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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.
GPUOpen HIP: A thin abstraction layer on top of CUDA and ROCm intended for AMD and Nvidia GPUs. Has a conversion tool for importing CUDA C++ source. Supports CUDA 4.0 plus C++11 and float16. ZLUDA is a drop-in replacement for CUDA on AMD GPUs and formerly Intel GPUs with near-native performance. [33]
Ampere is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia as the successor to both the Volta and Turing architectures. It was officially announced on May 14, 2020, and is named after French mathematician and physicist André-Marie Ampère.
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]
Ada Lovelace, also referred to simply as Lovelace, [1] is a graphics processing unit (GPU) microarchitecture developed by Nvidia as the successor to the Ampere architecture, officially announced on September 20, 2022.
Painting of Blaise Pascal, eponym of architecture. Pascal is the codename for a GPU microarchitecture developed by Nvidia, as the successor to the Maxwell architecture. The architecture was first introduced in April 2016 with the release of the Tesla P100 (GP100) on April 5, 2016, and is primarily used in the GeForce 10 series, starting with the GeForce GTX 1080 and GTX 1070 (both using the ...
Painting of Alessandro Volta, eponym of architecture. Volta is the codename, but not the trademark, [1] for a GPU microarchitecture developed by Nvidia, succeeding Pascal.It was first announced on a roadmap in March 2013, [2] although the first product was not announced until May 2017. [3]
Nvidia claims a 128 CUDA core SMM has 86% of the performance of a 192 CUDA core SMX. [9] Also, each Graphics Processing Cluster, or GPC, contains up to 4 SMX units in Kepler, and up to 5 SMM units in first generation Maxwell. [9] GM107 supports CUDA Compute Capability 5.0 compared to 3.5 on GK110/GK208 GPUs and 3.0 on GK10x GPUs. Dynamic ...