58 results about "Parallel generation" patented technology

The invention discloses a computational fluid mechanics-oriented parallel boundary layer grid generation method and device. The method comprises the following steps of: firstly, generating an initial background grid with boundary layer units according to an original CAD (Computer Aided Design) geometric model; then, according to the initial background grid and the topological connection relation thereof, obtaining an object plane boundary of the background grid and grid units connected with the object plane boundary so as to construct a fixed closed area; performing regional decomposition on the initial background grid by using a graph division tool; secondly, encrypting curved surface grids of the sub-regions; carrying out parallel calculation on normal vectors of curved surface grid points and a stratified progress long distance according to the boundary layer unit, and generating a triangular prism unit by applying a stratified progress method; and finally, carrying out quality detection and intersection judgment on all boundary layer units to obtain a complete boundary layer grid. According to the method, the defect of lack of a boundary layer grid parallel generation method in large-scale grid generation can be overcome, rapid parallel generation of large-scale boundary layer grids is realized, and the performance bottleneck in the aspect of generation efficiency is overcome.

The invention is suitable for the field of data processing, and discloses a parallel generation method of reply texts, terminal equipment and a storage medium. The reply text parallel generation method comprises the following steps: when input information is detected, generating a global vector corresponding to a dialogue context, and generating an initial reply sequence corresponding to the global vector; inputting the global vector and the initial reply sequence into an A-G module for parallel processing to obtain a plurality of candidate sequences; and generating reply content according to the candidate sequence. Through a parallel processing mechanism of an A-G module, a plurality of candidate sequences are generated through single iteration, and the time delay required by a traditional word-by-word generation method is shortened. The problem of delay caused by multiple iterations of a traditional sequence generation method is solved. In the global vector generation stage, through the synergistic effect of position embedding and multi-head self-attention, the sequential relation and deep semantics of the dialogue context can be captured. And a candidate sequence overall evaluation mechanism of an A-G module is combined, so that a semantic fault phenomenon caused by a local optimal solution in a traditional method is effectively avoided.

The invention discloses a water chilling unit fault diagnosis method and system for unbalanced data, and belongs to the field of water chilling unit fault diagnosis, and the method comprises the steps: restoring balance fault data with original data characteristics through employing original data based on a disturbance reconstruction mechanism; performing extraction and modeling on the time sequence characteristics and the space structure of the balance fault data by using a space-time automatic encoder, and reconstructing original data; respectively extracting time sequence features and topological features by utilizing a dynamic topological time sequence feature integration network, and performing adaptive fusion by adopting a dynamic gating fusion mechanism; and classifying the fused features to obtain a fault diagnosis result. According to the method, parallel generation of multiple types of fault samples is achieved, it is guaranteed that each type of generated fault data has similar time-space characteristics with original fault data, the method can adapt to the real-time changing working condition of the water chilling unit, collaborative modeling of time sequence characteristics and dynamic topological characteristics in a complex multi-sensor system of the water chilling unit is achieved, and the modeling efficiency is improved. And high-precision real-time diagnosis can also be realized on edge equipment.

A system and method for performing tensor transforms on customized digital hardware. The system is comprised of a plurality of computational blocks, a control unit, and memory. The control unit is configured to read the generated source tensor slices for the generated indexes and read from memory the source tensor data and weight data interpolate the tensor slices based on the weights according to a transformation guide. The source tensor data and tensor weights are sent to multiple computational blocks for parallel generation of interpolated output tensor data. The data in memory can be configured so that only one address is needed to read multiple tensor dimensions or a tensor slice. Additionally, the memory can be configured to accept multiple memory addresses in parallel. The computational block output provides a grid-sampled output tensor.

The invention discloses a transformer over-capacitance threshold value dynamic adjustment method based on real-time monitoring. The method comprises the following steps: S1, multi-dimensional total element real-time acquisition; s2, data layering preprocessing and directional transmission; s3, preliminarily judging an edge end basic threshold value and a cluster; s4, calculating insulation, environment and operation three-dimensional coupling threshold values; s5, optimizing a small sample causal interpretable AI threshold value; s6, new energy consumption and cluster cooperation threshold correction; according to the multi-dimensional strategy parallel generation method, by constructing an insulation, environment and operation three-dimensional coupling threshold calculation system, the suitability of super-capacity protection and the actual operation state of the transformer is improved; an AI threshold optimization framework can be explained by means of small sample causality, and transparency and reliability of super-capacity threshold adjustment logic are guaranteed; through the new energy consumption and cluster collaborative threshold correction and multi-strategy fusion optimization mechanism, the new energy consumption efficiency is guaranteed, and unnecessary protection actions are reduced through cluster load linkage.

