CLUSTER RESOURCE MANAGEMENT USING ADAPTIVE MEMORY DEMAND

    公开(公告)号:US20210397480A1

    公开(公告)日:2021-12-23

    申请号:US17466185

    申请日:2021-09-03

    Applicant: VMware, Inc.

    Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. In some examples, a local memory estimate is determined for a workload. The local memory estimate is determined using a memory reclamation parameter for the workload executed by a current host of the workload. A destination memory estimate is also determined for the workload. The destination memory estimate is determined using a full memory estimate unreduced by memory reclamation parameters. The workload is executed using a host that is selected in view of an analysis that uses the local memory estimate for the current host and the destination memory estimate for at least one destination host.

    Cluster resource management using adaptive memory demand

    公开(公告)号:US11113109B2

    公开(公告)日:2021-09-07

    申请号:US16742111

    申请日:2020-01-14

    Applicant: VMware, Inc.

    Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. Some aspects involve determining a destination memory estimate and a local memory estimate for various workloads executing in a datacenter. Goodness scores are determined corresponding to the candidate workload being executed on a number of different hosts. The goodness scores are determined using the local memory estimates for the currently executing workloads, the destination memory estimate is utilized for the candidate workload if it is not executing on the corresponding host. The workloads are balanced based on the goodness scores.

    CLUSTER RESOURCE MANAGEMENT USING ADAPTIVE MEMORY DEMAND

    公开(公告)号:US20210216372A1

    公开(公告)日:2021-07-15

    申请号:US16742111

    申请日:2020-01-14

    Applicant: VMware, Inc.

    Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. Some aspects involve determining a destination memory estimate and a local memory estimate for various workloads executing in a datacenter. Goodness scores are determined corresponding to the candidate workload being executed on a number of different hosts. The goodness scores are determined using the local memory estimates for the currently executing workloads, the destination memory estimate is utilized for the candidate workload if it is not executing on the corresponding host. The workloads are balanced based on the goodness scores.

    EFFICIENTLY PURGING NON-ACTIVE BLOCKS IN NVM REGIONS USING POINTER ELIMINATION

    公开(公告)号:US20200133846A1

    公开(公告)日:2020-04-30

    申请号:US16174264

    申请日:2018-10-29

    Applicant: VMware, Inc.

    Abstract: Techniques for efficiently purging non-active blocks in an NVM region of an NVM device using pointer elimination are provided. In one set of embodiments, a host system can, for each level 1 (L1) page table entry of each snapshot of the NVM region, determine whether a data block of the NVM region that is pointed to by the L1 page table entry is a non-active block, and if the data block is a non-active block, remove a pointer to the data block in the L1 page table entry and reduce a reference count parameter associated with the data block by 1. If the reference count parameter has reached zero at this point, the host system purge the data block from the NVM device to the mass storage device.

    HIERARCHICAL RESOURCE TREE MEMORY OPERATIONS

    公开(公告)号:US20190171390A1

    公开(公告)日:2019-06-06

    申请号:US15830850

    申请日:2017-12-04

    Applicant: VMware, Inc.

    Abstract: Hierarchical resource tree memory operations can include receiving, at a memory scheduler, an indication of a proposed modification to a value of a memory parameter of an object represented by a node of a hierarchical resource tree, wherein the proposed modification is made by a modifying entity, locking the node of the hierarchical resource tree by the memory scheduler, performing the proposed modification by the memory scheduler, wherein performing the proposed modification includes creating a working value of the memory parameter according to the proposed modification, determining whether the proposed modification violates a structural consistency of the hierarchical resource tree based on the working value, and replacing the value of the memory parameter with the working value of the memory parameter in response to determining that the proposed modification does not violate a structural consistency of the hierarchical resource tree based on the working value, and unlocking the node of the hierarchical resource tree by the memory scheduler.

    Cluster resource management using adaptive memory demand

    公开(公告)号:US11669369B2

    公开(公告)日:2023-06-06

    申请号:US17466185

    申请日:2021-09-03

    Applicant: VMware, Inc.

    CPC classification number: G06F9/5016 G06F9/505 G06F2209/5022

    Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. In some examples, a local memory estimate is determined for a workload. The local memory estimate is determined using a memory reclamation parameter for the workload executed by a current host of the workload. A destination memory estimate is also determined for the workload. The destination memory estimate is determined using a full memory estimate unreduced by memory reclamation parameters. The workload is executed using a host that is selected in view of an analysis that uses the local memory estimate for the current host and the destination memory estimate for at least one destination host.

    Efficiently Purging Non-Active Blocks in NVM Regions Using Virtblock Arrays

    公开(公告)号:US20220129377A1

    公开(公告)日:2022-04-28

    申请号:US17571417

    申请日:2022-01-07

    Applicant: VMware, Inc.

    Abstract: Techniques for efficiently purging non-active blocks in an NVM region of an NVM device using virtblocks are provided. In one set of embodiments, a host system can maintain, in the NVM device, a pointer entry (i.e., virtblock entry) for each allocated data block of the NVM region, where page table entries of the NVM region that refer to the allocated data block include pointers to the pointer entry, and where the pointer entry includes a pointer to the allocated data block. The host system can further determine that a subset of the allocated data blocks of the NVM region are non-active blocks and can purge the non-active blocks from the NVM device to a mass storage device, where the purging comprises updating the pointer entry for each non-active block to point to a storage location of the non-active block on the mass storage device.

Patent Agency Ranking