47 results about "Computation type" patented technology

An architecture of a multi-cloud inspector for any computing device type is provided. According to an embodiment, a method for implementing multi-cloud inspection includes accessing an object list, determining which objects to inspect, determining which inspectors to use, creating object copies, providing and running inspectors for each object copy, receiving inspection report summaries, generating an enriched dataset, and adding the enriched dataset to a security graph database.

The invention discloses an accurate formula calculation method and device based on a large language model, and the method comprises the steps: receiving a mathematical formula image inputted by a user and a calculation request described by a natural language, carrying out the recognition of the mathematical formula image, generating a standard LaTeX expression, carrying out the grammar and semantic verification, employing the large language model to analyze the calculation request, and carrying out the analysis of the calculation request. The method comprises the steps of identifying a calculation type, a target variable and a parameter, outputting a structured operation instruction, converting a standard LaTeX expression into a mathematical object compatible with a symbol calculation library according to the structured operation instruction, dynamically declaring a symbol variable according to the operation instruction, and executing symbol operation based on a parameter extraction result to obtain a symbol calculation result. A symbol calculation result is converted into a readable format to be output, LaTeX mathematical expressions and natural language description are supported, a large language model and a multi-modal model are used for accurately recognizing a formula and analyzing a user natural language problem, complex symbol calculation and equation solving are automatically completed, tasks can be automatically completed through natural language interaction, and the use threshold is lowered.

The invention discloses a calculation circuit, a data processing method, a storage medium and electronic equipment. Wherein the calculation circuit comprises an instruction processing sub-circuit, and the instruction processing sub-circuit is used for obtaining atomic instructions and caching the atomic instructions corresponding to the same target operation address in the same target queue; the calculation sub-circuit is used for obtaining original data, corresponding to the target operation address, in the memory, calculation types indicated by the atomic instructions in the target queue and sorting attributes of the atomic instructions in the target queue; generating target calculation result data based on the original data, the calculation type and the sorting attribute; and updating the original data corresponding to the target operation address into the target calculation result data. According to the embodiment of the invention, the execution efficiency of the atomic instruction can be improved.

The invention provides an atomic index generation method based on real-time data streaming processing, and relates to the technical field of data processing, and the method comprises the steps: generating a cache key based on an attribute unique code and an atomic index code, and querying whether a corresponding index calculation object exists in a cache; if the cache object does not exist, initializing an index calculation object comprising an index value, a start timestamp, a calculation type, an atomic index code and a calculation rule, and storing the index calculation object into a cache; if the cache object exists, corresponding index calculation operation is executed according to the calculation type, the index calculation operation comprises duration calculation, accumulated value calculation, aggregation calculation or user-defined rule calculation, and an index value in the cache is updated; writing the cached index values into a target database in batches according to a preset time period, and avoiding repeated writing by taking timestamps and the atomic index codes as unique identifiers; and resetting the index value in the cache to prepare for the next calculation period.

According to the reconfigurable multiply-accumulate unit for the neural network processor and the processor, an efficient reconfigurable multiplier is constructed by organizing a large number of low-precision multiplication units. A peripheral reconfigurable computing circuit is designed to form a multiply-accumulate unit, so that the multiply-accumulate unit can flexibly support computing requirements of various precisions, various computing types and various data paths, and the compatibility and efficiency of hardware to a neural network are remarkably improved.

The present application provides an addition tree computation device, method and computation device for the addition operation of floating-point numbers and fixed-point numbers. The data input module receives input data and calculation type instructions; the transmission control module controls the first multiplexer, according to the calculation type instructions, to send floating-point numbers to the first entrance of the fusion calculation module, or to send fixed-point numbers to the second entrance of the fusion calculation module; the fusion calculation module is used to perform addition operations, and the data normalization output module performs output processing on the operation results according to the control of the transmission control module, and outputs the final calculation results. Through the modification and design of the fixed-point number addition tree chip circuit, high-speed and high-precision addition operations for two data types including floating-point and fixed-point numbers are realized.