The invention relates to the technical field of pseudo-random binary sequence design, in particular to a parallel PRBS generation method and system for testing a multi-protocol high-speed serial transceiver, and the method comprises the steps: setting demand parameters of a pseudo-random binary sequence for testing the multi-protocol high-speed serial transceiver, and enabling the demand parameters to comprise an order, a bit number and a feedback polynomial; constructing a generator matrix for describing state transition of the linear feedback shift register according to the feedback polynomial; according to the bit number of the pseudo-random binary sequence, generating a mapping matrix of the pseudo-random binary sequence through the exponentiation of the generated matrix; based on the mapping matrix and the current beat linear feedback shift register state, outputting a pseudo-random binary sequence meeting the requirement parameters for testing the multi-protocol high-speed serial transceiver. According to the method, parallel generation of any PRBS can be supported, the PRBS parallel implementation logic configuration is simple, the hardware implementation complexity is low, the PRBS output throughput rate is high, and the design requirements of multi-protocol high-speed SerDes can be met.

The invention discloses a hydrological electronic achievement archive batch output method and system and a medium, and the method comprises the following steps: data extraction: reading annual calibration data of specified equipment from a database, including calibration time, a standard value, a measured value and an error rate field; template rendering: reading an Excel template by using a POI (Point of Interest), and mapping data to a template placeholder; and PDF generation: creating a Document object by the iTextPDF, setting a page margin, inserting a page header, dynamically rendering a table, and outputting the PDF through HttpServletResponse. And in combination with intelligent excel-to-pdf of the StirlingPDF, a three-level processing normal form of'type shunting-parallel generation-dynamic assembly 'of the equipment detection document is realized in a breakthrough manner.

The invention discloses a dual reasoning acceleration method based on draft prediction and compressed memory, which comprises the following steps of: 1) acquiring an input context of model reasoning and a token sequence generated by a model at each stage of reasoning; 2) according to an input context of model reasoning and a token sequence generated by the model, predicting subsequent candidate tokens in parallel as draft tokens; the method comprises the following steps of (1) performing parallel generation, (2) performing main model verification, (3) organizing draft tokens according to a tree structure, (4) performing main model verification, (5) compressing each reasoning block into compressed tokens with a fixed length s, and (6) performing context reconstruction. According to the method, through the combination of parallel generation and context compression, the problem of serial low efficiency of traditional autoregression is solved, and the redundant overhead of long-sequence reasoning is relieved.

Systems and methods for dynamic adaptation of radiotherapy are disclosed. Example operations for radiotherapy planning include obtaining a radiotherapy problem (e.g., a multi-criterion optimization problem) for providing radiotherapy; performing treatment plan optimization for delivery of radiotherapy; and generating treatment plan data based on at least one of the plurality of solutions, wherein such treatment plan data is used to generate a radiation treatment plan for the particular human subject with the radiation treatment machine. In one example, treatment plan optimization includes identifying a parameterized linear programming equation from a radiation treatment problem; converting the parameterized linear programming equation for execution by parallel processing hardware; and solving the plurality of converted parameterized linear programming equations in parallel on parallel processing hardware to produce a plurality of solutions (e.g., including a Pareto surface) of the radiation therapy problem corresponding to the parameters defining the radiation therapy problem.

The application relates to an acceleration method of an AES key expansion algorithm and an instruction set processor, wherein the acceleration method is based on a VAESKEYE extension instruction set, a plurality of independent AES key expansion algorithms are accelerated in parallel by pipelining execution of instructions in the VAESKEYE extension instruction set; the VAESKEYE extension instruction set adopts a RISC architecture and is used for generating any one of AES key expansion words in the AES key expansion algorithm according to a source operand; the VAESKEYE extension instruction set adopts a plurality of AES key expansion word parallel generation algorithms, the plurality of AES key expansion word parallel generation algorithms refer to algorithms for taking a key word or a key expansion word and an AES key expansion round number in 8 independent AES key expansion algorithms as inputs and respectively completing generation of 8 independent AES key expansion words in parallel. The application greatly improves the speed of executing the AES key expansion algorithm.

