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Nvidia Optimus is a computer GPU switching technology created by Nvidia which, depending on the resource load generated by client software applications, will seamlessly switch between two graphics adapters within a computer system in order to provide either maximum performance or minimum power draw from the system's graphics rendering hardware.
Nvidia's free and open-source driver is named nv. [35] It is limited (supporting only 2D acceleration), and Matthew Garrett, Dirk Hohndel and others have called its source code confusing. [36] [37] [38] Nvidia decided to deprecate nv, not adding support for Fermi or later GPUs and DisplayPort, in March 2010. [39]
For certain GPU models, Nvidia and AMD video card drivers attempt to detect the GPU is being accessed by a virtual machine and disable some or all GPU features. [35] NVIDIA has recently changed virtualization rules for consumer GPUs by disabling the check in GeForce Game Ready driver 465.xx and later. [36]
When it was first introduced, the name was an acronym for Compute Unified Device Architecture, [4] but Nvidia later dropped the common use of the acronym and now rarely expands it. [5] CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. [6]
IOMMU hardware-based GPU isolation support, increasing security by restricting GPU access to system memory. GPU paravirtualization support, enabling display drivers to provide rendering capabilities to Hyper-V virtualized environments. Brightness, a new interface to support multiple displays that can be set to calibrated nit-based brightness ...
It is possible to run SLI without using the bridge connector on a pair of low-end to mid-range graphics cards (e.g., 7100GS or 6600GT) with Nvidia's Forceware drivers 80.XX or later. Since these graphics cards do not use as much bandwidth, data can be relayed through just the chipsets on the motherboard. However, if there are two high-end ...
In the research paper, Apple did not explicitly say that it used no Nvidia chips, but its description of the hardware and software infrastructure of its AI tools and features lacked any mention of ...
This representation does have certain limitations. Given sufficient graphics processing power even graphics programmers would like to use better formats, such as floating point data formats, to obtain effects such as high-dynamic-range imaging. Many GPGPU applications require floating point accuracy, which came with video cards conforming to ...