53 results about "Check point" patented technology

The embodiment of the invention provides a distributed training system and a distributed training method. The distributed training system and the distributed training method are used for improving the training efficiency of model distributed training. Training nodes in the distributed training system are used for storing check points in video memories of GPUs of the training nodes and sending the check points to memories of CPUs of the training nodes; the training node is also used for sending the check points in the memory of the CPU to the storage system through asynchronous operation; the training node is also used for sending abnormal information to the management node under the condition that the node state information of the training node is abnormal information; the management node is also used for determining whether the training node is a fault node based on the abnormal information, and isolating the fault node under the condition that the training node is the fault node; and the management node is also used for loading a target check point corresponding to the fault node from the storage system to other training nodes under the condition that the training node is the fault node, so that other training nodes complete a model training task of the fault node based on the target check point.

A check point remote backup method based on large model parallel strategy perception comprises the following steps: S1, constructing a Checkpoint backup scheme: S11, constructing different cross-node parameter backup mapping relationships according to different parallel modes; s12, constructing a model parameter fragment distribution scheme according to the parameter load capacity of each card and the redundant copy number; s13, grouping the training nodes according to the number of backup copies set by a user, and generating a plurality of full mutual backup groups with equal sizes; the training nodes in the full mutual backup group are mutually backed up; s2, managing memory allocation in a Checkpoint backup process on the basis of a memory multiplexing mechanism; scheduling of CPU resources in the Checkpoint data transmission process is managed according to the asynchronous transmission process; s3, realizing punctual writing of the Checkpoint through a round and time threshold combined triggering method; and S4, controlling the startup and scheduling of the Checkpoint backup. According to the method, when the node breaks down, the system can quickly recover the model state from other nodes according to a set backup strategy, and the continuity of a training task and the fault-tolerant capability of the system are ensured.

The invention relates to a GPU (Graphics Processing Unit) check point storage method in large model distributed training, which comprises the following steps of: 1, loading check point configuration information when training is started; 2, monitoring a back propagation completion signal of each layer in the training process, and immediately triggering check point fragment storage operation of a certain layer after parameter updating of the layer is completed; 3, the model state of the layer is asynchronously copied to a CPU memory from a GPU memory, and consistency verification is carried out; 4, asynchronously storing the check point fragments from the CPU memory into a persistent storage; 5, when training needs to be recovered, the check point file is loaded from the persistent storage, integrity verification is carried out, all layers of fragmented data are recombined into a complete model state, and training is recovered. And the synchronous blocking and I / O bottleneck of the check points in the training process are reduced, so that the training efficiency is improved, and the fault recovery time is shortened.

The invention discloses a multi-device collaborative integrated kitchen management system, and relates to the technical field of intelligent kitchen control, and the system comprises the steps: analyzing an order or menu request into a task graph, building dependence, and adding a capability demand, resource mutual exclusion, a quality window, a risk level and migration window, and a check point strategy label for a task node; the edge arrangement gateway collects the equipment state, the resource occupation and the network health degree, and reschedules and generates a main plan and a shadow plan under the constraint of a rolling window and a freezing window; a main plan is converted into an intention type transaction to be issued, idempotent processing is carried out according to a transaction identifier, feeding, discharging and valve opening are carried out, token reservation-consumption is carried out, and account checking and verification are carried out; generating a process check point according to a check point strategy, and executing thermal migration, compensation or security degradation and account checking synchronization according to a migration window and a shadow plan when the process check point is abnormal; repeated actions and state drifting caused by re-delivery are reduced, and the stability of continuous meal delivery is guaranteed.

One or more implementations of this specification provide model training and checkpoint file storage systems and methods. In an implementation, a method includes executing, by a model training module of a storage system, a training task of an artificial intelligence model, during execution of the training task, suspending, by the model training module, the training task if a first checkpoint file is generated and sending a request to a checkpoint file processing module of the storage system to cache the first checkpoint file, locally caching, by the checkpoint file processing module, the first checkpoint file based on the request, and concurrently performing, by the check file processing module, a notification operation and a storage operation.

