132 results about "Request queue" patented technology

The invention provides a chip verification method and device, equipment, a medium and a program product, and the method comprises the steps: receiving a first operation instruction of a to-be-verified module and a second operation instruction of a reference model in parallel, the reference model being a function model used for simulating the expected behavior of the to-be-verified module; searching a first instruction record matched with the first operation instruction from a request queue of the reference model, and searching a second instruction record matched with the second operation instruction from a request queue of the to-be-verified module; and determining a verification result of the to-be-verified module according to a comparison result of the first operation instruction and the first instruction record and / or a comparison result of the second operation instruction and the second instruction record. According to the invention, a structured and reusable universal chip verification method is realized, so that a tedious customized scoreboard design is replaced, and the efficiency and accuracy of verification work are greatly improved.

The present application relates to a data replay method, a data processing unit, a network interface card, a device, and a storage medium. The method comprises: when a storage stack is restarted, acquiring a replay-pending request queue from a persistent memory, the replay-pending request queue being a queue obtained by mapping a transmission buffer area into the persistent memory, and the transmission buffer area being used for receiving a request from a host side; on the basis of the replay-pending request queue, acquiring a replay-pending request from the persistent memory; and resending the replay-pending request to a target acceleration component directed to a storage device, so as to instruct the storage device to store target data which resides in the persistent memory and corresponds to the replay-pending request. In the method, a request queue, a request, and data corresponding to the request are stored in the persistent memory in advance, and if the storage stack is restarted, the replay-pending request is recovered from the persistent memory, eliminating the need for DMA and encryption / decryption techniques, and shortening an interruption duration of a storage data path, thereby improving data storage efficiency on the host side.

The invention discloses an on-chip network system based on cache consistency, belongs to the technical field of computer network communication, and aims to solve the technical problems of global consistency flow overload, on-chip network scheduling delay, directory node load imbalance and too high core resource occupation of a traditional router architecture. Comprising a multi-core cluster, distributed directory nodes, a multi-channel network-on-chip and a hardware acceleration module, cores are connected through a bus, and local cache consistency is achieved based on an MSI protocol; a directory node divides a physical address space into a plurality of fragments based on an address hash fragmentation mechanism, each directory node maintains a sparse directory table, and when the length of a request queue of any directory node exceeds a set threshold value, a dynamic load balancing mechanism is triggered; the multi-channel network-on-chip provides a control channel, a data channel and a configuration channel, and each channel performs message scheduling based on a dynamic priority mechanism; and the hardware acceleration module is used for processing three types of consistent transactions.

Cache, cache management method, and electronic device. The cache includes: multiple cache lines, a first read request queue and a second read request queue; a first read request queue is configured for storing and sending a first read request to a memory controller; the first read request is configured for requesting data from memory and storing the data in the memory controller; the number of the first read requests stored in the first read request queue is greater than that of the multiple cache lines; the second read request queue is configured for storing and sending a second read request to memory controller; and the second read request corresponds one-to-one with the first read request, and the second read request is used to request data corresponding to the first read request from the memory controller when a cache line corresponding to the first read request is idle

The invention relates to a solid state disk dynamic wear balancing method and system based on data popularity, and the method comprises the steps: tracking the access characteristics of each data page in a solid state disk through a page-level counter, and enabling the access characteristics to comprise the write operation frequency, the modification period and the survival time; the data pages are dynamically divided into high-heat data, medium-heat data or cold data based on a preset threshold value, and corresponding heat layering labels are marked; collecting accumulated writing times and I / O request queue length of each channel of the solid state disk in real time, and calculating wear imbalance degree and load imbalance degree; performing data exchange according to a preset exchange mode priority based on the popularity hierarchical label, the wear imbalance degree and the load imbalance degree; and updating the logic mapping table and the channel state parameters, carrying out statistics on the balance income and the system overhead, and dynamically correcting the tolerance coefficient based on the current load type according to the income-overhead ratio.