The application discloses a kind of parallel random number generation devices based on pulse driving micro-ring resonator cavity, by adopting pulse mode driving micro-ring resonator cavity, improve the instantaneous power level in cavity, enhance nonlinear effect, to effectively expand the effective bandwidth of chaotic entropy source, improve the complexity of entropy source.Meanwhile, using the characteristics that micro-ring resonator cavity naturally supports multi-wavelength output, and combining with filter demultiplexing structure, the parallel output of multiple chaotic entropy sources is realized, which is beneficial to improve the parallel generation ability of random number.Finally, by combining post-processing methods such as difference, quantization and decorrelation, the overall generation rate of random bits is improved while ensuring randomness quality.The application has relatively simple structure, is suitable for integrated implementation, and can meet the application requirements of high-speed parallel random number generation.

Embodiments of the present disclosure relate to a method, an apparatus, an electronic device and a medium for event extraction. The method comprises: extracting a plurality of named entities from a document as a plurality of event arguments. The method further includes determining an event type and a template corresponding to the event type in the document. The method also includes filling the plurality of event arguments in respective locations in the template to generate a plurality of candidate event records, and filtering the plurality of candidate event records to obtain one or more target event record. In this way, respective candidate event records are generated through iteration while event extraction is performed at a document level, which can avoid performance fluctuations caused by manual selection of an event role generation sequence, and can also avoid under-fitting brought about by parallel generation to thus improve the event extraction accuracy.

The invention provides an aircraft manufacturing process instruction intelligent generation method based on hybrid retrieval enhanced generation, and the method guarantees that a generated instruction has professional sentence patterns with historical experience and compliance indexes with standard specifications through a hybrid retrieval mechanism. A large model is limited in a specific process generation link through the agent workflow, strict placeholder filling logic is matched, the illusion problem that key parameters are pinched by the model is thoroughly eradicated, meanwhile, the parallel generation architecture enables the generation time of a long-flow process instruction to be greatly shortened, and unification of high accuracy, high controllability and high efficiency is achieved.

This invention provides a method, apparatus, electronic device, and storage medium for generating multiple candidate responses, belonging to the field of artificial intelligence technology. The method includes: inputting a target prompt into a large language model; generating multiple candidate responses for the target prompt through multiple parallel generation threads; during the generation of multiple candidate responses word-by-word, obtaining hidden state features corresponding to each parallel generation thread using the network layer of the large language model; performing batch-dimensional attention calculations on each hidden state feature using a cross-thread shared layer to obtain shared state features; and using the output layer of the large language model to predict the output words of each parallel generation thread based on the shared state features. This invention breaks the independence between parallel generation threads by introducing a cross-thread shared layer between the network layer and the output layer, enabling interaction and fusion of feature dimensions among the threads during the generation process. This effectively utilizes the global information of the parallel group, improving the diversity and quality of generated candidate responses.

The invention discloses an auto-regression and mask diffusion double-normal-form fusion language model hardware acceleration system based on an FPGA (Field Programmable Gate Array), and relates to the field of FPGA and machine learning. The invention provides a model core calculation process-oriented hardware acceleration architecture by aiming at a language model fusing double normal forms of an autoregression model and a mask diffusion model and adopting the characteristics of revising an attention mechanism and parallel generation of a KV cache. The method disclosed by the invention is implemented by taking an Eso-LMs (Esolic Language Models) model as an example. The system comprises a layer normalization and adaptive layer normalization modulation module, a QKV projection module, a rotation position coding application module, a KV cache management module, a multi-head attention calculation module, an output projection and residual connection module and a multi-layer perceptron module. By optimizing the calculation sequence and the data flow of each module in the model calculation process and adopting the pipeline parallel and resource reuse technology, the efficient reasoning acceleration of the language model fusing the autoregression and mask diffusion double normal forms on the FPGA platform is realized, and the model reasoning speed is obviously improved. According to the system, the advantage of FPGA customizable hardware acceleration is fully exerted, the utilization efficiency of hardware resources is improved, data pipeline blockage is eliminated, calculation delay and storage overhead are reduced by reconstructing the data flow direction and constructing a whole-process pipeline processing architecture, and the system is suitable for the deployment requirement of an edge calculation scene.

