle time according to an idle time determination strategy after the market information and the return are ensured to be processed; the operator type with high real-time performance is divided into the pre-calculation operator and the decision operator, the pre-calculation operator is processed in the current idle time, the decision operator is processed in the current transaction time, the idle time can be fully utilized, glitch time delay in the transaction process is reduced, and the performance and time delay penetration stability of a transaction system are improved.

The invention relates to a distributed light path tracking method and system based on precomputation, and the method comprises the following steps: S1, dividing scene data, and then carrying out distributed storage, dividing the scene data into a plurality of data blocks containing a BVH structure and geometric data according to the spatial distribution characteristics and storage overhead of a scene object, the static data are distributed to the distributed storage unit in a balanced mode to serve as initial static data of the distributed storage unit; s2, generating a pre-rendering camera according to the data access frequency of the KD tree; s3, predicting the data access frequency; s4, reordering the data items according to the data access frequency; and S5, performing distributed rendering.

The application discloses a privacy protection neural network inference method based on multi-point evaluation. K Segment k Polynomial, and a safe multiplication tree and a safe remainder tree are established, and then a remainder polynomial is safely evaluated. Since the polynomial power to be evaluated in the online stage is reduced, the number of self-multiplication items is reduced, thereby reducing the communication round number of overall polynomial evaluation, reducing the number of calls of the safe multiplication triplets in the secret sharing, and correspondingly reducing the offline pre-computation cost. In addition, the layered structure of the safe multiplication tree and the remainder tree supports parallel computation of multi-point input, and can fully utilize the parallel computation capacity of a modern multi-core processor or a GPU.

The application discloses a rendering precalculation system for power grid data, and relates to the technical field of power grid data.The rendering precalculation system comprises a data acquisition module, a data integration processing module, a rendering processing module, a display module, a data selection module, a data preprocessing module, a system verification module and a display selection module.The data acquisition module is responsible for collecting a large amount of real-time and historical data from various sensors, monitoring devices and databases of a power grid.The data integration processing module is used for integrating and processing the data collected by the data acquisition module, so that the data of the data acquisition module is more convenient for the rendering processing module to use after being arranged.The application filters and pre-processes data in priority through the data selection module, calls historical rendering data through a data comparison module, and starts system verification at regular time intervals through a timing module in the system verification module, so that the system operation efficiency is improved, the waste of computing resource is reduced, and the system operation stability is enhanced.

This invention proposes a robotic arm obstacle avoidance path planning method based on an improved ant colony algorithm, relating to the fields of robot path planning and intelligent optimization algorithms. This method endows the joint configuration space with a non-uniform metric structure induced by a metric tensor G(q), where G(q) is derived from the normalized joint inertia matrix W. I The algorithm consists of three parts: the singularity gradient outer product term and the obstacle spacing gradient outer product term. Local geodesic distances are approximated using the mean of the metric tensors at both ends of the node. All edge weights are pre-calculated and cached during the PRM graph construction phase. The ant colony uses the reciprocal of the geodesic distance as a heuristic function, drives non-uniform pheromone evaporation using the normalized value of the metric tensor trace increment, and uses the weighted sum of geodesic length cost and inertia-weighted velocity mutation penalty as the comprehensive path cost. The beetle whisker algorithm performs pre-search and completes non-uniform pheromone initialization under geodesic metrics. This method effectively improves path safety, continuity, and dynamic adaptability.

The invention concerns a computer program and a method for optimising quantisation in an attention-based neural network (40). The dataflow architecture of the network includes quantisation stages (41Q-47Q) downstream of respective transformation stages, which involve transformations (representable through transformation matrices) and offline transformations. The method first comprises optimising a transformation stage (41, 423) for subsequent quantisation by a respective quantisation stage (41Q, 42Q), by optimising an offline transformation of this stage in an unsupervised manner, the offline transformation representable through a dot product of an offline input tensor and an offline transformation matrix, using an objective function designed to reduce a degree of tailedness of a distribution of tensor components of a tensor resulting from said dot product. Next, this stage is precomputed at least partly by performing the optimised offline transformation as an affine transformation based on said dot product, and stored to ready the network for inferences.

The invention provides a path planning method, system and equipment based on a mixed satellite A and a medium, and belongs to the technical field of automatic driving path planning. The method comprises the following steps: constructing a variable-resolution grid map according to environment obstacle distribution, adopting a high resolution in an obstacle area, and adopting a low resolution in an open area; performing pose validity verification on the starting point and the target point; dynamically updating map obstacle information based on real-time sensor data; pre-calculating the RS curve connectivity from all discretized vehicle kinematics reachable points to a target point by adopting a parallel calculation mode, and establishing a directly connectable node set; in the process of executing the mixed A star algorithm, when the expansion nodes are located in the directly connectable node set, the pre-calculated RS curve is directly called to complete path planning, and search is terminated. According to the method, through the variable-resolution map and the pre-calculation mechanism, the calculation complexity is remarkably reduced, and the real-time performance and efficiency of path planning are improved.

