公开(公告)号：US11681544B2

公开(公告)日：2023-06-20

申请号：US17395147

申请日：2021-08-05

Applicant: VMware, Inc.

Inventor： Xin Xu ,  Na Zhang ,  Xiaolong Cui ,  Jiayuan He ,  Ridhi Surana

IPC: G06F9/455 ,  G06N20/00 ,  G06F11/34 ,  G06F11/30

CPC classification number: G06F9/45558 ,  G06F11/301 ,  G06F11/3433 ,  G06N20/00 ,  G06F2009/45595

Abstract: Disclosed are aspects of interference-aware virtual machine assignment for systems that include graphics processing units (GPUs) that are virtual GPU (vGPU) enabled. In some examples, an interference function is used to predict interference for assignment of a workload to a graphics processing unit (GPU). The interference function outputs a predicted interference to place the workload on the GPU. The workload is assigned to the GPU based on a comparison of the predicted interference to a plurality of predicted interferences for the workload on various GPUs.

公开(公告)号：US20210373930A1

公开(公告)日：2021-12-02

申请号：US17395147

申请日：2021-08-05

Applicant: VMware, Inc.

Inventor： Xin Xu ,  Na Zhang ,  Xiaolong Cui ,  Jiayuan He ,  Ridhi Surana

IPC: G06F9/455 ,  G06N20/00 ,  G06F11/34 ,  G06F11/30

Abstract: Disclosed are aspects of interference-aware virtual machine assignment for systems that include graphics processing units (GPUs) that are virtual GPU (vGPU) enabled. In some examples, an interference function is used to predict interference for assignment of a workload to a graphics processing unit (GPU). The interference function outputs a predicted interference to place the workload on the GPU. The workload is assigned to the GPU based on a comparison of the predicted interference to a plurality of predicted interferences for the workload on various GPUs.

公开(公告)号：US11113093B2

公开(公告)日：2021-09-07

申请号：US16432108

申请日：2019-06-05

Applicant: VMware, Inc.

Inventor： Xin Xu ,  Na Zhang ,  Xiaolong Cui ,  Jiayuan He ,  Ridhi Surana

IPC: G06F9/455 ,  G06N20/00 ,  G06F11/34 ,  G06F11/30

Abstract: Disclosed are aspects of interference-aware virtual machine assignment for systems that include graphics processing units (GPUs) that are virtual GPU (vGPU) enabled. In some examples, a plurality of workloads are executed alone and co-located with other workloads in a virtual graphics processing unit (vGPU)-enabled system to determine baseline parameters and measured interferences. A machine learning model is trained to predict interference based on the measured interferences and the baseline parameters. A workload is assigned and executed on a particular GPU associated with a minimum predicted interference with the workload based on currently-assigned workloads of the particular GPU.