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DLSS uses machine learning to combine samples in the current frame and past frames, and it can be thought of as an advanced and superior TAA implementation made possible by the available tensor cores. [13] Nvidia also offers deep learning anti-aliasing (DLAA). DLAA provides the same AI-driven anti-aliasing DLSS uses, but without any upscaling ...
Specialized processing cores on some modern workstation's GPUs are dedicated for deep learning since they have significant FLOPS performance increases, using 4×4 matrix multiplication and division, resulting in hardware performance up to 128 TFLOPS in some applications. [59] These tensor cores are expected to appear in consumer cards, as well.
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.
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
AlexNet is highly influential, resulting in much subsequent work in using CNNs for computer vision and using GPUs to accelerate deep learning. As of mid 2024, the AlexNet paper has been cited over 157,000 times according to Google Scholar.
The specific problem is: Needs attention from a current expert to incorporate modern developments in this area from the last few decades, including TPUs and better coverage of GPUs, and to clean up the other material and clarify how it relates to the subject. WikiProject Artificial intelligence may be able to help recruit an expert. (November 2021)
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]
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 ...