The invention relates to a large model training check point storage method and device and a storage medium, and the method comprises the steps: when a main training thread executes an iterative training task, through an independently-running asynchronous thread, executing a check point storage operation on the main training thread before the main training thread executes the check point storage operation; a memory space matched with the check point data structure is applied and organized in a CPU memory in advance; when the check point needs to be stored, the main training thread can directly write the latest check point data into the pre-allocated target memory in an overwriting manner, so that time-consuming memory application and organization operation are stripped from a key path of the main thread. Through the method and the device, the influence of check point storage on the training task is reduced, and the utilization rate of the GPU in the training process is effectively improved.

The invention discloses an assembly line check point implementation and fault recovery method and system based on a distributed memory, and belongs to the technical field of cross-center assembly lines. The method comprises the following steps: dividing a cross-data-center assembly line into a plurality of sub-assembly lines, and executing the sub-assembly lines on corresponding data centers in a cluster respectively; when the execution of the sub-assembly line is finished, acquiring Arrow format data of the current check point; storing the Arrow format data of the current check point in a distributed memory system or a disk storage system of a cluster; and when a system fault occurs or the execution of the cross-data center assembly line task fails, fault recovery is performed based on the Arrow format data of each check point. According to the method, the interruption and data loss risks of assembly line tasks can be reduced, and the reliability and fault tolerance of a large-scale data processing assembly line are improved.

The invention relates to the technical field of artificial intelligence, and particularly provides a check point storage method and device of an artificial intelligence model, a medium and a product. The method comprises the following steps: acquiring storage equipment information and PCIe topological information, and constructing a transmission topological graph based on the storage equipment information and the PCIe topological information; based on the transmission topological graph, determining a target parallel transmission path from the GPU to the storage device; dividing the global check point data into a plurality of check point fragments based on the bandwidth capability of the target parallel transmission path; transmitting the plurality of check point fragments from the GPU to corresponding storage equipment in parallel through a plurality of independent transmission streams; and executing a two-stage persistence operation, and transmitting and storing the check points in the storage device to a remote storage system in a fragmented manner. According to the method provided by the invention, a data transmission path can be systematically optimized, heterogeneous storage resources are cooperatively utilized, and high reliability and rapid recovery capability are considered, so that the training efficiency of a large-scale artificial intelligence model is improved.

The embodiment of the invention provides a training cluster check point storage method, a training cluster check point recovery method and electronic equipment. The training cluster check point storage method comprises the steps that distributed cluster node memories cooperatively store check points, and the memories are used for storing check point data of each round of training. According to the method provided by the embodiment of the invention, cluster memory collaborative management is adopted, the node memory stores the whole check point, and the storage frequency of the check point is improved; in addition, a cluster memory control manages multi-node check points and supports grouped redundant backup; and moreover, the check points are directly stored in the memory, so that the time delay of storing the check points is greatly reduced.

The invention relates to the technical field of artificial intelligence, and discloses a model check point file management system which comprises a data downloader, a metadata storage system, a local storage system and a remote storage system. The data downloader is used for receiving a check point file acquisition request and sending a metadata acquisition request for acquiring a storage address of a first check point file to the metadata storage system; the metadata storage system is used for querying first metadata corresponding to the first check point file according to the metadata acquisition request and sending a first storage address to the data downloader; the data downloader is used for acquiring the first check point file from the remote storage system according to the first storage address and storing the first check point file to the local storage system; the local storage system is used for returning the first check point file to the first training task. According to the method, massive check point files can be stored, the storage performance is optimized, and reliable operation of model training tasks can be guaranteed.

A page distortion correction method and system, an electronic device and a computer readable medium. The page distortion correction method comprises: determining a target text line to be corrected, and selecting a plurality of check points in the target text line, the plurality of check points satisfying that the connecting line of the plurality of check points is coincident with or parallel to a correction reference line when the page is not distorted; comparing the positions of the plurality of check points with the correction reference line, and calculating the offset amount of the check points to be corrected; and correcting each character of the target text line according to the calculated offset amount. The method is simple and efficient, has good restoration, strong adaptability, and the correction result is more stable.

