314 results about "Simics" patented technology

The invention relates to the technical field of artificial intelligence chips, and discloses a model performance estimation method and device and computer equipment, and the method comprises the steps: determining model configuration data and candidate distributed strategies of a target model; converting the original calculation graph corresponding to the single-card deployment state based on the model configuration data and the strategy configuration data of the candidate distributed strategies to obtain a distributed overhead calculation graph corresponding to the multi-card deployment state; and performing performance estimation on the candidate distributed strategy according to the basic overhead and the additional overhead in the distributed overhead calculation graph to obtain strategy performance data of the target model under the candidate distributed strategy, thereby realizing conversion of a single-card model into a multi-card model. And based on the multi-card model, simulation calculation of the multi-card interconnection mode is realized on the premise of limited hardware resources, so that the influence of a communication operator and a topological structure corresponding to the multi-card interconnection mode in the overall operation of the model is reflected, and the upper limit of the model performance can be accurately evaluated in a simulator verification stage before silicon is applied.

A platform for multi-stage simulations in a multi-agent simulator computing system utilizes context sharing across simulation sessions. The platform generates agents based on input traits, executes simulation sessions to produce outputs, and persists outputs and agent configuration data (e.g., metadata associated with simulation sessions). A graphical user interface displays simulation outputs. In response to user interaction with a particular output item (e.g., a user follow-up query or inquiry into simulation traceability), the platform identifies the associated agent using persisted configuration data and performs additional operations, which can include generation and execution of additional queries for follow-up simulations.

A computing platform can generate a virtual world and a set of virtual agents having agent traits and interaction rules. For example, by automatically analyzing experimenter queries, the platform can bind the agents to machine learning models that perform tasks responsive to the questions. The platform can generate additional hypotheticals to enable chains of simulations. The platform can execute a first simulation session by causing the set of agents to generate a first output set. Using an additional data source to generate new world characteristics, such as environmental and / or temporal conditions, the platform can generate and apply agent evolution logic for subsequent simulations, such as by performing mutation of agent traits, selection of agents, crossover of agent characteristics, and / or deletion of agents that do not meet a fitness threshold. The platform can persist agent states and outputs to generate user-interactive visualizations, aggregations, and training data sets for training agent models.

The invention discloses a reinforcement learning calculation simulation method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence computing, and the method comprises the steps: inputting the determined current model parameter configuration, current hardware configuration and current working load into a target simulation system to obtain a plurality of parallel grouping combinations, determining a target simulation system according to the current hardware configuration, determining an effective parallel packet combination from the plurality of parallel packet combinations based on a preset Monte Carlo method, inputting the effective parallel packet combination into a simulator of a preset neural network model, and performing delay time calculation according to the effective parallel packet combination through the simulator to obtain a delay time sequence; and the combination corresponding to the shortest delay time is used as a target parallel grouping combination, so that the technical problems of mismatching of simulation scenes, insufficient precision and lack of effective support for heterogeneous clusters are solved, reliable performance prediction and optimal parallel strategy suggestions are provided through high-precision performance modeling and automatic exploration, and the method is suitable for large-scale popularization and application. Therefore, the resource consumption of large-scale GRPO training is reduced.

The invention provides an intelligent teaching-assistant system base LLM training method for a drilling simulator, and belongs to the technical field of petroleum drilling large language model training, and the method comprises the steps: obtaining the simulation data of the drilling simulator based on an intelligent teaching-assistant system base large language model, and carrying out the field self-adaptive pre-training; performing fine adjustment on the original weight by utilizing low-rank self-adaption, and performing operation steps and fault diagnosis generation; the method comprises the following steps: constructing an enterprise private knowledge base, training a large language model by utilizing retrieval enhancement generation, and obtaining a trained verification header through explicit supervision; a direct preference optimization loss function is defined, a direct preference optimization loss function of retrieval perception is obtained in combination with the verification head, the large language model is optimized, and large language model training is completed; according to the invention, an external professional knowledge base can be fused, an equipment operation mechanism can be understood, an intelligent assistant architecture with teaching guidance and error diagnosis capabilities is provided, and the intelligent level of the drilling simulator is improved.