The invention provides a Kubernetes-based large model reasoning optimization method, system and equipment, and the method comprises the steps: constructing a resource scheduling assembly for a large model, and monitoring a real-time resource state at a current moment; constructing a batch processing agent component for the large model, performing feature analysis on the received reasoning request queue, and determining request features corresponding to the reasoning requests in the reasoning request queue; the real-time resource state is evaluated according to the request features, and the batch processing size is adjusted based on the evaluation result to generate the optimal batch processing length; batching the reasoning requests in the reasoning request queue according to the optimal batch processing length, and packaging each batch of reasoning requests into batch data; the resource scheduling component is utilized to distribute batch data to Pod in the K8s cluster for reasoning, a large model reasoning result is obtained, the quantity of the reasoning Pod is automatically adjusted according to the flow and the resource load required by reasoning, a GPU with poor performance is prevented from becoming a system bottleneck, and the responsiveness and the stability of service are improved.

The invention relates to a designated driver service request processing method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a received current request sent by a designated driver service request queue, determining a target request type according to the current request; the designated driving service request queue comprises a new request sub-queue, a detection retry request sub-queue and a step retry request sub-queue; the target request type is the request type of the current request; the request type comprises a new request, a detection retry request or a step retry request; in response to the fact that the target request type is a new request or a stepped retry request, obtaining a historical request processing success rate; the historical request processing success rate is the processing success rate of each historical request in the previous preset first time window; and in response to the situation that the historical request processing success rate is smaller than a first success rate threshold, intercepting the current request, updating the target request type as a detection retry request, and transferring and storing the current request to a detection retry request subqueue. By adopting the method, the efficiency can be improved.

The invention relates to the technical field of large model service management, and discloses a system for carrying out self-adaptive current limiting on a token number and a QPS called by a large model. A dynamic monitoring module of the system is responsible for collecting a request flow data set comprising a token consumption sequence, a request frequency sequence and a response delay sequence; a traffic feature extraction module performs multi-dimensional feature analysis on the data set to generate a traffic feature matrix containing token consumption rate, request frequency fluctuation coefficient and delay sensitivity index; the adaptive current-limiting decision module dynamically matches a load balancing strategy based on the matrix, and generates a current-limiting control parameter set containing a token quota threshold and a QPS upper limit threshold; the real-time regulation and control module dynamically adjusts the request queue according to the request queue to generate a new request scheduling sequence; and the feedback optimization module monitors the execution effect and iteratively updates the load balancing strategy. According to the invention, through real-time perception and dynamic adjustment, refined and adaptive management of large model service resources is realized.

The invention discloses a request processing method and device in a distributed system, equipment, a medium and a product, and relates to the field of distributed systems. The method comprises the following steps: sending a target IO request; inserting the target IO request into a request queue based on the priority information of the target IO request; processing at least one IO request in the request queue in sequence; wherein the at least one IO request is ranked in the request queue according to the priority from high to low. The IO requests which can cause the real-time influence on the training tasks are processed preferentially, and the IO requests which do not influence the training real-time performance are processed in parallel while the training tasks are ensured to be continuously carried out. The waiting time for the computing nodes to carry out the training tasks is shortened, and the overall resource utilization rate and the task execution efficiency of the distributed system are improved.

Systems and methods for selectively bypassing an external cache (EC) of a storage system are provided. In one example, when the EC backing storage device is saturated, reads bypass the EC and are completed via a redundant array of independent disks (RAID) subsystem of the storage system. One or more performance metrics for the EC backing storage device may be monitored to predict one or more saturation thresholds (e.g., in terms of latency and / or throughput). Based on this monitoring, tuning may be performed to drive utilization of the EC into a “knee region” of a performance (or response) curve of the EC backing storage device. For example, the depth of one or more request queues at the front-end of an EC lookup may be manipulated based on a current measure of saturation relating to the EC backing storage device to limit the number of in-flight reads pending for the EC.

The application relates to the technical field of chip micro-architecture, and provides a task dispatching system and a computing chip, wherein the system comprises a central controller and a plurality of computing units; the central controller comprises a queue manager, the queue manager is used for managing a task queue in the central controller; the task queue stores the identities of a plurality of to-be-processed task blocks; the computing unit is used for sending a task request to the queue manager when any task block is completed; the queue manager is used for responding to the task request, obtaining the identity of a target task block to be processed from the managed task queue, and returning the identity of the target task block to the computing unit corresponding to the task request; and the computing unit is further used for receiving the identity of the target task block and performing a task based on the identity of the target task block, so that the computing resources of the chip are fully utilized, the "tail effect" that other computing units are forced to idle and wait due to long time consumption of individual tasks is avoided, and the overall operation performance is improved.

