32 results about "Average memory" patented technology

A method of building a computer system is provided. The method comprises determining an average memory storage per virtual machine, determining an average number of virtual machines per host computer, and determining an amount of memory storage per memory pool. The method also comprises determining a maximum number of host computers per memory pool based on the average memory storage per virtual machine, the average number of virtual machines per host computer, and the amount of memory storage per memory pool. The method also includes assembling the appropriate number of host computers and memory storage, organized around memory pools, to handle a specific number of virtual machines.

A computer application program executing on a computer, such as a portable computer, is selected for termination by first identifying computer application programs executing on the computer. A priority value is assigned to each of the identified computer applications. The priority value is based on multiple characteristics of the identified computer application programs. The computer application program with the smallest priority value is automatically terminated. If the computer application program with the smallest priority value is in a modal state in which it waits for a response from a user, then a default response is provided to the application prior to terminating the computer application program. The characteristics associated with the computer application programs may include average launch times, average memory usages, a class or type of application, frequencies of usage, and an amount of data stored on the computer by the computer application program.

A method, system and computer program product for optimizing memory usage of an application running on a virtual machine. A virtual machine memory block is pre-allocated and the average memory usage of the virtual machine is periodically computed using statistics collected from the virtual machine through an API. If the memory usage average becomes higher than a maximum threshold, then a recovery mode is entered by releasing the virtual machine memory block and forcing the running application to reduce its processing activity; optionally, a garbage collector cycle can be forced. If the computed memory usage average becomes lower than a minimum threshold value, which is lower than the maximum threshold value, then a normal mode is entered by re-allocating the virtual machine memory block and forcing the running application to resumes its normal processing activity. Optionally, when the virtual machine is idle, a deep garbage collection is forced.

The invention relates to an energy-saving dynamic adjustment method of a virtual web application cluster in a cloud computing environment. The energy-saving dynamic adjustment method includes: a building the virtual web application cluster; b monitoring the use condition of a virtual web application server; c judging the conditions of average central processing unit (CPU) use ratio and average memory use ratio in a section of [min%, max%]; d continuing to monitor the virtual web application server if both the CPU use ratio and average memory use ratio are in the section of [min%, max%]; e using a dynamical expanding method to build a new server if one of the CPU use ratio and average memory use ratio is larger than max% and the other of the CPU use ratio and average memory use ratio is larger than min%; f using a dynamic reduction method to remove a server on a host machine with the lowest resource use equivalent if one of the CPU use ratio and average memory use ratio is smaller than min% and the other of the CPU use ratio and average memory use ratio is smaller than max%; and g using a dynamic specification variation expanding method to build a new server if one of the CPU use ratio and average memory use ratio is smaller than min% and the other one of the CPU use ratio and average memory use ratio is larger than max%. The energy-saving dynamic adjustment method adjusts the web application cluster through the dynamical expanding method, the dynamic reduction method or the dynamic specification variation expanding method, ensures concentrated and lowest quantity operation of the host machine in a cloud platform, and achieves effective energy saving effect.

The invention discloses a method for realizing instruction buffer lock, which comprises the following steps: 1) analyzing program summary, pre-running a section of program, and recording a memory block access sequence, citation times, re-access time interval and hit times; and 2) selecting memory blocks to be locked in a buffer, setting an access counter and a least recently used (LRU) counter for each memory block, accessing memory block access times recorded in the counters, assigning weights N1 and N2 to the access counter and LRU counter in each memory block, counting according to N1*access times+N2*(LRU counter limit-LRU value), and if the counted values are greater than a threshold M, locking the memory blocks in the buffer, wherein N1+N2=1. In the invention, the memory blocks locked in the instruction buffer can be replaced only when the lock is removed, the buffer hit rate is improved greatly, the accesses to low-level storage are reduced, and average memory access delay is reduced.

The invention provides a fuzzy test method. The method comprises the following steps of: selecting a predetermined number of seeds from a seed pool; mutating the selected seeds to generate a pluralityof program inputs; monitoring the running state of a target program which has received the program inputs, and obtaining memory state information of a test process; determining an average memory state space of the current test according to the acquired memory state information; aiming at the seeds participating in the test in the seed pool, respectively comparing memory state space correspondingto each seed with the average memory state space; and reserving the seeds of which the memory state space is greater than the average memory state space. The invention also provides a device for realizing a fuzzy test, electronic equipment and a computer readable storage medium.