Provided in the present application is a method for fusing operators in a computational graph, which method is applied to an AI compiling process. The method comprises: acquiring a target graph, wherein the target graph comprises a plurality of nodes and at least one edge, and the nodes are associated with operators in a computational graph; determining computation types of two nodes connected to a first edge, wherein computation logic of two operators corresponding to the two nodes both comprise a loop statement; and on the basis of a first computation type and a second computation type, fusing the loop statement of one operator into the loop statement of the other operator, so as to obtain a fused operator which is obtained by means of fusing the two operators. In the solution provided in the present application, it is not necessary to compress all loop statements of operators into one dimension and recalculate indexes for the operators, instead, two operators can be fused by means of computation types of the two operators, so that a high-performance fused operator can be obtained.

Techniques for building and maintaining model webs are described. In some examples, a model web is built by selecting models for the model web from one or more available model types based on at least one or more of availability, tensor information, and compute type, instantiating synapses between the selected models to form the model web and updating information regarding availability of the selected models of the model web to indicate being in use.

The invention discloses a Pandas expression generation system based on visual interaction, and belongs to the technical field of data processing. The front-end interaction layer is used for providing a graphical interface; the logic processing layer is used for converting a Pandas expression character string; and the expression storage layer is used for storing the generated expression in a JSON format. According to the method, a user can intuitively configure a data set, a screening condition, a grouping dimension and a calculation type through a graphical interface, and a system automatically converts configuration into a Pandas expression and stores the Pandas expression; according to the scheme, the problem that a traditional data processing tool depends on the programming capability is solved, the efficiency and autonomy of data processing are improved, and the method is suitable for scenes such as data analysis and business reports.

An aspect of the present disclosure facilitates routing diverse incoming requests to optimal computing options while satisfying requisite performance metrics. In one embodiment, in a computing environment having multiple compute types, a historical data containing characteristics in transport payloads of incoming requests, and characteristics in processing corresponding incoming requests by respective compute types is collected. A system trains, based on the historical data, a machine learning (ML) model to select compute types for incoming requests. Upon receiving a new incoming request sought to be processed, the system extracts from a transport payload of the new incoming request, the first set of characteristics to create a new request context. The system then applies the ML model to the new request context to identify a target compute type and forwards the new incoming request to the target compute type.

The invention provides a server energy efficiency optimization system and method based on heterogeneous computing and a storage medium, belongs to the technical field of data processing, and is used for optimizing the energy efficiency of a server of heterogeneous computing through computing with a computing tool as granularity. The method comprises the following steps: an orchestration agent obtains description information from a consumption entity, wherein the description information is used for describing a consumption entity request to obtain a target service; the orchestration agent splits the target service into N sub-services and determines N calculation tools of which the calculation types are matched with the N sub-services one by one from the M calculation tools, and N is an integer larger than 2 and smaller than or equal to M; the orchestration agent calls N calculation tools to execute calculation of the N sub-services, and results of the N sub-services are obtained; and the orchestration agent combines the results of the N sub-services into the result of the target service, and returns the result of the target service to the consumption entity.

The application discloses an AI generated text detection method, system, device and medium, and relates to the technical field of text processing. The application converts a Chinese text sentence to be detected into a tone category sequence composed of tone categories. In this process, the categories of Chinese tones are used as a quantitative index of phonological structure, and text analysis is converted from a high-dimensional and high-cost semantic space to a low-dimensional and high-efficiency phonological feature space. The application is not dependent on training data of a specific model and is adaptable to text detection of multiple models. Then, N-gram analysis is performed on the generated tone category sequence, and the occurrence frequency of each N-gram combination is calculated to form a feature vector. Finally, an AI generated text is judged through a pre-trained classification model. In this process, the calculation type in processing is mainly string processing and frequency statistics, and the inconsistency problem of the model in multiple model invocations is avoided, so that the AI generated text can be accurately detected.