The invention belongs to the technical field of artificial intelligence and high-performance computing, and discloses a dynamic sampling and parallelization acceleration method for pulse graph neural network computing. An innovative dynamic graph sampling mechanism is provided, the instantaneous importance of nodes is evaluated according to historical pulse activities of the nodes, limited computing resources are dynamically allocated to the nodes and areas with the most abundant information, and a sampling strategy is adaptively adjusted. Secondly, the invention further provides a state decoupling parallelization method, pre-calculation and caching are carried out on a stateless layer of the SNN, part of serial dependence between time steps is broken, and remarkable acceleration of the calculation process is achieved. According to the method, a better effect is achieved under different data sets, and compared with other methods, the method has competitiveness in performance. On a MINIST data set and a DvsGesture data set, on the premise that the accuracy rate is basically kept unchanged, a remarkable acceleration effect is achieved, and meanwhile memory consumption of the method is obviously reduced.

In various examples, optimized cluster templates (e.g., template triblock data, template CLASes or some portion thereof such as template range data, etc.) are precomputed for various patterns of triangle clusters (e.g., regular grids and / or irregular meshes of various edge resolutions) and corresponding compression levels. For example, optimized range assignments may be computed by iteratively generating candidate range assignments using different strategies, evaluating each range assignment using a designated metric (e.g., a cost that estimates, models, approximates, or otherwise quantifies the anticipated time cost of traversal), and tracking the best (e.g., optimized) range assignment (or top N) for each optimized triblock layout. As such, a range assignment may be iteratively optimized for each supported pattern of triangles and corresponding compression level, and may be used to generate a corresponding cluster template.

The invention relates to the technical field of database optimization, in particular to a distributed cache preloading-based SQL query result quick return method, which comprises the following steps of: performing parameter abstraction on an SQL to generate a key prefix; judging SQL fingerprint hotspots, marking preloaded objects, and writing the preloaded objects into a hotspot list; generating a preloading task by utilizing the hotspot list; designing cache and storage; loading the result set in a fragmentation manner, splitting the result set into a plurality of fragmentation tasks, and concurrently executing pre-computation by using threads; adding data consistency metadata when the cache is written; splicing cache keys, and querying cache and storage hit conditions; providing a cache failure and avalanche prevention mechanism of the step random TTL; and the gateway layer exposes cache system design and performance monitoring indexes, and triggers an alarm by using the cache system design or performance monitoring. According to the method, the problems of high passive back-to-source delay, inaccurate hotspot identification, poor data consistency, large result set loading bottleneck, cache avalanche and the like in the existing distributed cache technology are solved.

This invention relates to the field of quantum computing technology, and particularly to a method, system, computer device, and storage medium for optimizing the fidelity of quantum circuits. The method includes: acquiring the hardware parameters of the quantum circuit to be executed and the quantum processing unit cluster; standardizing the quantum circuit, analyzing the type of quantum gate and its active bits, and standardizing the multi-bit gates; constructing a unified fidelity cost model based on the quantum circuit and hardware parameters, and quantizing the cost into an additive cost; spatially partitioning the quantum circuit based on the coupling relationship between the quantum bits, and temporally partitioning the quantum circuit based on the quantum gate sequence to form a set of spatiotemporal sub-blocks; pre-calculating the partitioning cost for each spatiotemporal sub-block, and determining the candidate execution mode for each spatiotemporal sub-block accordingly; using a multi-objective global optimization algorithm to globally optimize the allocation scheme to obtain a set of optimal cooperative execution schemes; and outputting the quantum circuit mapping results.

A resource allocation method and device based on bitmap precalculation, the method comprising: generating a global resource state bitmap according to CORESET configuration in a PDCCH, precalculating a candidate pre-allocation bitmap set for each possible candidate PDCCH; extracting a corresponding pre-allocation bitmap from the candidate pre-allocation bitmap set as a candidate set bitmap; comparing the candidate set bitmap with the global resource state bitmap to determine whether the resources conflict, if the resources do not conflict, the resources are available, and then the resources are occupied. The present application transfers the complex function calculation at the scheduling time to the precalculation in the initialization stage, only needs simple bitmap retrieval and bit operation at the scheduling time, greatly shortens the PDCCH resource allocation time consumption, replaces the real-time intensive calculation by pre-storing the bitmap, significantly reduces the CPU load, focuses the processor on the core scheduling algorithm, reduces the resource redundancy consumption, and effectively improves the overall capacity and energy utilization efficiency of the communication system.

This invention discloses a path locking pre-calculation optimization method, device, equipment, and storage medium. The method adopts a point-to-line, small-to-large, layered, progressive, synchronous solution, anchor point boundary finding, and efficient pre-control approach. Through three major designs—vehicle model feature extraction and inclusion relationship pre-determination, map topology association preprocessing, node-to-node interlocking, road segment-to-node interlocking, and progressive interlocking calculation of road segments—combined with optimization techniques such as rapid distance threshold determination, nearest-point diffusion sampling collision detection, and synchronous solution of minimum release distance, the entire pre-calculation algorithm is lightweighted. This invention can reduce the amount of polygon collision detection execution during pre-calculation by more than 95%, shorten the total pre-calculation time of the entire road network by more than 95%, and reduce the peak CPU utilization to less than 10%. It is perfectly adapted to ultra-large-scale industrial AGV scenarios with 20,000+ road segments, 10,000+ nodes, and multiple path point intervals, possessing strong engineering practicality.