The invention provides a method, a device and a system for scheduling a memory access command. The method comprises the steps: a memory controller receives a to-be-scheduled memory access command sent by memory access equipment, wherein the to-be-scheduled memory access command includes an original priority of the to-be-scheduled memory access command; the memory controller inserts the to-be-scheduled memory access command into a scheduling queue according to the relation between existing memory access commands in the scheduling queue, the relation between the to-be-scheduled memory access command and the existing memory access commands in the scheduling queue and the relation between the original priority of the to-be-scheduled memory access command and a current priority of the existing memory access commands in the scheduling queue. Therefore, memory access bandwidths and memory access delays of different memory access equipment can be satisfied, the operational stability of a computer system is improved, the idleness rate of a memory bus of the computer system is decreased, the bandwidth utilization rate is improved and the average memory access delay is reduced.

The embodiment of the invention discloses a message degradation method and a related device, which are used for degrading according to the actual condition of user equipment so as to improve the degradation efficiency. The method provided by the embodiment of the invention comprises the following steps: periodically acquiring current memory use information of a client and current CPU use information within a preset time length; according to the current memory usage information and the current CPU usage information, obtaining average memory usage information and average CPU usage information within a preset duration; sending the average memory usage information and the average CPU usage information to a server; receiving a first threshold sent by the server, wherein the first threshold is obtained by the server according to the average memory usage information and the average CPU usage information; when the message is received, storing the moment when the message is received in a momentqueue, wherein the moment queue is used for storing the moment when the message is received; judging whether the number of moments stored in the moment queue exceeds a first threshold value or not; and if so, performing degradation processing on the message according to the type of the message.

The embodiment of the invention provides a cloud platform and a virtual machine scheduling method and device based on the cloud platform, and belongs to the technical field of the Internet. The virtual machine scheduling method based on the cloud platform comprises the following steps: step 1, determining to distribute a host machine node for a virtual machine to be scheduled; step 2, obtaining the average CPU utilization rate and the average memory utilization rate of a plurality of host machine nodes of the cloud platform in the latest preset time period; step 3, at least according to the average CPU utilization rate and the average memory utilization rate of each host machine node in the nearest first preset time period, counting the weight value of the current available resource measurement of each host machine node; and step 4, allocating the host machine node with the maximum weight value of the current available resource measurement to the virtual machine to be scheduled.

The invention discloses a graph database caching method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining a plurality of sampling point objects and sampling edge objects obtained through sampling; memory space occupation of each sampling point object and each sampling edge object is acquired; calculating the average memory space occupation of the sampling point object and the average memory space occupation of the sampling edge object; based on the average memory space occupation of the sampling point objects, the average memory space occupation of the sampling edge objects and the size of a cache space, determining the number of maximum point objects and the number of maximum edge objects which can be accommodated in the cache space; and caching based on the maximum point object number and the maximum edge object number. According to the technical scheme provided by the invention, the utilization rate of the cache space can be improved, so that the subsequent data access efficiency is improved.

Embodiments of the invention provide a virtual machine scheduling method and device, and a computer readable storage medium. The method comprises the steps of determining related feature values in a network function virtualization (NFV) scene; wherein the related characteristic values at least comprise the number of average virtual processors (vCPUs) required by a plurality of pre-created virtualmachines and the number of required average memories; and determining which Hypervisor server each virtual machine should be created on one by one based on the related feature values and in combination with a weight algorithm, wherein the Hypervisor server is the Hypervisor server with the highest total weight.

The invention provides an anti-addiction method and device based on a memory, electronic equipment and a storage medium. The method comprises the following steps: after an application program is started, acquiring a use time threshold t and an average memory consumption threshold s of the application program according to attribute information of the application program and a current time state; monitoring foreground running time T of the application program; when the current station running time T is larger than or equal to the use time threshold value t of the preset time proportion, the current average memory consumption m of the application program is monitored; and when the current average memory consumption m meets an average memory consumption threshold value s in a preset memory proportion range, starting an anti-addiction strategy for the application program. According to the method, dual management and control can be carried out based on time and memory, real-time dynamic monitoring is carried out on memory changes in the use process of application programs, especially entertainment game application programs, anti-addiction management and control of a system cannot be avoided no matter how the application programs change, and a user is prevented from being addicted to the application programs.