The embodiment of the invention relates to the technical field of artificial intelligence, and provides a parallel generation method of response texts and electronic equipment. The method comprises the following steps: receiving a group of tokens, and obtaining a representation vector corresponding to each token based on at least one historical text block and the token; denoising the representation vectors corresponding to the group of tokens in parallel, and obtaining a prediction text block corresponding to the group of tokens based on the denoised representation vectors; in response to the fact that the reasoning task is not completed, taking the prediction text block as a new historical text block, generating a group of new tokens based on at least one historical text block, and returning to the step of obtaining the representation vector corresponding to each token based on the at least one historical text block and the token by using the coding module; and in response to completion of the reasoning task, obtaining a response text corresponding to the reasoning task based on the at least one historical text block and the predicted text block. According to the method provided by the invention, the token of the response text can be generated in a parallel mode, and the problems of long reasoning delay and low response speed in the prior art are solved.

This application proposes an automatic method and apparatus for generating distillation data in underground coal mines. The method includes: acquiring unlabeled data and combining it with instruction data to form a distillation dataset, and distributing it to multiple parallel generation channels; forming a structured candidate inference result set; fusing and calibrating the candidate inference result set to generate labeled distillation data, performing multi-dimensional qualification checks, and selecting valid labeled results; constructing an unbiased distillation training dataset, and inputting it into the target model for supervised fine-tuning training to obtain a distillation model adapted to underground coal mine scenarios. By automatically generating highly diverse distillation data that conforms to the characteristics of underground scenarios, the problem of high labeling costs and uneven data quality is effectively solved; the model's distillation performance is improved through preference consistency constraints and multi-dimensional quality checks, significantly enhancing the generalization ability and recognition accuracy of the distillation model in complex underground environments.

The invention discloses an unsupervised real image denoising method based on a self-cooperation parallel generative adversarial network. The method mainly comprises the following steps: constructing a noise extraction module based on an initial denoiser by using the superposition of noise, and extracting noise components of a real image; a parallel generation confrontation branch framework is adopted, a branch 1 synthesizes a pseudo real noise image through a non-pairing synthesis mode and then synthesizes a noise image through a self-synthesis mode, namely, non-pairing synthesis-self-synthesis; the branch 2 is used for synthesizing a noise image in a self-synthesis mode and then synthesizing a pseudo real noise image in a non-pairing synthesis mode, namely self-synthesis-non-pairing synthesis; and adopting a self-cooperation strategy, replacing the previous weaker de-noising device with the current more convergent de-noising device after each iteration until the de-noising device is completely convergent, completing network training and obtaining a final model. According to the method, noise on a real image can be well removed, and the method is an effective image denoising method.

The invention relates to the technical field of finite element grids, and particularly discloses a block structure method-based hexahedral grid parallel generation method for a fast reactor core component, which comprises the following steps of: performing Delay inner triangulation in an area on the same side of a winding wire, solving a Laplace equation to generate an isoline, and generating an orthogonal grid according to the isoline; obtaining a triangular surface grid template on the same side of the winding wire; dividing the fuel rod assembly into six sections, dividing each section into a plurality of layers, taking the first section as a basic section, dividing block grids in each layer on the basis of the triangular surface grid template on the same side of the winding wire, generating quadrilateral surface grids in the block grids, rotating the grids on each layer at a set angle once to obtain grids on each layer of other sections, and forming the quadrilateral surface grids on the same side of the winding wire; the grids of all the layers are connected to form a hexahedral grid model; the hexahedral mesh model is expanded; and carrying out parallel optimization on the loop call function. According to the method, the problems that the hexahedral mesh of the fast reactor core assembly cannot be correctly generated and the mesh division efficiency is low are solved.