This invention relates to the field of computer file system technology, and in particular to a file system kernel service and high-concurrency scheduling method based on a unified protocol. The method includes the following steps: Step 1: Starting a receiving thread and a file operation thread on the server side, the file operation thread including a lightweight thread and a heavyweight thread; Step 2: Listening to the network port through the receiving thread to receive JSON-formatted requests sent by clients, the requests containing timestamps and operation types; operation types include copy, move, create directory, delete, list, and restore; Step 3: Storing the received requests in a receiving queue; Step 4: Retrieving requests from the receiving queue and distributing them according to the operation type; Step 5: Executing the operation; This invention exposes file operation capabilities through independent processes and a unified JSON protocol. The six types of operation semantics, as well as the semantics of abort and recoverable deletion, are all uniformly defined at the protocol layer. The dual-type threads and request queue improve throughput and stability under multiple clients and large-scale tasks.

The embodiment of the invention provides a cache device, an operation method, electronic equipment and an artificial intelligence processor. The cache device comprises a receiving module, a scheduling module and an execution module. The receiving module is configured to receive a plurality of requests; the scheduling module comprises a plurality of waiting queues, the scheduling module is configured to store the plurality of requests into the plurality of waiting queues respectively and correspondingly based on the request types of the plurality of requests, and the plurality of waiting queues comprise a read-write request queue and a calculation request queue; the execution module comprises a plurality of execution assembly lines, the execution assembly lines are respectively coupled with corresponding waiting queues in the plurality of waiting queues, the execution assembly lines further comprise a read-write assembly line and a calculation assembly line, the read-write assembly line is configured to execute read-write requests transmitted from the read-write request queue, and the calculation assembly line is configured to calculate the read-write requests transmitted from the read-write request queue; the compute pipeline is configured to execute compute requests transmitted from the compute request queue. The cache device can improve the calculation efficiency of the universal graphics processor.

Embodiments of the present disclosure provide a data read / write method, system, and apparatus, a computing device, and a storage medium. The data read / write method comprises: receiving, by means of an asynchronous I / O layer, a data read / write request sent from a user space, and storing the data read / write request in a request queue; when the asynchronous I / O layer determines that the data read / write request is of a pass-through type, sending the data read / write request to a driver layer; and parsing the data read / write request by means of the driver layer, and sending request information of the data read / write request to a target processing end device for read / write processing. The data read / write request sent from the user space is received by means of the asynchronous I / O layer, and is sent to the driver layer after the data read / write request is determined to be of the pass-through type, thereby reducing context switching and data copying overhead, and improving the processing efficiency of I / O operations. The request is parsed at the driver layer and sent to the processing end device for read / write processing, thereby optimizing the scheduling of I / O tasks, reducing disk addressing time and I / O latency, and improving overall performance and system stability.

A system-on-chip (SoC) is accessed. The SoC includes a mesh network and one or more coherency ordering agents (COAs). The COAs coordinate coherency for one or more processors coupled to the mesh network. The COAs are coupled to one or more communication converters (CCs) by the mesh network. A processor sends a request to a target device. The request is based on a first communications protocol and includes a memory address. The request is sent by a COA to a CC. A request queue within the CC stores the request. The request is checked against one or more additional requests. The CC translates the request, resulting in a converted request, based on a second communications protocol. The translating is based on the checking. The CC transmits the converted request to the target device.

The application discloses a decoding method, an electronic device and a storage medium. The decoding method comprises the following steps: obtaining a plurality of decoding request queues with different priorities; at least one decoding request is contained in at least one decoding request queue; decoding requests in each decoding request queue are obtained in a descending order of priority to perform decoding. Through the method, the decoding order of the decoder can be reasonably arranged, and the QoS performance of the storage device is improved.

A power demand management method is provided. The method includes an electric climate control unit (CCU) detecting one or more additional electric CCUs in proximity to the electric CCU and the electric CCU establishing a communication link with the one or more additional electric CCUs. The method includes generating and transmitting a pending power request by the electric CCU for power from a power source. The electric CCU monitors one or more additional pending power requests from the one or more additional CCUs and monitors a position of the electric CCU in a power request queue of the electric CCU and the one or more additional CCUs for obtaining power from the power source. Further, the method includes the electric CCU soliciting power from the power source when a level of the position of the electric CCU in the power request queue is sufficient to solicit power from the power source.