The invention relates to a software and hardware co-simulation chip verification method, system and device and a storage medium, and relates to the field of software and hardware co-simulation. The method is based on a hyperSemu system comprising an hsComple and an hsRun and an FPGA (Field Programmable Gate Array) comprising a DUT (Device Under Test) and a Transactor. The method comprises the following steps of: writing an RTL (Real Time Language) design code of a chip; compiling the RTL design code by utilizing hsCompile to obtain a DB file; downloading the DB file to an FPGA (Field Programmable Gate Array) through hsRun so as to carry out hardware simulation; according to the DUT and the Transactor, a Hybrid server program and a Hybrid client program are written, and the Hybrid client program comprises a simulator program and a Linux system; and performing software simulation in the Linux system according to the DUT and the simulator program. The technical effect of the invention is that the efficiency and speed of chip simulation verification are improved.

The invention is suitable for the technical field of artificial intelligence, and provides a data processing method and device for a big language model based on federal learning, and the method comprises the steps: decomposing the big language model, and obtaining an adapter and a simulator; performing layer compression processing on the simulator to obtain a compression simulator, and deploying the adapter and the compression simulator to a plurality of clients; obtaining adapter parameters uploaded by each client after training the adapter based on a local data set; performing global aggregation on universal adapter parameters in the adapter parameters, and performing grouping aggregation on personalized adapter parameters in the adapter parameters to obtain aggregated adapter parameters; and outputting the aggregated adapter parameters to the client. According to the scheme, privacy protection can be realized, and individual user preferences are reserved.

In various examples, synthetic dataset regeneration for AI systems and applications is described herein. For instance, systems and methods described herein may use a simulator to generate a synthetic dataset along with data (referred to, in some examples, as “log data”) representing information associated with the generation of the synthetic dataset by the simulator. For instance, the log data may represent at least parameters used to generate synthetic dataset, values for the parameters, assets associated with the parameters, and / or values representing results associated with the synthetic dataset. The systems and methods may then use the log data to recreate, modify, and / or enhance the synthetic dataset. For example, the synthetic dataset may be recreated by providing at least the log data as input to the simulator such that the simulator regenerates the dataset using the same parameters, values, and / or assets.

The invention provides an information synchronization method, system and device for an embedded training simulator and a medium. The information synchronization method comprises the steps that task event information in the embedded training simulator is obtained; performing task classification on each piece of task event information to obtain each piece of task event information with attribute tags; according to the attribute tag of each task event information, performing task priority classification on each task event information by using an improved multi-factor priority scoring algorithm to obtain a task priority queue; according to the task priority queuing queue, generating a to-be-pushed data packet, and performing information synchronization on the to-be-pushed data packet; according to the invention, by introducing a task priority-based scheduling mechanism, the pushing sequence and the synchronization strategy of the task information are dynamically optimized, so that the scheduling rhythms and the transmission paths of the tasks with different priorities are intelligently distributed; and the dynamic adaptive capacity and the efficient task delivery capacity of the embedded training simulation in the training process can be improved.

In one embodiment, a method may receive a request to upgrade software for a switch. The method may use an application-specific integrated circuit (ASIC) simulator to generate a digital twin to store a first image and a first configuration of the switch. The method may use the digital twin to generate a second image and a second configuration by replaying the first configuration on the first image. The method may communicate the second image and the second configuration from the digital twin to an ASIC memory of an ASIC associated with the switch by applying batch direct memory access (DMA).

Coaching simulator systems and methods, and non-transitory computer readable media, include receiving an interaction between a customer and an agent; scoring the interaction using an evaluation form; identifying a recurring improvement area for the agent based on the scored interaction and past scored interactions; creating a prompt for a large language model (LLM) by populating a prompt template; providing a framework to invoke the LLM using the created prompt, a model and a plurality of hyperparameters; starting a first coaching simulation scenario by invoking the LLM to present a first question to the agent; receiving a first answer to the first question from the agent; querying the LLM to analyze the first answer to the first question; and querying the LLM to provide real-time feedback and a score for the agent based on the analyzed first answer to the first question.

A non-transitory computer readable medium is provided comprising instructions that when executed on a processor load a software program into a software debugger for execution on an emulated processor representing a processor portion of a system on chip (SoC), load a hardware design into a hardware simulator representing a programmable gate array portion of the SoC, coordinate execution of software debugger and hardware simulator to simulate operation of the SoC, communicate data between the software debugger and the hardware simulator, and display computed results and current values.

