29 results about "Working set" patented technology

Systems and methods for using object storage as a primary storage tier for a file system of a virtual storage system are provided. According to one embodiment, ephemeral storage of a host on which a virtual storage system is running in the cloud is used as an external cache in which all or some subset of file system metadata may be stored, for example, to boost read IOPS and reduce latency of the read path. In various examples, external cache policies may be defined to trigger adding to, updating, and / or re-warming the external cache to accelerate access to file system metadata, thereby making a virtual storage solution that maintains all file system data and file system metadata within object storage a suitable and cost-effective platform for certain types of workloads. In some example, the working set of a workload may also be kept in the external cache to further accelerate read performance of the virtual storage system.

The invention relates to a pointer analysis-based incremental data flow path extraction method. The method comprises the following steps of: firstly, acquiring an initial pointer variable related to an incremental code as a task variable set; then, performing reverse query on the task variables based on the pointing relation constraint graph to obtain a basic variable set and a memory object pointed by the basic variable set; and after the working set is initialized, executing pointing relation propagation, propagating the memory object to a pointing set of the task variable, and classifying a new association pointer found in propagation into an indirect variable set. And executing explicit dependency query on the indirect variable set, adding a new dependency variable into the task set, repeating the process until the constraint graph is stable, and finally obtaining pointing information of all variables. And an inter-process data dependence sub-graph is constructed, and an incremental data flow path is extracted. According to the method, through a locality principle and a reverse query strategy, an analysis range is limited to incremental code related variables, and the overhead and memory problems of global analysis are avoided.

The application belongs to the technical field of computer memory management, and discloses an active page replacement method and system based on regional reuse mode identification, which comprises the following steps: working set identification based on memory access sample clustering, obtaining memory access samples by sampling the memory access instructions of a process, and clustering the samples to obtain the working set in the current monitoring window in real time; adaptive memory region division based on working set integration, dividing the address space into regions according to virtual address continuity and adaptively splitting / merging; reuse mode identification based on state transition, determining the reuse mode of each region according to the switching between hot and cold states of each region and the state duration; active page replacement and prefetching method based on the reuse mode, prefeteching the regions that will reach the reuse time, and triggering the replacement of the regions that are in the cooling state for a long time. Compared with the existing passive page fault triggering method, the application can reduce the page fault and jitter, reduce the replacement traffic, and improve the application execution efficiency and system throughput.

A working set of data blocks to be flushed from a cache to non-volatile data storage is identified, and a physical block of non-volatile data storage is allocated. At least some of the data blocks in the working set are compressed to generate compressed data blocks. The compressed data blocks are stored into the physical block of non-volatile data storage. For each one of the compressed data blocks stored into the physical block, an independent virtual layer pointer indicating a location of that compressed data block within the physical block of non-volatile data storage is stored into a single, flexibly sized virtual layer block that is allocated for storing the working set. The flexibly sized virtual layer block is part of a logical address mapping tree.

[Problem] To provide a work setting system for setting work of a mounted function unit that is mounted on a moving body capable of autonomous movement at a movement destination of the moving body. [Solution] A work setting system according to the present invention comprises: a movable moving body; the mounted function unit that executes a function at a movement destination by being mounted on the moving body; a map display unit that displays, on a user interface, a map that indicates a region in which the moving body can move; a point setting unit that sets a point that constitutes the movement destination of the moving body on the map, said point being the location where the function of the mounted function unit is executed; a point function display unit that displays, for the point, functions that can be executed by the mounted function unit, said functions being displayed in a manner that makes it possible to select a function; and a link function unit that associates the execution of the function that is selected by the point function display unit with the point that is set by the point setting unit.

A working-set structure is used to organize cached data for storing to persistent storage, which includes leaf structures and page descriptors (PDs) for data pages to be persisted. Upon adding a new PD located in an address range of an existing leaf structure, a PD population count of the existing leaf structure is compared to a predetermined PD population threshold. When the count is below the threshold, the new PD is incorporated into an existing set of PDs for the existing leaf structure, and otherwise (a) a new leaf structure is created, and (b) the new leaf structure is used for the new PD and later-added PDs in the address range. Flush parallelism is enhanced by avoiding large differences in PD population across a set of leaf structures.