The application provides a memory bank bit flip error real-time detection and correction method and system, which is applied to the technical field of memory bank, obtains to-be-returned data and associated information, and performs instant risk judgment on the data items in the current return window to output a delivery qualification state. When the risk item is identified, the delivery authorization of the original data is blocked, the request context information is retained, and the risk item is corrected. Then, the correction result is bound to the request identifier based on the request context information, and the correction result is injected into the return path according to the link scheduling strategy to replace the original data and complete the delivery. In addition, the subsequent request queue is locally shunted according to the correction processing state, the continuous return of the request unrelated to the risk item is maintained, and the system throughput is maximally guaranteed. Therefore, the application has the beneficial effects of guaranteeing data reliability, significantly improving the concurrent processing capacity and response efficiency of the memory system.

A method, device and system of scheduling a resource of a processor is provided. The method includes: receiving a current task request forwarded by a proxy node from a client user corresponding to any container; adding the request to a queue: adding the current task request to a task request queue of a processor corresponding to the client user; allocating a resource: in a case where a resource of the processor is idle, fetching a task request at a head of the task request queue and allocating the resource of the processor to the currently fetched task request; and returning a result: returning a task execution result to the proxy node after the task is completed and releasing the resource of the processor; and when the task request queue is not empty, skipping to the step of allocating a resource.

The invention provides an automatic operation and maintenance scheduling system and method in a cloud computing environment. The method comprises the following steps: predicting a load demand curve through historical load time sequence data and real-time load indexes of an online service cluster; generating an arbitration decision of resource operation and maintenance scheduling according to the simulated resource occupation contour of the online service cluster constructed by the load demand curve and the resource request queue corresponding to the offline task cluster; issuing a reserved resource permission to the second control ring by the arbitration decision, and injecting a virtual node resource view complementary with the reserved resource permission in time and space into the first control ring; and when the real-time load index triggers the first control ring to perform resource scaling operation, the first control ring executes instance scaling in a resource boundary limited by the virtual node resource view, and the second control ring starts and stops the offline task instance in the corresponding resource block according to the current reserved resource permission. According to the technical scheme provided by the invention, collaborative scheduling of operation and maintenance of the online service cluster and the offline task cluster can be realized under load fluctuation.

A fair and efficient guest to hypervisor virtual machine socket protocol may be provided by: in response to a host determining to reject a message received from a guest that was previously accepted for processing by the host, transmitting a rejection to the guest; in response to receiving, at the guest, the rejection, adding the message to a processing request queue on the guest; in response to determining that resources to handle the message have become available for the guest, transmitting an indication to the guest that the host is able to reaccept the message; in response to receiving, at the guest, the indication, retransmitting the message to the host according to the processing request queue; and in response to receiving the message from the guest a second time, accepting the message in an execution queue in a virtual memory of the host.

This invention provides a method and system for distributing I / O across SAS expanders between a controller and a disk. The method includes: an ITS module retrieving I / O requests from an I / O request queue and encapsulating them into SCSI commands; selecting a target device address; selecting the local expander channel address for odd-numbered slots and the peer expander channel address for even-numbered slots; the SAS driver transmitting the SCSI command to the local expander via the SAS bus; the local expander selecting the corresponding channel for transmission based on the SAS address encapsulated in the SCSI command; and when the local expander fails to distribute the I / O, it returns a corresponding I / O error to the ITS module, which modifies the SAS address in the SCSI command to the corresponding channel address on the peer expander and re-distributes the I / O. This invention provides a method and system for distributing I / O across SAS expanders between a controller and a disk, allowing I / O to be distributed to the storage disk via the expander belonging to the peer controller when I / O distribution between the current controller and the expander / storage disk fails.

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing at least one program, method, and user interface to facilitate a camera sharing session between two or more users. A camera sharing session is initiated based on session configuration information comprising a user identifier of a user permitted to control image capturing at a camera communicatively coupled to a first device. A trigger request is received from the second device and in response, an image capture, which results in at least one image, is triggered at the camera and the image is transmitted to the second device.

This application provides a data exchange out-of-order suppression method and electronic device, belonging to the field of switch technology. This method can suppress out-of-order data exchange at each level of a switching system. The data exchange out-of-order suppression method provided in this application can be applied to multi-level switching systems. The method includes: a first scheduler transmitting first dequeue information to the data path; the first dequeue information includes a request number that the first scheduler dequeues from a waiting request queue; each request in the request queue carries a request number; the request number is used to identify the source and / or service from which each request originates, and requests from the same source or service carry the same request number; controlling the closure of a first switch among multiple first switches corresponding to the request number in the first dequeue information, and a second scheduler scheduling the dequeue of the request corresponding to the closed first switch.