The invention provides an underground mine live-action three-dimensional modeling system and method based on unmanned aerial vehicle SLAM and multi-sensor fusion. The underground mine live-action three-dimensional modeling system comprises a hardware platform and a software platform. The hardware platform takes an unmanned aerial vehicle as a main body, and integrates a visual sensor, a laser radar, an IMU, a self-adaptive lighting system, a visual laser acquisition control point device, a roof control point identification camera and a wireless communication module; the wireless communication module is used for transmitting the acquired data back to a software system in real time and transmitting remote control instructions among the components; the software platform comprises a front-end SLAM module and a modeling and rendering module; the front-end SLAM module adopts a vision-laser radar-IMU tight coupling SLAM algorithm and fuses control point data acquired by a top plate control point identification camera to realize real-time point cloud registration and map construction of absolute coordinate constraint in a GPS-free environment; the core of the modeling and rendering module is a Mesh and 3DGS double-model parallel generation technology, and the modeling and rendering module has the parallel operation capability of synchronously completing Mesh model generation and 3DGS model training.

The present invention belongs to the technical field of language model text generation, and relates to an automatic parallel language model text generation method, which comprises the following steps: 1) constructing structured training data; 2) fine-tuning structured instructions; 3) automatic parallel generation; 4) traversing paragraph trees. The present invention uses structured data to fine-tune the instructions of the language model, so that during the generation process, the language model automatically issues parallel generation instructions to the reasoning system in combination with the language model's own understanding of the generated content structure, generates multiple parallel generation streams, and thus increases the parallel degree of the language model generation.

The invention discloses a content generation data processing method and system based on multi-agent collaboration, and the method comprises the steps: carrying out the semantic deconstruction of a multi-modal content demand inputted by a user through a task analysis agent, and generating a structured task description vector containing a theme dimension, a style element and an emotional tendency; generating a multi-modal content draft based on the structured task description vector; inputting the multi-modal content draft into a quality evaluation agent network, and generating a quality evaluation matrix containing semantic coherence scores and style matching degrees; and dynamically adjusting a content generation strategy through a decision coordination agent according to the quality evaluation matrix, optimizing an agent cooperation weight by adopting a reinforcement learning mechanism, and outputting a final optimized multi-modal content work. By utilizing the embodiment of the invention, high-quality and high-consistency parallel generation and deep fusion of multi-modal contents such as texts, images and audios can be realized, and the creativity and semantic coherence of final works and the matching degree with user requirements are improved.

The invention discloses an electric vehicle self-charging system and a self-charging method thereof. The system comprises a first motor, a second motor, a first generator, a second generator, a vehicle-mounted battery and a control circuit. In the running process of the vehicle, the system converts kinetic energy of the vehicle into electric energy and stores the electric energy in a vehicle-mounted battery through an energy recovery mode and a parallel power generation mode; when the vehicle is in a static state, through a static power generation mode or a low-power operation mode, self-charging is achieved through a low-power-consumption motor and a high-efficiency generator. The control circuit dynamically adjusts the working mode of each component according to the running state and working condition of the vehicle, and the energy recovery and charging efficiency is optimized.

The present invention discloses a parallel boundary layer mesh generation method and device for computational fluid dynamics. The method includes: first, generating an initial background mesh with boundary layer elements according to the original CAD geometric model; then, obtaining the physical surface boundary of the background mesh and the mesh elements connected thereto based on the initial background mesh and its topological connection relationship to construct a fixed closed region; further, performing regional decomposition on the initial background mesh using a graph partitioning tool; secondly, densifying the surface mesh of the sub-region; then, performing parallel calculations on the normal vectors of the surface mesh points and the layer advancement distance according to the boundary layer elements, and generating triangular prism elements by applying the layer advancement method; finally, performing quality inspection and intersection judgment on all boundary layer elements to obtain a complete boundary layer mesh. The present invention can make up for the regret of the lack of a parallel generation method for boundary layer meshes in large-scale mesh generation, realize the rapid parallel generation of large-scale boundary layer meshes, and overcome the performance bottleneck in terms of generation efficiency.