The invention discloses an interaction method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: displaying a time-limited group carrying a group theme through a target interface, and enabling members in the group to share a creation work in a preset group effective time period through the time-limited group; in response to a group participation event for a target time-limited group, displaying a group interaction page of the target time-limited group, the target time-limited group providing an intra-group work set for interaction of intra-group members; and in response to a work sharing event for the target created work, updating the work set in the group and / or a work sharing message sent in the group, and after the current moment exceeds the end moment of the effective period of the time-limited group, sending the work sharing message to the target created work. At least part of the created works in the intra-group works set of the time-limited group are stored and displayed in association with the group theme and / or the effective time period and / or the current account, and the creation passion of the user can be stimulated by newly adding an interaction mode for the created works of the user.

1. The name of the design product: the working setting graphical user interface of electronic equipment. 2. The use of the design product: for an electronic equipment. 3. The design points of the design product: the graphical user interface. 4. The picture or photo that best shows the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the present graphical user interface is used for working setting. Design 1 front view to design 8 front view are working setting interfaces, and the user can make relevant settings through touch operation according to the content prompt of the interface. Design 9 front view is a working setting interface, and the user can set more parameters by sliding up in the pop-up window, as shown in the interface change state diagram of design 9.

The application relates to a GPU progressive optimization method for neural operator backbone network reasoning and belongs to the electronic information technical field.The method comprises the following steps: step S1, initializing constraints and tolerances;step S2, obtaining baseline execution time and reference results through baseline measurement;step S3, obtaining an estimated split value based on a working set model and expanding;step S4, performing KSweep evaluation and consistency checking, and preferably obtaining; a process of scanning and measuring each candidate set is called KSweep; step S5, fixing, adding fusion reasoning optimization, and performing consistency verification, if the consistency verification is passed, outputting and saving the optimal configuration, and directly loading and executing in the running stage; otherwise, backtracking or adjusting and recalibrating, and returning to step S3. The application shortens the reuse distance between adjacent layers, reduces the round-trip overhead of intermediate activation between the video memory and the cache, and thus improves the reasoning efficiency.

Automatically generating definitions of materialized views. Generally, automated MV generation identifies a set of candidate MVs by examining the working set of query blocks. Once candidates are formed, the candidate MVs are further evaluated to compute the benefit to the candidate MVs. An improved method for generating a candidate set of MVs is described herein. The improved method is referred to as the extended covered sub-expression technique (ECSE). Under ECSE, various relationships between join sets other than strict equivalence are used to generate new result join sets. Such relationships include subsets, intersections, supersets, and unions, which are described in further detail below. In some cases, relationships between the result join sets and the initial join sets are considered to generate new result join sets. The final result join sets are then used to form a candidate set of MVs.

The present disclosure provides a cluster management method, device, electronic equipment and storage medium. The cluster management method comprises: initiating a work cluster addition and deletion task by a meta cluster, the work cluster addition and deletion task being used to instruct to add a specified work cluster in a cluster system or to instruct to delete the specified work cluster in the cluster system; wherein the cluster system comprises at least one cluster, the at least one cluster comprising one meta cluster and at least one work cluster, the meta cluster carrying operation and maintenance control of the cluster system, the operation and maintenance control comprising work cluster addition and deletion processing, and the work cluster carrying a business container to execute a business task; and according to indication information of the addition and deletion task, controlling the specified work cluster to implement corresponding cluster deployment or removal in the cluster system. According to the present application, the work cluster can be expanded or deleted according to actual needs through the meta cluster, thereby helping to improve the applicability of the cluster system.

A working set of data blocks to be flushed from a cache to non-volatile data storage is identified, and a physical block of non-volatile data storage is allocated. At least some of the data blocks in the working set are compressed to generate compressed data blocks. The compressed data blocks are stored into the physical block of non-volatile data storage. For each one of the compressed data blocks stored into the physical block, an independent virtual layer pointer indicating a location of that compressed data block within the physical block of non-volatile data storage is stored into a single, flexibly sized virtual layer block that is allocated for storing the working set. The flexibly sized virtual layer block is part of a logical address mapping tree.