The invention discloses a program execution management method and device, a vehicle and a medium. The method comprises the steps that a program instruction of a vehicle electronic control unit is received; wherein the program instruction is generated when a check point is triggered based on a program execution sequence running in the electronic control unit; analyzing the program instruction to obtain address information of the check point; matching the address information with pre-stored address information to obtain a first matching result; wherein the pre-stored address information is obtained from the cache table; if the first matching result is that the address information is not matched, the address information is locked in a door lock trigger, and fault reporting is carried out through the door lock trigger. According to the technical scheme, the program execution sequence is managed in the system-level chip according to the matching operation of the pre-stored address information in the cache table, an extra CPU period can be avoided or minimized, extra cost and performance overhead are reduced, and safety of vehicle functions is guaranteed.

The invention relates to a method for accelerating model training recovery, electronic equipment and a storage medium. The method comprises the steps of executing a first task for constructing a training component based on an instruction of recovery model training, and independently executing a second task through a concurrent execution unit corresponding to a main execution unit; wherein the second task is used for loading the check point file corresponding to the training component to the memory from the external storage system; wherein the training component comprises a model object and an optimizer object, the check point file comprises state data, stored in historical model training, of the training component, and the first task and the second task are at least partially overlapped in execution time; and in response to an event of completing the first task and the second task, loading the state data in the memory into the corresponding training component to complete state recovery of the training component. According to the method, the parallel support of each task in the model training recovery process can be realized, and the time consumption of model training recovery is effectively reduced.

The invention provides a safety function block active defense method and system for a safety instrument system. The method comprises the following steps: before executing a core algorithm, performing pointer security check and numerical field check on input data of a security function block; if the check is passed, entering a pre-operation stage, and monitoring an operation risk in real time through a preset check point by utilizing a reverse analysis pre-operation algorithm or a soft floating point pre-operation algorithm on the premise of not executing an actual instruction which possibly causes hardware exception; and executing a deterministic output strategy according to a pre-operation result, and outputting a unified hierarchical state code (ERR) through a special state pin. The method has the advantages of endogenous safety, fault behavior determination, high diagnosis precision, high configuration efficiency and the like, controller shutdown caused by data exception can be effectively avoided, and the robustness of an industrial control system is improved.

The invention relates to a simulation analysis method and device for program fragments. Comprises: constructing an original program file of a target program; running a target program fragment in the original program file through a simulator, capturing a corresponding running state, and generating check point data; merging the check point data into the original program file to obtain a to-be-tested program file; and according to the check point data in the to-be-tested program file, recovering the running state of the target program fragment in the to-be-tested program file in the test environment, and obtaining the performance data of the target program fragment during running of the target program. By optimizing storage and recovery processes of check points, the number of times of operation of a specified program on a simulator is reduced, tracking of a CPU register, codes and data is avoided, and the performance is improved; meanwhile, the construction method of the test instruction slicing system is improved, so that the generated program slices can run in target environments such as a simulator, a simulation environment and an FPGA without depending on a specific test system, and portability and test efficiency are improved.

The invention relates to processing of containerized environments. The present disclosure relates to a computer-implemented method of processing a containerized environment related to a service requested by a client, comprising the steps of: (a) monitoring the time taken by a container to initialize and / or the number of requests for a service received by the container from the client; (b) determining a container selected from among the containers based on the monitoring; (c) performing checkpoint setting on the selected containers and storing the checkpoint of each selected container in a container checkpoint cache; and (d) when the client requests the service, reading the corresponding check point in the container check point cache and recovering the corresponding selected container from the stored check point so as to serve the service.

A payment management system including a payment management unit that initiates a transaction, an operation unit that manages the issuance of at least one certificate, a governance unit that operates based on at least one parameter defined in the at least one certificate; at least one validation unit that receives the at least one certificate and validates portions of the transaction; and a payment unit that issues payment based on the terms of the at least one certificate, where the operation unit crates a governance protocol for each transaction with the governance protocol including at least one epoch and at least one checkpoint.