Virtual platform system for use in a cloud-based system, comprising: a virtual platform simulator configured to represent in software a physical remote client device and to have this representation interact with a virtual platform application; a process virtual machine configured to execute program instructions of the virtual platform application and comprising a code morpher component for transforming the program instructions of the virtual platform application into native program instructions for execution on a physical host machine of the cloud-based system; and interception components for capturing transactions from the virtual platform simulator and the process virtual machine. The transactions are related to the execution of the program instructions of the virtual platform application. The virtual platform system is configured to compare the captured transactions with pre-stored transactions, preferably stored in a blockchain, to obtain a comparison result, and to allow the execution of the program instructions depending on the comparison result.

Apparatus and method achieve topology optimization with bidirectional mesh adaptation. A mesh engine generates a mesh for a geometry of a computer aided design model of a design domain. A multi-physics simulator derives of physical field variables on the mesh based on material properties and boundary conditions of the design domain. An adjoint sensitivity is determined based on a given cost function and sensitivity formulation to drive a design variable lower or higher, the design variable defining a density of the design domain. An optimizer determines an optimization yielding a new set of design variables based on the adjoint sensitivity. A bidirectional mesh adaptation is performed on regions of the mesh by coarsening or refining the mesh element size. The multi-physics simulation, optimization and mesh adaptation are iteratively performed until optimized convergence criteria are met.

A platform for adaptive multi-agent simulation in a virtual world instantiates a set of agents with input traits and executes a simulation session, generating an output set. Upon detecting a change event in the virtual world, a trained model recommends an evolution operation, which is applied to the set of agents to generate an evolved set. The evolution operation includes mutation, selection, crossover, deletion of agents, or a combination thereof. The platform persists at least a portion of the initial output set and executes a second simulation operation using the evolved agents, generating a new output set and thereby enabling analysis and comparison of simulation results. The disclosed adaptive simulation approach with persisted context enables realistic and dynamic modeling of complex systems.

The invention relates to a reconfigurable equipment simulation system based on software radio, and the system achieves the high-integration, user-friendly and efficient-management reconfigurable equipment simulation system through the modularization and seamless integration of a radio waveform design function, an equipment simulation user operation interface design, a business logic function design and a project management function. Therefore, even if a user does not have a deep programming capability, the user can quickly construct, test, manage and deploy the equipment simulator with complete functions. The system is rich in waveform component and UI component library, customizable in function and good in flexibility, software radio waveform design and equipment simulation are innovatively and seamlessly integrated, automatic non-inductive or manual upgrading can be achieved, the universality is good, various equipment simulators can be designed, the designed equipment simulators have open function expansion, and the system is suitable for popularization and application. And a complete project management process is provided.

The invention belongs to the technical field of computers, and discloses a simulator starting acceleration method and device, equipment and a storage medium, and the method comprises the following steps: obtaining a pre-read block set; performing priority ranking on the data blocks according to the access frequency labels to obtain a pre-read block sequence; extracting a preset number of high-priority data blocks from the pre-read block sequence to generate a target pre-read block subset; executing a pre-reading operation on the target pre-reading block subset to obtain pre-loaded data; storing the preloaded data in a cache, and generating a preloaded cache; in response to a simulator starting instruction, reading the preloading cache to obtain starting data; initializing the simulator according to the starting data to obtain an initialized simulator environment; and executing a simulator starting process by adopting the initialized simulator environment. According to the invention, the starting speed of the simulator can be improved under the condition that the personalized requirement of a user on simulation precision is met.

The invention discloses a controller simulation system construction method and device, equipment and a medium, relates to the technical field of simulation, is applied to a preset transaction-level component, and comprises the following steps: connecting a simulation model of a controller and equipment based on a nonvolatile memory host controller interface specification, and connecting a preset virtual operating system simulator through an inter-process communication component; converting a first transaction level modeling message sent by the preset virtual operating system simulator into a first transaction layer data packet message, and calling the simulation model to process the first transaction layer data packet message; and converting a second transaction layer data packet message sent by the simulation model into a second transaction level modeling message, and sending the second transaction level modeling message to the preset virtual operating system simulator, so that the preset virtual operating system simulator processes the second transaction level modeling message, and realizing connection communication between the preset virtual operating system simulator and the simulation model so as to construct the simulation system. And the construction of the controller simulation model is realized.

A method can include receiving property data for a simulation model; analyzing the property data with respect to geometry of the simulation model to select a matrix preconditioner scheme using a machine model; and executing a computational simulator that implements parallel processing based on application of the matrix preconditioner scheme to a matrix representing the simulation model to generate simulation results based on the property data.