According to the method for improving the crosspiece chart, the super crosspiece chart obtained through the method, the terminal product of the super crosspiece chart and the storage medium of the super crosspiece chart, a string of work completed in a natural sequence in the longitudinal axis direction of the crosspiece chart is combined into one work to be expressed, and the work is defined as a work set; a different code name is correspondingly set for each subitem work under the work set to serve as an assignment of each subitem work, and the same type of work of different work sets has the same code name; the code names of the sequential sub-item work of each work sink are recorded on the corresponding position, representing the work process through the time continuation, of the row where the work sink is located in the crosspiece chart, so that the time continuation expressed by the transverse line of the position is replaced. According to the method, the number of longitudinal tables of the crosspiece chart is greatly reduced, adverse effects on vision and psychology caused by huge increase of the number of lines and the number of the tables are eliminated, the application range of the crosspiece chart is greatly expanded, the method is visual, vivid, simple and clear, and key paths of work are easy to find.

The invention discloses a large model reasoning method and system based on active load awareness, and belongs to the technical field of large model reasoning services. Aiming at the problem that reasoning service is difficult to consider resource efficiency and service quality due to burstiness and heterogeneity of mixed loads in the prior art, the invention provides a closed-loop method of cycle planning, online scheduling and self-adaptive adjustment and optimization. In the period planning stage, prospective instance pre-configuration is carried out by utilizing long-term load prediction; in the online scheduling stage, the request is routed and scheduled through response length sensing and a heterogeneous scheduling strategy; and in the self-adaptive tuning stage, fine-grained correction is carried out on the instance scale based on peak working set pre-judgment. According to the method, resource supply and request scheduling are coordinated, the SLO is guaranteed, the delay peak is effectively inhibited, the GPU utilization rate is improved, and the method is suitable for an enterprise-level LMaaS platform.

The present application relates to the technical field of artificial intelligence computing power scheduling, in particular to a load balancing and performance guarantee method for multi-modal AI computing power service, comprising: firstly, analyzing request characteristics, extracting a computing work set and a minimum safe capacity to generate a local key-value cache baseline, and fitting to generate a minimal algebraic arrival curve of network direct writing traffic; then, combining the baseline, the curve and the network topology routing hop count to build a key-value cache non-eviction model and solve the physical cache capacity limit; further, determining the number of isolated paths according to the limit and the single-path capacity, calling the hardware register to set the capacity bitmask, and building a space-time physical isolation architecture; finally, when the traffic breaks through the upper bound of the curve, establishing an orthogonal damping constraint relationship based on equivalent arithmetic strength, and synchronously reducing the computing end micro-batch and the network end transmission unit. The present application solves the problem of physical squeezing of local cache by network direct writing through bottom-layer physical isolation and double-end orthogonal feedback.

Innovations in training a machine learning model using an accelerator pipeline with deferred updates to model parameters are described. An accelerator identifies one or more first-class micro-batches (“MBs”) and a second-class MB of a working set. A first-class MB contains, as inputs, frequently accessed embeddings stored in graphics processing unit (“GPU”) memory. The accelerator schedules the first-class MB(s) for training using one or more GPUs. During the training, the accelerator obtains the second-class MB, which contains, as inputs, non-frequently accessed embeddings stored in main memory. At least some updates to the model parameters from the training with the first-class MB(s) are deferred until after training with the second-class MB. The accelerator schedules the second-class MB for training. Finally, after the training with the second-class MB, the accelerator updates the non-frequently accessed values for the second-class MB. At this point, the GPU(s) also update model parameters, applying deferred updates.

In one embodiment, a computer-implemented method includes receiving, at a wearable mask, first information pertaining to a work setting, wherein the first information comprises video, audio, haptic feedback, or some combination thereof, determining, using an edge processor communicatively coupled to the wearable mask and based on the first information, one or more first characteristics of the work setting, generating, using the edge processor and based on the one or more first characteristics of the work setting, one or more first control instructions configured to modify one or more first operating parameters of a tool, and transmitting, to the tool, the one or more first control instructions to modify the one or more first operating parameters of the tool.

The invention belongs to the technical field of computer memory management, and discloses an active page changing method and system based on regional reuse pattern recognition, and the method comprises the steps: based on the working set recognition of memory access sample clustering, sampling a memory access instruction of a process to obtain a memory access sample, the samples are clustered to obtain a working set in the current monitoring window in real time; carrying out adaptive memory region division based on working set integration, dividing an address space into regions according to virtual address continuity, and carrying out adaptive splitting / merging; identifying a reuse mode based on state transition, and determining the reuse mode of each region according to the switching of each region between cold and hot states and the state duration; according to the active page swap-out and prefetching method based on the reuse mode, a region about to reach the reuse moment is prefetched, and swap-out is triggered for a region in a cooling state for a long time. Compared with an existing passive missing page triggering method, the method has the advantages that missing pages and jitter can be reduced, swap-in and swap-out flow is reduced, and application execution efficiency and system throughput are improved.

