Search results
Results from the WOW.Com Content Network
The Direct Rendering Manager was created to allow multiple programs to use video hardware resources cooperatively. [4] The DRM gets exclusive access to the GPU and is responsible for initializing and maintaining the command queue, memory, and any other hardware resource.
Hardware-accelerated GPU scheduling: masked as an additional option in the system settings, when enabled offloads high-frequency tasks to a dedicated GPU-based scheduling processor, reducing CPU scheduling overhead. Requires ad-hoc hardware and driver support. [61] Sampler Feedback, allowing a finer tune of the resources usage in a scene. [62]
Support for heterogeneous memory management (HMM), suited only for graphics hardware featuring version 2 of the AMD's IOMMU, was accepted into the Linux kernel mainline version 4.14. [ 12 ] Integrated support for HSA platforms has been announced for the "Sumatra" release of OpenJDK , due in 2015.
Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any transformation of data that can be calculated in software running on a generic CPU can also be calculated in custom-made hardware, or in some mix ...
The SIMT execution model has been implemented on several GPUs and is relevant for general-purpose computing on graphics processing units (GPGPU), e.g. some supercomputers combine CPUs with GPUs. The processors, say a number p of them, seem to execute many more than p tasks.
In computing, CUDA is a proprietary [1] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
GPU virtualization refers to technologies that allow the use of a GPU to accelerate graphics or GPGPU applications running on a virtual machine. GPU virtualization is used in various applications such as desktop virtualization , [ 1 ] cloud gaming [ 2 ] and computational science (e.g. hydrodynamics simulations).
Nvidia started enabling PhysX hardware acceleration on its line of GeForce graphics cards [7] and eventually dropped support for Ageia PPUs. [ 8 ] PhysX SDK 3.0 was released in May 2011 and represented a significant rewrite of the SDK, bringing improvements such as more efficient multithreading and a unified code base for all supported platforms.