The invention discloses a storage method of a model check point, which is applied to persistent storage of the model check point in the field of artificial intelligence (AI). According to the storage method of the model check points, the operation of updating model parameters in the model training process is deployed on a central processing unit (CPU) to be executed, and the updated model parameters can be reserved after the CPU executes the operation of updating the model parameters. Thus, during the period that the accelerator continues to execute model training based on the updated model parameters, the CPU can store the reserved model parameters in the target storage medium at the same time, persistent storage of the model parameters can be achieved without interrupting the training process, and normal training of the AI model is prevented from being affected.

The present invention relates to a method for setting collision information for simulating robot motion and an apparatus for performing the same, the method including the steps of: obtaining robot installation information about an operation space of a robot, dangerous region information, and body part information in which a collision can occur in each dangerous region; setting a check point for judging a collision danger with respect to the robot; and calculating coordinate information and shape information of the check point based on at least a part of the obtained information and the set check point.

The invention relates to the technical field of data processing, in particular to an electric energy meter AI code review method and system based on check point cues. The method is applied to a system architecture comprising a client and an AI server, and comprises the following steps: inputting an embedded engineering code and a cue word for examination through the client; the client carries out grammatical analysis on the embedded code to form an analysis block; the client combines the analysis blocks with the corresponding cue words and matches standardized information in combination with an external knowledge base to form an examination unit; the AI server receives the review unit, dynamically identifies the problems of array crossing, excessive memory applications and variable defense, and outputs a structured review result; and the client summarizes all review results, performs classified statistics according to defect types, and generates visual reports and logs. According to the invention, the detection accuracy of specific scene defects is obviously improved; and the time cost of diamagical examination and the risk of artificial omission are greatly reduced.

The invention discloses an environment security check method and device for task automatic verification, and a storage medium, and the method comprises the steps: screening all security check personnel according to the check point information of a check point, and determining a target security check personnel in all security check personnel; generating a security check task according to the check frequency and position information in the check point information and the shift information and personnel information of the target security inspector, and sending the security check task to a target security check terminal of the target security inspector; at any moment in the security check task execution process, automatically or responding to a control instruction to obtain a task execution image; and performing compliance examination on the task execution content in the task execution image, and giving an alarm if the task execution content does not meet the rule. According to the invention, high management and control of security check task execution are realized, and the efficiency of environmental security check is improved.

A memory system includes a memory device and a controller. The memory device includes a plurality of memory blocks. The controller recognizes a change in a pattern of a plurality of write data, delays a checkpoint operation associated with a write operation regarding the plurality of write data entries when operational data regarding the plurality of write data entries is within a range that is capable of being stored in a buffer, and performs the checkpoint operation when the operational data is beyond the range.

A processor of a game system acquires first positional information indicating a position of a mobile terminal that is acquired via a GPS receiver, determines whether the first positional information of the mobile terminal is contained in any of pieces of second positional information respectively corresponding to check points, and provides a reward as content of a game to a player corresponding to the mobile terminal every time the first positional information is contained in any of the pieces of second positional information. A memory stores evaluation corresponding information indicating a correlation between a combination of contents of rewards, and evaluation information including at least one of winning / losing, a ranking, and an earned point of the player in the game. The processor further determines the evaluation information of the player corresponding to the mobile terminal in the game based on the evaluation corresponding information according to the combination of the contents of provided rewards.

The invention relates to the technical field of cloud computing, in particular to a check point file synchronization method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a file list cached under a source directory; the check point files in the file list are distributed to all the sending processes through the main control process; sending a query request to a receiver server, and confirming the existence state and file information of the check point file on the receiver server according to feedback information returned by the receiver server; and sending the check point file to the receiving process through the sending process in response to the condition that the existence state is non-existence or the file information is represented to be required to be updated. By setting a plurality of groups of processes and transmitting a plurality of check point files in parallel, network bandwidth resources can be effectively utilized, and the consistency of the files on each server is ensured. By sending the query request in advance, whether the latest check point file exists on the receiver server or not can be checked, repeated transmission is avoided, and waste of bandwidth resources can be reduced.