This invention discloses a physically isolated minimal deterministic safety actuator and its control method for intelligent driving, belonging to the field of functional safety technology for intelligent driving. The device adopts a hardware architecture physically independent of the main decision-making unit, possessing independent power supply and timing. Its runtime working set is no larger than 10KB, and it has no operating system or dynamic memory. Deterministic control is achieved through hardware-fixed logic, with a worst-case response time of no more than 50ms. The device is equipped with independent sensing paths and hardwired execution interfaces, enabling direct actuator driving without relying on the vehicle bus. Cross-domain health monitoring enables multi-node status monitoring and computing power management. This invention can provide a safety fallback in the event of a system-wide failure, resisting common-cause failures, meeting ASIL D functional safety level, and features low cost, small size, easy integration, and suitability for mass production. It solves the problems of insufficient independence and poor real-time performance of traditional safety islands.

In one embodiment, a computer-implemented method includes receiving, at a wearable mask, first information pertaining to a work setting, wherein the first information comprises video, audio, haptic feedback, or some combination thereof, determining, using an artificial intelligence agent executed on an edge processor communicatively coupled to the wearable mask and based on the first information, one or more first characteristics of the work setting, generating, using the artificial intelligence agent executed on the edge processor and based on the one or more first characteristics of the work setting, one or more first control instructions configured to modify one or more first operating parameters of a tool, and transmitting, to the tool, the one or more first control instructions to modify the one or more first operating parameters of the tool.

The embodiment of the invention provides a multi-energy coupling process energy consumption optimization method and device, and the method comprises the steps: obtaining an equipment working parameter set of each equipment unit in a multi-energy coupling system, building a multi-energy coupling process energy consumption optimization model of each equipment unit based on the equipment working parameter set, determining a to-be-optimized decision variable according to the model, and carrying out the optimization of the to-be-optimized decision variable. Determining a target function according to the maximum benefit of the whole process and the minimum single-factor energy consumption, and determining constraint conditions according to the processing capacity of the device, the purchase quantity of raw materials, the product yield and the low-hydrocarbon parameters; generating a particle swarm containing a preset number of particles, and setting initial positions and speeds for the particles; the position of the particle is related to the value of the decision variable; and based on the multi-energy coupling process energy consumption optimization model, the objective function and the constraint condition, solving the multi-energy coupling process energy consumption optimization model by using a multi-objective particle swarm optimization algorithm, and determining an optimization result of the value of the decision variable. According to the embodiment of the invention, the energy consumption of the whole plant is reduced under the condition of ensuring the maximum benefit of the whole process.

Antagonistic queries can have a high resource and time footprint triggering a range of issues, such as causing compilation performance degradation of other queries and machine failures. Described herein are techniques for automatically identifying antagonistic queries and redirecting the antagonistic queries to dedicated resources. This redirecting can help better balance the workload on different work clusters and to isolate antagonistic workloads from impacting the compilation and execution performance of other queries.

A working-set structure is used to organize cached data for storing to persistent storage, which includes leaf structures and page descriptors (PDs) for data pages to be persisted. Upon adding a new PD located in an address range of an existing leaf structure, a PD population count of the existing leaf structure is compared to a predetermined PD population threshold. When the count is below the threshold, the new PD is incorporated into an existing set of PDs for the existing leaf structure, and otherwise (a) a new leaf structure is created, and (b) the new leaf structure is used for the new PD and later-added PDs in the address range. Flush parallelism is enhanced by avoiding large differences in PD population across a set of leaf structures.

A task setting system is provided that sets tasks for onboard functional units mounted on an autonomously movable body at a destination of the autonomously movable body. [Solution] The work setting system of the present invention comprises a movable vehicle 2, an on-board function unit 4 that is mounted on the vehicle and executes functions at its destination, a map display unit 42 that displays a map on a user interface showing the area in which the vehicle can move, a point setting unit 44 that sets a point on the map that will become the destination of the vehicle and at which the function of the on-board function unit will be executed, a point function display unit 46 that displays functions that can be executed by the on-board function unit for each point so that they can be selected, and a link function unit 52 that links the execution of the function selected by the point function display unit to the point set by the point setting unit.