This invention relates to the field of industrial automation control and communication systems, and provides a PLC library management method based on cloud function-driven architecture. The method includes defining PLC control logic as library module source files, parsing and function-converting them into cloud functions and uploading them to a cloud function library; dragging the target cloud function into the business process or logic diagram, automatically identifying the corresponding function ID and generating a queue of function execution requests to be called; receiving call requests from the queue, determining whether there are existing cloud function instances available for scheduling; if no available instances are found, dynamically instantiating the target cloud function and performing function calculations based on an event queue mechanism; and filtering out a set of functions to be deployed to edge devices based on the calculation results and distributing them to the edge cloud devices. By combining the PLC library management module with cloud function-driven architecture, the basic unit of PLC cloud computing is reduced to a function, providing finer granularity, allowing users to directly deploy function code, and automatically completing tasks such as data redundancy, load balancing, regional redundancy, and log recording.

The invention relates to the technical field of computers, in particular to a Kubernetes container vertical stretching adjustment method and device, and the method comprises the steps: collecting business data, system data and scene data; determining a message priority coefficient according to the message delay requirement, and quantizing and generating a load index according to the message priority coefficient, the request queue length and the push error rate; diagnosing a performance state according to the average push delay, the memory page change rate and the network bandwidth utilization rate; constructing a resource demand index by combining the load index, the performance state and the active connection number, and judging a resource demand state according to the resource demand index; and determining a scaling direction based on the CPU utilization rate, the memory utilization rate and the network bandwidth utilization rate, and determining a CPU adjustment amount and a memory adjustment amount in combination with the resource demand state, the scaling direction and the context switching times of the process in the container. According to the method, the utilization efficiency of cluster resources is maximized, and a higher-level intelligent solution is provided for elastic scaling of cloud native applications.

Systems and methods for learning behavioral activity correlations. A method includes intercepting a plurality of requests, wherein each of the plurality of requests is directed to a respective destination entity of a plurality of destination entities; creating a request queue by queueing the plurality of requests; inspecting contents of the plurality of requests; separately forwarding each intercepted request to its respective destination entity based on the request queue; monitoring runtime output of each of the plurality of destination entities, wherein the runtime output includes behavioral activities of the plurality of destination entities; and training a machine learning model based on the contents of the plurality of requests the runtime output of each of the plurality of destination entities, wherein the machine learning model is trained to output request-output correlations between groups of requests and subsequent behavioral activities.

The application provides a kind of industrial cloud platform computing resource dynamic scheduling method and system combined with deep learning, it is related to industrial cloud platform technical field, first, the real-time request queue parameter set and real-time container resource parameter set of containerized application instance set in industrial cloud platform are acquired, then correlation coupling analysis is carried out to generate service quality sensitivity descriptor set, then call deep learning request flow prediction network to identify request flow evolution mode, generate predicted request timing distribution set in future prediction time window, according to the node available resource parameter set of the two sets above Resource reservation dynamic programming is carried out to physical computing node cluster, generate dynamic binding relationship mapping set, finally, based on the dynamic binding relationship mapping set Migration scheduling instruction sequence is generated and issued to container orchestration scheduler, to realize the dynamic accurate scheduling of computing resource.

Systems and methods disclosed herein for improving data retrieval for dashboards using data caching. The system may implement a cache memory to store results for executed queries and / or anticipated queries, allowing for data to be retrieved asynchronously, and may implement a request queue to distribute the queries among processing nodes.

The present application relates to the technical field of transmission system of measured value, control signal or similar signal, disclose a kind of photovoltaic cell cabinet remote monitoring and protection method, comprising: remote terminal unit local determination measured value whether deviate from normal state statistical boundary model, and send corresponding heartbeat maintenance signal or heartbeat abnormal signal;Remote center receives heartbeat abnormal signal, will request join pull request queue, and according to center itself downlink congestion threshold control data pull control signal release rate, the present application is solved by queue arbitration of center side, when batch exception arrives, the downlink control channel congestion problem of immediate pull logic of abnormal reporting, guarantee system remote control stability.