The invention provides a steer-by-wire fault degradation processing method, device and equipment and a medium, and belongs to the technical field of intelligent driving fault processing, and the method comprises the steps: obtaining the fault information of each redundant subsystem in system components in real time, and determining the current component state level of each system component; executing corresponding fault processing measures according to the current component state level; wherein the system assembly comprises a lower steering engine and a road feeling simulator, and the fault information comprises no fault, failure fault and degradation fault. According to the technical scheme provided by the embodiment of the invention, the corresponding processing operation can be executed according to the current component state level of each system component, so that the degradation fault and the failure fault of the redundant drive-by-wire system can be accurately processed.

Systems and methods for using distributed quantum-based computing simulators are disclosed. In one embodiment, a method may include: (1) receiving, at a driver node and from a service, a set of operations and a location for each operation compiled from a set of quantum computing instructions provided by a client device; (2) generating, by the driver node, a declarative instantiation plan for the set of operations identifying a plurality of worker nodes, each worker node corresponding to one of the locations; (3) instantiating, by the driver node, the declarative instantiation plan; (4) issuing, by the driver node, the operations to the worker nodes based on the locations for each operation; (5) receiving, by the driver node, results from each worker node; (6) aggregating, by the driver node, the results; and (7) returning, by the driver node, the aggregated results to the client device via the service.

The invention discloses a method for realizing accurate synchronization of a time sequence in a simulator based on a shared memory, which relates to the technical field of simulator development and cross-process communication, and comprises the following steps: constructing a standardized three-layer layout comprising a head control region, an annular data region and a compact storage unit, the annular data area circularly accesses, and the compact storage unit binds data and a time sequence; cross-platform zero-leakage resource management is realized through a global singleton handle manager, and interface multiplexing is provided or a shared memory is created and mapped; the sending end encodes data, binds a time sequence and atomically updates a write pointer, and the receiving end reads the data, calibrates the time sequence and atomically updates a read pointer; and executing time sequence precision, transmission delay, throughput and stability verification. According to the method, the lock competition overhead is eliminated, the cross-process data transmission efficiency is greatly improved, the time sequence synchronization accuracy is guaranteed, and the hardware bus refinement requirement is met.

The invention discloses a water engineering scheduling intelligent parallel caching system for intelligent water conservancy and an optimization method. The system comprises a constraint-driven asynchronous hierarchical caching module, a topology-sensitive cumulative hash module and a polymorphic hierarchical storage module. According to the system, a three-level framework of thread local buffering, global batch processing and an generational sliding window is adopted, and boundary constraint pre-verification is executed on a scheduling scheme; decision vectors are rearranged according to the upstream and downstream topological relation of the water engineering, an upstream engineering decision preferentially participates in Hash calculation and is endowed with a higher weight, and the weight is decreased progressively according to an exponential function; target value arrays are dynamically distributed, and volume class, flow class and time sequence class constraint violation degrees are stored in a layered mode; according to the method, through a topology-aware Hash mechanism and a self-adaptive caching strategy, the recognition precision and the caching hit rate of similar schemes are remarkably improved, repeated calling of a hydraulic simulator is effectively reduced, and the calculation efficiency of water engineering scheduling optimization is improved.

The invention discloses a virtual-real combined sky-ground multi-domain heterogeneous network cooperative computing simulation system and a virtual-real combined sky-ground multi-domain heterogeneous network cooperative computing simulation method. The system comprises a heterogeneous computing power prototype subsystem, a virtual simulation subsystem, a satellite-borne general computing terminal, a programmable network simulator, a heterogeneous resource management subsystem and a simulation verification system interface. Real hardware computing power characteristics are introduced through a physical board card, large-scale expansion is realized through virtual nodes, and authenticity and large-scale performance of simulation are considered; link parameters are generated according to a high-precision orbit dynamics model, and the fidelity of sky-ground network simulation is greatly improved; based on a mixed container arrangement technology, unified management and intelligent scheduling of sky, air and ground heterogeneous resources are realized, and a powerful platform is provided for verifying an advanced cross-domain collaborative algorithm; one set of system can support various simulation verification requirements of networking routing, task unloading, distributed cooperative computing, constellation cluster management and control and the like, and the research and development cost and complexity are reduced.