The invention relates to a GPU progressive optimization method for neural operator backbone network reasoning, and belongs to the technical field of electronic information. Comprising the steps of S1, initializing constraints and tolerances; s2, baseline measurement is carried out to obtain baseline execution time and a reference result; s3, obtaining a pre-estimated segmentation value based on the working set model and expanding the pre-estimated segmentation value; s4, carrying out KSweep evaluation and consistency check, and carrying out optimization; the process of scanning and measuring the candidate set one by one is called KSweep; s5, fixing, newly adding fusion reasoning optimization, carrying out consistency verification, if the consistency verification is passed, outputting and storing optimal configuration, and directly loading and executing in an operation stage; otherwise, returning or adjusting and recalibrating, and returning to the step S3. According to the method, the multiplexing distance between adjacent layers is shortened, and the round-trip overhead of intermediate activation between the video memory and the cache is reduced, so that the reasoning efficiency is improved.

The invention discloses an embedded system snapshot optimization method and system oriented to a resource-constrained environment. The method comprises the following steps: firstly, configuring snapshot parameters according to hardware parameters of the embedded equipment; secondly, constructing a page state management structure, and continuously capturing page writing events during scanning in a pre-copying stage so as to distinguish a high-writing-frequency page from a low-writing-frequency page; executing multiple rounds of traversal in the pre-copying stage to ensure the convergence of the working set, and judging whether to terminate the pre-copying stage or not according to the convergence; storing the identified working set pages instead of all dirty pages in the shutdown stage again, setting write protection for non-working set pages, and restoring the operation of the virtual machine; after the operation of the virtual machine is recovered, a non-working set is stored in the background; and finally, real-time redundancy elimination and writing are carried out. According to the method, the shutdown duration can be effectively shortened in an embedded scene with dense dynamic write-in and obvious working set change, the snapshot duration and the storage write-in burden are reduced, and the overall performance of an embedded virtualization operation framework is improved.

Systems and techniques for cost-based prefetching are described. In one example, a processor includes a cache system having a hierarchy of one or more cache levels and an instruction prefetcher associated with a cache level of the cache system. The instruction prefetcher encodes fetch requests to a prefetcher table and determines a cost associated with each entry based on a memory level from where the instructions associated with the fetch requests were fetched. The instruction prefetcher evicts entries in the prefetcher table based on the cost associated with one or more corresponding fetch requests in response to adding new entries. The described techniques hide instruction fetch latency that a processor frontend experiences with workloads that have code working sets that do not fit in higher levels of the cache system.

The invention discloses a method and system for automatically positioning windows cloud desktop memory leak, and belongs to the technical field of cloud computing, and the method is implemented by the following steps: establishing a driver-level memory monitoring mechanism, tracking the change conditions of a page storage pool and a non-page storage pool in real time through a PoolMon tool, and storing the change conditions of the page storage pool and the non-page storage pool in real time; collecting memory allocation statistics of each pool label, handle counting of a driving object and a memory occupation trend, and emphatically monitoring a driving module related to the virtualization component; an application-level memory monitoring mechanism is established, private working sets, handle counts and GDI object use conditions of all processes are collected regularly through an expanded WMI query interface, a process-level memory use file is generated, and a memory behavior mode in the life cycle of the process-level memory use file is recorded; and starting a verification process when the potential memory leak is detected. According to the invention, automatic distinguishing and identification of drive-level and application-level memory leaks can be realized; and based on an intelligent judgment mechanism of a threshold value, false alarms are reduced.

Methods, devices, and systems for information routing. A destination indication corresponding to data is received. The data is transmitted on a routing path based on routing information retrieved from a routing table bypass that includes a routing cache and a match mask. In some implementations, the destination indication comprises at least a portion of a network address. Some implementations include bypassing a routing table based on the routing information being present in the routing cache or the match mask. In some implementations, a total number of entries of the routing cache is fewer than a number of addresses in a working set. In some implementations, the match mask is dynamically programmable. In some implementations, an entry of the match mask includes a bit mask, a bit match and a routing destination associated with at least a portion of an address. In some implementations, the data comprises a packet.