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Does VMware workstation have GPU passthrough?

Does VMware workstation have GPU passthrough?

VMware Workstation 15 does not support GPU pass-through at the moment. The only VMware product that does support it is VMware vSphere. Even if it was supported, there isn’t any way to pass through a GPU that is being used by the OS the hypervisor is running on, or you would lose the display on the parent OS.

How do I enable hardware acceleration in VMware?

Select a virtual machine in the Virtual Machine Library window and click Settings. Under System Settings in the Settings window, click Display. Select the Accelerate 3D graphics check box. The version of DirectX supported by your hardware version is displayed.

What is VMware BitFusion?

In August 2019, VMware acquired BitFusion, a pioneer in the virtualization of hardware accelerated devices with a strong focus on GPU technology. BitFusion offers a software platform that decouples specific physical resources from the servers they are attached to in the environment.

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Can you game on VMware?

To get the most out of your virtualized video game, click on the “Full Screen” icon of VMware Workstation. And game virtualization also works without problem. Thanks to this new feature, you can now play games installed in a virtual machine.

What VM software supports GPU passthrough?

NVIDIA enables GeForce GPU passthrough for Windows virtual machines. Linux users can now play Windows games through Virtual Machines. NVIDIA will now fully support GeForce GPU passthrough, a technology that enables access to GPU on a host machine from the virtual machine environment.

What is GPU passthrough?

GPU passthrough is a technology that allows the Linux kernel to directly present an internal PCI GPU to a virtual machine. The device acts as if it were directly driven by the VM, and the VM detects the PCI device as if it were physically connected.

How does BitFusion work?

VMware vSphere Bitfusion virtualizes hardware accelerators such as graphical processing units (GPUs) to provide a pool of shared, network-accessible resources that support artificial intelligence (AI) and machine learning (ML) workloads. You can also monitor client consumption of GPUs and assign quotas and time limits.