Search results
Results from the WOW.Com Content Network
The NVIDIA Deep Learning Accelerator (NVDLA) is an open-source hardware neural network AI accelerator created by Nvidia. [1] The accelerator is written in Verilog and is configurable and scalable to meet many different architecture needs. NVDLA is merely an accelerator and any process must be scheduled and arbitered by an outside entity such as ...
However, the frame generation feature is only supported on 40 series GPUs or newer and multi-frame generation is only available on 50 series GPUs. [2] [3] Nvidia has also introduced Deep learning dynamic super resolution (DLDSR), a related and opposite technology where the graphics are rendered at a higher resolution, then downsampled to the ...
In April 2016, Nvidia produced the DGX-1 based on an 8 GPU cluster, to improve the ability of users to use deep learning by combining GPUs with integrated deep learning software. [191] Nvidia gifted its first DGX-1 to OpenAI in August 2016 to help it train larger and more complex AI models with the capability of reducing processing time from ...
NVIDIA (NASDAQ:NVDA) is not only reinventing industries but actually creating new industries with its GPU-based deep learning and artificial intelligence technologies. Source: via Nvidia Today’s ...
The product line is intended to bridge the gap between GPUs and AI accelerators using specific features for deep learning workloads. [4] The initial Pascal-based DGX-1 delivered 170 teraflops of half precision processing, [5] while the Volta-based upgrade increased this to 960 teraflops. [6]
Deep learning anti-aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. [1] DLAA depends on and requires Tensor Cores available in Nvidia RTX cards. [1]DLAA is similar to deep learning super sampling (DLSS) in its anti-aliasing method, [2] with one important differentiation being that the goal of DLSS is to increase performance at the cost of image quality, [3] whereas the ...
During the 2010s, GPU manufacturers such as Nvidia added deep learning related features in both hardware (e.g., INT8 operators) and software (e.g., cuDNN Library). Over the 2010s GPUs continued to evolve in a direction to facilitate deep learning, both for training and inference in devices such as self-driving cars.
Turing is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia. It is named after the prominent mathematician and computer scientist Alan Turing . The architecture was first introduced in August 2018 at SIGGRAPH 2018 in the workstation-oriented Quadro RTX cards, [ 2 ] and one week later at Gamescom in consumer ...