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The GeForce 30 series is a suite of graphics processing units (GPUs) developed by Nvidia, succeeding the GeForce 20 series.The GeForce 30 series is based on the Ampere architecture, which features Nvidia's second-generation ray tracing (RT) cores and third-generation Tensor Cores. [3]
Tensor Core FP32 Accumulate Single precision (MAD or FMA) Double precision C870 GPU Computing Module [d] Tesla: May 2, 2007 1× G80 600 128 1350 — GDDR3 384 1.5 1600 76.8 No 0.3456 No 1.0 170.9 Internal PCIe GPU (full-height, dual-slot) D870 Deskside Computer [d] May 2, 2007 2× G80 600 256 1350 — GDDR3 2× 384 2× 1.5 1600 2× 76.8 No 0. ...
Nvidia RTX (also known as Nvidia GeForce RTX under the GeForce brand) is a professional visual computing platform created by Nvidia, primarily used in workstations for designing complex large-scale models in architecture and product design, scientific visualization, energy exploration, and film and video production, as well as being used in mainstream PCs for gaming.
The GeForce 20 series is a family of graphics processing units developed by Nvidia. [8] Serving as the successor to the GeForce 10 series, [9] the line started shipping on September 20, 2018, [10] and after several editions, on July 2, 2019, the GeForce RTX Super line of cards was announced.
The Nvidia Hopper H100 GPU is implemented using the TSMC N4 process with 80 billion transistors. It consists of up to 144 streaming multiprocessors. [1] Due to the increased memory bandwidth provided by the SXM5 socket, the Nvidia Hopper H100 offers better performance when used in an SXM5 configuration than in the typical PCIe socket.
Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...
The Tensor cores perform the result of deep learning to codify how to, for example, increase the resolution of images generated by a specific application or game. In the Tensor cores' primary usage, a problem to be solved is analyzed on a supercomputer, which is taught by example what results are desired, and the supercomputer determines a ...
The project was reported to have initially been targeting video streaming chips for data centers, but had its scope expanded to include desktop GPUs. [13] In June 2018, Intel confirmed it planned to launch a discrete GPU in 2020. [14] The first functional discrete "Xe" GPU, codenamed "DG1", was reported as having begun testing in October 2019. [15]