The application provides a splitting implementation method of a RISC-V vector cryptography instruction, which splits a message scheduling instruction into a plurality of micro-instructions for execution on a processor with a vector data path bit width of 128 bits according to a preset splitting rule in an instruction decoding stage, the splitting rule comprising: obtaining a message scheduling instruction in a SHA-512 algorithm, the message scheduling instruction being used to expand an input message block into a required message sequence; splitting the message scheduling instruction into a 0th type micro-instruction for processing a transformation path of sig0 and a 1st type micro-instruction for processing a transformation path of sig1 according to a calculation type; and the method does not introduce additional storage data space, and can reduce the area overhead of the processor for implementing the instruction while maintaining the unit data path operation throughput.

The application provides a transaction statistics method and device. The method comprises the following steps: obtaining a configuration object of a target statistics variable, the configuration object being generated according to a configuration operation of a user on a configuration page, the configuration object corresponding to a preset data structure; obtaining a calculation type and a condition object from the configuration object according to the preset data structure, the condition object comprising a condition attribute, the condition attribute being used for defining a matching rule of the condition object; obtaining at least one piece of transaction data; for each piece of transaction data, matching the transaction data with the condition object, and when the matching with each condition object is successful, updating a statistics result of the target statistics variable according to the transaction data and the calculation type. The application can generate a configuration object of a statistics variable according to user input. When it is necessary to add, modify and delete the statistics variable, the user only needs to re-input information of the statistics variable, and the software code does not need to be modified, thereby reducing the cost of adding, modifying and deleting.

The present application provides a method, device, equipment and storage medium for determining the online time in a game, belonging to the technical field of data storage. The method includes: obtaining the identifier of the target virtual character and the target time range; determining the target calculation type based on the target time range and the pre-stored time data, where the target calculation type includes: historical data reading or new data calculation, and the pre-stored time data includes: the historical login data of the target virtual character; if the target calculation type is new data calculation, obtaining the target login data of the target virtual character in the target time range from the game log library of the game; if the target calculation type is historical data reading, obtaining the target login data from the pre-stored time data; and determining the online time data of the target virtual character according to the target login data. The present application can obtain the online time data more quickly and efficiently, reducing the waste of computing resources.

An architecture of a multi-cloud inspector for any computing device type is provided. According to an embodiment, a method for implementing multi-cloud inspection includes accessing an object list, determining which objects to inspect, determining which inspectors to use, creating object copies, providing and running inspectors for each object copy, receiving inspection report summaries, generating an enriched dataset, and adding the enriched dataset to a security graph database.

An architecture of a multi-cloud inspector for any computing device type is provided. According to an embodiment, a method for implementing multi-cloud inspection includes accessing an object list, determining which objects to inspect, determining which inspectors to use, creating object copies, providing and running inspectors for each object copy, receiving inspection report summaries, generating an enriched dataset, and adding the enriched dataset to a security graph database.

The invention relates to the technical field of computers, and provides a correctness verification method and device for a large-scale text sequence BWT, equipment and a medium. The method comprises the following steps of: blocking a character string X and a suffix number group of the character string X, and shrinking the character string X by recursively calling block induction sorting until a character in the shrunk character string X1 is unique; in the backtracking stage of the recursive 0 layer, calculating the sequence of S * type suffixes of X according to the suffix array of X1, and calculating the hash value of a descending S * type suffix sequence; according to the sequence of the S * type suffixes of the character string X, calculating L type and S type suffix preamble character sequences of each block and hash values of the L type and S type suffix preamble character sequences; calculating an L * type suffix sequence and the hash value of each block of the L type BWT sequence by adopting a small top heap; calculating the hash value of each block of the S * type suffix sequence and the S type BWT sequence by adopting a large top heap; and combining the two types of BWT sequences, and outputting a final verification result, so that the space-time overhead of BWT correctness verification is reduced.