The invention relates to the technical field of computers, in particular to a TCP simulation connection method, device and equipment. The invention discloses a TCP (Transmission Control Protocol) simulation connection method, which is applied to a server simulated by a network simulator, and comprises the following steps of: creating a semi-connection table data structure, and integrating a semi-connection table to the network simulator; and when a TCP connection request is received, establishing a connection with the client based on the semi-connection table simulation. According to the embodiment of the invention, the semi-connection table change in the TCP connection establishment process can be simulated more accurately, effective simulation of DDos attack and protection is realized on the basis of not influencing the original model, and deeper research on the DDos attack is facilitated. Wherein the semi-connection table is realized by utilizing the structure of the chained hash table, so that the searching efficiency can be obviously improved, the semi-connection information can still be quickly searched and updated under the condition of large-scale connection requests, and the occupation of a memory is effectively reduced.

The invention relates to the technical field of industrial automation control, and provides a method and system for achieving online simulation of an HMI simulator, and the method comprises the steps: monitoring the starting and offline simulation process of an original HMI programming software simulator, and confirming that the original HMI programming software simulator completes the generation of a configuration file; receiving a mode switching instruction of a user through the mode switching interface; in response to the mode switching instruction, terminating the current simulator process; modifying a configuration file generated by the simulator, modifying an operation mode parameter in the configuration file from a first value representing offline simulation to a second value representing online simulation, and dynamically configuring a communication port parameter; the verification information of the configuration file is updated to ensure the legality of the file; and restarting the simulator, and loading the modified configuration file by the simulator so as to establish communication connection with an external PLC (Programmable Logic Controller) or instrument and enter an online simulation mode. On the premise of not depending on entity hardware, online communication and real-time joint debugging of the HMI simulator and the external equipment can be realized.

The invention relates to a joint debugging method and device for JTAG and OpenOCD based on a UVM platform. The method comprises the following steps: importing a JTAG DPI C function into a UVM verification platform; the JTAG DPI C function is used for controlling the OpenOCD to interact with a JTAG interface of the UVM verification platform; instantiating a JTAG DPI module on the UVM verification platform, and connecting a JTAG interface with a device to be tested; the method comprises the following steps: according to an OpenOCD configuration file, configuring the OpenOCD into a remote-bitbank mode; the OpenOCD configuration file comprises a remote host address, a remote host port number and a remote-bitbank interface; a JTAG time sequence packet received by the JTAG DPI module is converted into simulation test excitation interacting with a compiling simulator of the UVM verification platform through a TCP Socket interface and a direct programming interface DPI; and starting the OpenOCD, setting a preset port of the OpenOCD as a telnet connection port, and issuing a debugging command to the to-be-tested device through the preset port.

Provided in the embodiments of the present disclosure are a processing method, platform, and apparatus based on a chip simulator platform. The chip simulator platform is deployed with a first test end and a second test end, and the first test end and the second test end are respectively bound with different CPU resources in the chip simulator platform. The method comprises: performing received data packet redirection configuration on a local virtual network interface card of the chip simulator platform, the data packet redirection configuration being used for sending a specified data packet to a designated CPU resource; and when a soft interrupt is triggered in response to a network request issued by the first test end, according to an instruction of the received data packet redirection configuration and by means of the local virtual network interface card, sending a data packet corresponding to the soft interrupt to a CPU resource bound to the second test end for processing. According to the embodiments of the present disclosure, network environment simulation in a chip simulator environment is achieved by utilizing received data packet redirection technology.

According to the game copy automatic test case generation method and the terminal, a copy digital twinning scene is constructed through an environment simulator, an intelligent agent is generated, and the intelligent agent makes a decision by using a dual-network mechanism of a layered DQN controller; training agents in a grading manner by utilizing dynamic course learning, gradually improving difficulty according to copy complexity and migrating low-level training weights, and guiding the agents to explore in combination with a multi-dimensional reward function; generating a test case according to the agent exploration trajectory; according to the method, the digital twinning scene is constructed through the environment simulator, and the intelligent agent autonomously explores and covers a hidden path and a dynamic mechanism based on layered DQN and dynamic course learning, so that the test coverage rate can be effectively improved, the effectiveness of test case generation is ensured, and the dynamic course learning can effectively improve the training efficiency and quickly adapt to copy updating; the defects of low random test efficiency and poor static algorithm adaptability are overcome, and high-coverage, efficient and self-adaptive test case generation is realized.