The invention provides a multi-machine surveying and mapping management method and device, electronic equipment and a storage medium, and relates to the technical field of surveying and mapping. The method comprises the following steps: receiving a task instruction comprising a target ground resolution, a minimum overlapping degree, a task priority and a landform situation; according to the target ground resolution and a preset algorithm, calculating to obtain a navigation height, generating a plurality of navigation routes in combination with the landform situation, the lowest overlapping degree and the preset algorithm, and then generating control instructions corresponding to the unmanned aerial vehicles in combination with task priorities to control the unmanned aerial vehicles to perform surveying and mapping; and during surveying and mapping, surveying and mapping data returned by the unmanned aerial vehicles are spliced in real time. According to the method, the navigation height of the unmanned aerial vehicle is determined through the target ground resolution, and the navigation route is correspondingly generated according to the landform condition by combining the lowest overlapping degree, so that parallel generation of the multi-vehicle navigation route is realized, and surveying and mapping data returned by each unmanned aerial vehicle are spliced in real time; therefore, the reasonability of route planning and task allocation during unmanned aerial vehicle surveying and mapping is improved, and the surveying and mapping accuracy and efficiency are improved.

The present invention relates to a parallel syndrome generation device for a MPEG-2 synchronization byte decoder based on a lookup table, applicable to the digital multi-program system B recommended by ITU-T J.83. The device is characterized in that it mainly consists of a 1504-bit memory, 15 registers R0 to R 14 , 128 two-input AND gates and 128 two-input XOR gates. The syndrome generation device provided by the present invention inputs the received data of 188 bytes in a 16-bit parallel manner and outputs 1-byte syndrome in an 8-bit parallel manner, which can effectively reduce the logical resource requirements while increasing the processing speed by 16 times, and has the advantages of fast running speed and less consumption of logical resources.

The application discloses a text candidate screening method and device. The method comprises the following steps: obtaining initial candidate texts generated in parallel by a language model, and calculating the quality scores of the initial candidate texts; performing an iterative screening step to determine final candidate texts, which firstly takes the text with the highest quality score as the first final candidate text, and then in the repeatedly performed selection operation, for each candidate text, calculates the difference score between the candidate text and the selected final candidate set, and calculates a comprehensive score based on the quality score and the difference score, and determines the candidate text with the highest comprehensive score as the new final candidate text. The application guarantees efficiency through parallel generation, and solves the problem that it is difficult to balance the quality and diversity of generated texts in the prior art through the iterative screening strategy combining the quality score and the dynamic difference score, so that the diversity of the final candidate set can be significantly improved while ensuring high quality.

This invention discloses a cloud-based dialogue response method, device, and medium for AI toys, relating to the field of natural language processing technology. The method includes: performing structured task translation processing on a semantic constraint guidance graph and writing corresponding fields to generate a task-driven script; using a constraint projection hierarchical construction method to perform hierarchical response channel orchestration and parallel generation processing on the task-driven script and the semantic constraint guidance graph to obtain hierarchical candidate response clusters; performing convergence and optimization compensation on the hierarchical candidate response clusters to obtain the target response content, and combining the target response content with the task-driven script to encapsulate an executable response, generating a cloud-based response result package; and performing terminal response delivery and memory storage write-back based on the cloud-based response result package to generate response execution information. This invention, by performing semantic deconstruction and relational constraint construction on the natural language requests of AI toys, helps improve the accuracy, coherence, and terminal execution adaptability of the final response content.

A system and method for performing tensor transforms on customized digital hardware. The system is comprised of a plurality of computational blocks, a control unit, and memory. The control unit is configured to read the generated source tensor slices for the generated indexes and read from memory the source tensor data and weight data interpolate the tensor slices based on the weights according to a transformation guide. The source tensor data and tensor weights are sent to multiple computational blocks for parallel generation of interpolated output tensor data. The data in memory can be configured so that only one address is needed to read multiple tensor dimensions or a tensor slice. Additionally, the memory can be configured to accept multiple memory addresses in parallel. The computational block output provides a grid-sampled output tensor.

The application discloses a kind of application log fragment parallel generation and multi-level materialized view aggregation processing method, predefine application log general framework using standard log format and carry out encapsulation, at least including application identification, log type and log detailed content;In application, the log generator instance of encapsulated application log general framework is introduced, and it is matched to log recording demand, and the API provided by application log general framework is called to generate log record at the log recording point of the program code of application, and application log general framework establishes mapping relationship with application by application identification;When debugging or running application, application log is generated, and saved as original log file;In response to log aggregation instruction, according to preset aggregation strategy, multi-level materialized view aggregation processing is carried out to original log file, and saved as aggregation log file.The application can solve the technical problems that application log format is not standard, content is difficult to analyze, and mass log is difficult to compress.