The invention discloses a three-dimensional model concurrent analysis method and system based on multiple processes and a medium. The method comprises the steps that an analysis task is obtained, and an instance object of three-dimensional model analysis is obtained according to the type of the analysis task; according to the corresponding relation between the analysis task type and the calculation type, the calculation type of the analysis task is recognized, and a plurality of sub-tasks of the calculation type are obtained through decomposition according to the instance object; analyzing the performance of corresponding hardware according to the calculation type of the task; according to the hardware margin, a concurrent operation scheme of a plurality of subtasks of different calculation types is formulated; according to the concurrent operation scheme, generating a plurality of operator sub-processes and adding the operator sub-processes into a process pool; and starting the process pool, summarizing the operation result file of each arithmetic unit to obtain an operation result, and completing analytic operation. According to the method, the multi-process concurrency technology is introduced by formulating the concurrency operation scheme, so that the analysis operation efficiency of the three-dimensional model is improved, and the construction of a unified product data pool is promoted.

The invention discloses a processor performance test method, device and equipment and a storage medium, and relates to the technical field of performance test.The processor performance test method comprises the steps that a performance test program is compiled into a machine instruction, the machine instruction is divided into a plurality of instruction blocks, and all the instruction blocks are marked according to target labels; the target label comprises an instruction type and a memory access mode; the instruction type comprises a floating point calculation type and an integer calculation type; obtaining performance data of each kernel when the processor executes the task; the performance data comprises a core utilization rate, a cache hit rate, memory delay and inter-core communication delay; distributing the instruction block to a target kernel of the processor based on the target label and the performance data, so that the target kernel executes the instruction block to obtain corresponding test data; and recording the test data, and determining a performance test result of the processor according to the test data. Therefore, the effectiveness of the performance test can be improved.

Embodiments of the present disclosure may provide a processing unit and a computing system that divide computations according to the types of computations performed during an inference computation using an artificial intelligence model and perform the divided computations by separate processing units, thereby being capable of reducing an overall time required for the inference computation and improving the performance of the inference computation.

The invention relates to a heterogeneous multi-core task scheduling and heat balance control method and device for an X21E processor. The method comprises the following steps: constructing a dynamic weighing multiprocessor cluster interconnection system based on a CXL protocol; according to the functional positioning and real-time demand difference of the dynamic weighing data, data transmission is realized by adopting a dual-channel transmission logic in which metadata and original data are separated; acquiring thermal state information of each processor endpoint in real time, and judging whether task migration is triggered or not; computing resources of all processor end points are virtualized into shared computing power pools, and adaptive resources are distributed from the corresponding computing power pools according to the computing types and computing power requirements of the dynamic weighing tasks; and when a thermal balance scheduling condition is met, the non-interruption migration of the dynamic weighing task is carried out, and thermal balance control and task scheduling of the multiprocessor cluster are completed. According to the method, the problems of high data interaction time delay, uneven cluster heat distribution, poor CXL technical scene adaptability, task migration data loss and rigid computing power configuration of a multiprocessor cluster in a dynamic weighing scene are solved.

The invention relates to the technical field of data processing, in particular to a data label definition and configuration method and system based on a trusted data space, and the method comprises the following steps: generating a unique label identifier, executing a calculation type decision based on a stream batch integrated architecture, executing metadata conversion, and configuring a label based on a multi-modal label definition system. The method has the beneficial effects that the label definition complexity is reduced: an open rule definition mechanism is adopted, so that business personnel can autonomously define the label without a professional technical background, the use threshold of a label system is greatly reduced, and the label configuration efficiency is improved; through a multi-type label combination mechanism and a multi-dimensional association query function, deep mining of data values is realized, so that a single data source can derive dozens of service labels, and the data reuse rate is remarkably improved.

The application relates to a method and device for implementing reduction calculation, a computer device, a readable storage medium and a program product. The method comprises the following steps: arranging first registers used by a plurality of threads in a thread bundle corresponding to a target reduction calculation into a register block, the numbers of the first registers used by each thread being the same; generating j pooling instructions based on the size of the register block and the calculation type of the target reduction calculation, the pooling instructions carrying a pooling type matched with the calculation type and pooling frame size information, the input registers of the first pooling instruction being the first registers, the input registers of the i-th pooling instruction being the output registers of the (i-1)-th pooling instruction, i being an integer greater than 1 and less than or equal to j, and j being an integer greater than 1; and sequentially executing the j pooling instructions, each thread storing a calculation result of the target reduction calculation in the output registers of the j-th pooling instruction. The method can improve the efficiency of reduction calculation.