The invention relates to a model training method and device, electronic equipment, a storage medium and a computer program product. The method comprises the steps that a check point module in a target model is determined; in the forward propagation stage, forward calculation is executed on the check point module, and only target parameters in the process that the check point module executes the forward calculation are stored in the video memory; and in the back propagation stage, if the last layer included in the check point module is the Flash Attention layer, the forward re-calculation of the Flash Attention layer is skipped, the gradient of the Flash Attention layer is determined according to a preset Flash Attention reverse algorithm, and the forward re-calculation is executed on other network layers in the check point module to determine the corresponding gradient. According to the embodiment of the invention, the redundant calculation overhead of the forward re-calculation of the Flash Attention layer can be saved, and the training efficiency is effectively improved.

The invention is suitable for the technical field of computers, and particularly relates to a general generation method and system for check points of a simulator and related equipment. The universal check point generation method of the simulator comprises the following steps: configuring simulation parameters of the simulator based on a simulation point acquisition module, and performing first simulation through the simulator to acquire an instruction of a to-be-acquired application program in an acquisition interval to obtain a basic block vector file; performing clustering analysis on the basic block vector file through a simulation point analysis tool to obtain a hotspot file and a weight file; and the simulator performs simulation for the second time according to the hotspot file and the weight file to obtain a plurality of check points. Compared with the prior art, the method has the advantages that single-core and multi-core check points can be quickly acquired, the simulation point starting instruction and the simulation point ending instruction are added into the simulator, and meanwhile, the acquisition interval of the application program can be determined by setting the simulation point starting instruction and the simulation point ending instruction, so that code segments needing to be acquired are accurately marked; and irrelevant code segments are filtered out.

The invention is suitable for the technical field of databases, and relates to a log analysis method and device, computer equipment and a computer readable medium. Wherein a logic log record corresponding to a transaction is obtained in response to analysis of the redo log, and whether the current time reaches a check point triggering period or not is recognized; if the current time reaches the check point triggering period, determining a target active transaction which is started earliest from the active transactions, and taking a redo log starting point corresponding to the target active transaction and a system logic clock corresponding to the logic log record as candidate check points for associative storage; responding to a received application system logic clock returned by the log application end, and determining a target candidate check point matched with the application system logic clock in the stored candidate check points; and configuring a redo log starting point in the target candidate check points as a formal check point of the redo log. According to the invention, the memory overhead required for promoting the check point can be reduced.

The invention provides a reverse time migration imaging method and device based on lossless compression and a medium, and belongs to the field of seismic exploration data processing. The method comprises the following steps: determining a check point configuration strategy, and generating a check point list; performing forward delay on the shot point wave field to obtain an inspection point wave field; compressing and storing the obtained check point wave field; the receiving point wave field is subjected to reverse continuation to reach a corresponding check point, and the shot point wave field of the check point is read; the shot point wave field of the read check point is decompressed, and shot point wave fields of two time slices of the check point are obtained through calculation; and calculating to obtain a reverse time migration imaging field. According to the method, the IO bandwidth is improved while the storage requirement of the hard disk is reduced, so that the calculation efficiency of overall reverse time migration is improved.

Computer systems for check point identification for a subject through in silico modeling are provided. One or more conditions and a plurality of contacts associated with the subject are identified in a data repository. A subset of decision rules is discovered from among a plurality of decision rules through alignment of a condition in the one or more conditions against the decision rules. The subset of decision rules models a response to the first condition at a first entity. A first decision rule in the subset of decision rules is activated using an evaluation module when a corresponding triggering condition for the decision rule arises in the data repository. A notification rule actionable upon the activating of the first decision rule is identified. A notification is communicated using a computer network to a notification path, consisting of a subset of the plurality of contacts, in accordance with the notification rule.

The invention provides a check point file storage method and device, a check point file acquisition method and device, a medium and a computing device. The storage method of the check point file comprises the steps that according to an adjacent check point of a current check point, the condition meeting the change degree of the adjacent check point relative to a middle check point is determined, and the middle check point represents at least one check point between a nearest base line point and the adjacent check point; determining a storage type of a check point file related to the current check point based on the conforming condition; and saving a checkpoint file related to the current checkpoint based on the saving type.