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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. ...
Core config – The layout of the graphics pipeline, in terms of functional units. Over time the number, type, and variety of functional units in the GPU core has changed significantly; before each section in the list there is an explanation as to what functional units are present in each generation of processors.
Tensor cores: A tensor core is a unit that multiplies two 4×4 FP16 matrices, and then adds a third FP16 or FP32 matrix to the result by using fused multiply–add operations, and obtains an FP32 result that could be optionally demoted to an FP16 result. [12] Tensor cores are intended to speed up the training of neural networks. [12]
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.
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.
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 ...
Blackwell is a graphics processing unit (GPU) microarchitecture developed by Nvidia as the successor to the Hopper and Ada Lovelace microarchitectures.. Named after statistician and mathematician David Blackwell, the name of the Blackwell architecture was leaked in 2022 with the B40 and B100 accelerators being confirmed in October 2023 with an official Nvidia roadmap shown during an investors ...