The invention relates to the technical field of automatic driving, in particular to an automatic driving task scheduling method, system and equipment based on dynamic priority, and the method comprises the steps: dividing an automatic driving task into a sensing task and a reasoning task based on the calculation type, execution frequency and period of the automatic driving task, constructing a sensing task pool and a reasoning task pool based on the execution information; calculating the scheduling priority of the automatic driving task based on a preset dynamic priority calculation formula; and executing the automatic driving task based on the scheduling priority. In this way, for various heterogeneous computing tasks facing the automatic driving task, the resource utilization rate can be effectively improved, and task blocking delay is avoided.

The invention discloses a data skew optimization method based on Spark, belongs to the field of big data and databases, and aims to recognize a skew partition in advance on a Map task side, process skew data according to user requirements, and avoid the situation that the skew data is shuffled to a Reduce end, time is long when shuffle data is pulled by a skew Reduce, a long-tail task occurs, the operation efficiency of a whole analysis task is affected, and the operation efficiency of the whole analysis task is improved. And the data skew optimization mode is not only suitable for a two-table Join calculation type, but also suitable for all calculation tasks including a Shuffle process, and the calculation performance of the Shuffle type Spark task can be improved.

The invention provides a multi-core-switching fast number-theory transformation system and a task execution method. The system comprises a task identification module, a scheduling module, a control module and a multi-core-particle operation module, wherein the multi-core-particle operation module comprises core particles which are respectively arranged for a plurality of privacy calculation types; wherein the task identification module is used for dynamically identifying a privacy calculation type to which a fast number theory transformation operation task belongs; the scheduling module is used for determining the priority of the operation task according to the privacy calculation type to which the operation task belongs, and scheduling the operation task to the control module according to the priority; the control module is used for distributing the operation task to the core particle of the corresponding type according to the privacy calculation type to which the scheduled operation task belongs so as to serve as the operation task of the core particle; and the multi-core-particle operation module is used for controlling all types of core particles to execute respective operation tasks in parallel so as to realize parallel execution of the operation tasks of various privacy calculation types.

The invention provides a Sencil calculation compiling optimization method based on a data stream architecture, a Sencil program is written in a mode of adding a guidance statement in a C language, and the statement is used for defining a data dependency relationship between a Sencil calculation type and a time axis; the compiler analyzes the guidance statement, analyzes the data dependency relationship between the time axes, and determines the starting interval of each time axis and the data needing to flow; time axis operation is distributed to adjacent parallel computing nodes according to the relation between the number of times of time axis iteration and the number of parallel data flow computing nodes, and continuous time axis iteration is distributed to the adjacent data flow computing nodes; a data flow instruction is generated for operation in each time axis, and asynchronous communication and parallel execution between nodes are controlled through a data flow diagram. The invention further provides corresponding electronic equipment. Therefore, the parallel execution between the time shafts is realized while the flexibility of Sencil programming is ensured, the memory access overhead and the synchronization overhead of a plurality of computing nodes are reduced, and the program performance is improved.

The technology disclosed relates to accessing external data in spreadsheet cells and includes spreadsheet cells that can use formulaically defined external data, allowing users to utilize many cells as if they were one cell and to simplify or expand the type of calculations possible within a cell. The disclosed technology further includes a spreadsheet application that can perform looped calculations within the spreadsheet cells without the need to use an embedded programming language. Additionally the disclosed spreadsheet application can use named variables and formulaic cell designators for cell operations in which formulaically defined non-spreadsheet cell data variables and their values can be exposed and multiple values can exist in a cell, and the user can step through and see those different values.