A kind of offshore wind farm power collection system loss pre-calculation and large-scale solution acceleration method, comprising: constructing initial mathematical model considering cable construction cost and life cycle loss cost, and then converting nonlinear loss term into linear cost coefficient through network loss pre-calculation subproblem, to obtain mixed integer linear programming model easy to solve;Based on the location of wind turbine and substation, the initial feasible solution of hot start that meets the engineering constraints is constructed by using clustering partition and intra-sector routing strategy;Based on distance threshold, potential connections are screened, connections exceeding the threshold in the hot start solution are supplemented to the candidate set to form the final candidate cable set;Combined with the candidate set and the hot start solution, the solver is used to solve the optimization model efficiently, and the planning scheme is output.The present application significantly improves the solution efficiency and engineering practicability of super large scale offshore wind farm power collection system planning under the premise of accurately depicting network loss economy through model linearization and systematic solution acceleration design.

Methods, systems, and devices for data management are described. The method may include obtaining a first backup of a host data store in a host environment, the first backup containing a set of multiple files from the host data store, generating, for one or more files of the set, a respective hash value using content of a respective file of the one or more files, storing the respective hash value for the one or more files of the set of multiple files in a database in association with metadata for the respective file, where the database is indexed based on hash values, querying the database for a hash value generated based on content of a compromised file, and identifying, in response to querying, a latest backup of the host data store of the host environment that does not contain the hash value for the compromised file.

The application discloses a kind of security control method, device and system based on homomorphic encryption, method includes the following steps: using BGN encryption algorithm to generate encryption table, the BGN encryption algorithm is finite times homomorphism, support once multiplication homomorphic operation and infinite times addition homomorphic operation;Multiple homomorphic operations are carried out in parallel, first parallel calculation ciphertext homomorphic multiplication operation, then execute ciphertext homomorphic addition operation;Calculate to generate decryption table, the ciphertext in the decryption table is not the same as the ciphertext form in the encryption table.Form.BGN encryption algorithm used in the application has higher security level relative to semi-homomorphic encryption algorithm, supports protecting encryption controller parameter and transmission signal simultaneously;BGN encryption algorithm is optimized by pre-computation lookup table and parallel calculation mode, the control efficiency of encryption controller is guaranteed;Encoding and decoder are used to quantize data in encryption control system, the asymptotic stability of encryption control system is ensured.

Provided is an NTT acceleration chip, including: a twiddle factor computing module, including a plurality of pre-computing units and a plurality of real-time computing units, where the plurality of pre-computing units is configured to compute several initial lines of twiddle factors and an inter-line step factor in parallel by using a primitive root of unity; and the plurality of real-time computing units is configured to repeatedly and iteratively compute other lines of twiddle factors in parallel according to the inter-line step factor; a transposition module, including a plurality of transposition units, configured to perform transposition processing on an input sequence in parallel, to obtain a transposed sequence; and an NTT computing module, including a plurality of butterfly computing units, configured to perform a butterfly operation of orders and a point quantity in parallel according to the twiddle factors and the transposed sequence, to obtain an output sequence.

The invention provides a digital clock recovery system and method, and relates to the technical field of digital signal processing. The system comprises an interpolator, a timing error detector, a loop filter and a numerically controlled oscillator which form a feedback loop. Wherein the interpolator is a polynomial interpolator and is used for obtaining an interpolation result or an intermediate value by inquiring a pre-calculation module so as to reduce the operation complexity; a digitally controlled oscillator determines a base point and a fractional interval for interpolation by operating bits on an internal phase accumulator value to avoid division operations. The method comprises the following steps: performing polynomial interpolation by querying a pre-calculation module; detecting a timing error; filtering the error; and updating the timing information by performing a bit operation on the phase accumulator value. By means of the scheme, unification of high precision and low delay is achieved, loop performance is improved, and system resource consumption is reduced.

The application discloses a path lock control precalculation optimization method and device, equipment and a storage medium, the method adopts the idea of first point and then line, first small and then big, hierarchical progression, synchronous solution, anchor point boundary search and efficient pre-control. Through three designs of vehicle model feature extraction and inclusion relation pre-determination, map topology association preprocessing, node and node interlocking, road section and node interlocking, and progressive interlocking calculation of road sections, combined with distance threshold value rapid determination, nearest point diffusion sampling collision detection, synchronous solution of minimum release distance and other optimization means, the precalculation algorithm full process lightweight is realized. The application can reduce the polygon collision detection execution amount in the precalculation process by more than 95%, shorten the total time consumption of the whole road network precalculation by more than 95%, and reduce the CPU peak occupancy rate to within 10%. The application perfectly adapts to the super large scale industrial AGV scene of 20000+ road sections, 10000+ nodes and multi-road point intervals, and has strong engineering practicability.