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In computing, CUDA is a proprietary [1] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
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 ...
First generation Nvidia Ion products included a MCP79MX chipset with integrated GeForce 9400M G GPU, DDR3-1066 or DDR2-800 SDRAM, and the Intel Atom processor. The original reference platform was based on a Pico-ITXe motherboard designed for netbook and nettop devices.
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.
CUDA is a parallel computing platform and programming model that higher level languages can use to exploit parallelism. In CUDA, the kernel is executed with the aid of threads. The thread is an abstract entity that represents the execution of the kernel. A kernel is a function that compiles to run on a special device. Multi threaded ...
The simplest way to understand SIMT is to imagine a multi-core system, where each core has its own register file, its own ALUs (both SIMD and Scalar) and its own data cache, but that unlike a standard multi-core system which has multiple independent instruction caches and decoders, as well as multiple independent Program Counter registers, the ...
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CUDA execution core counts were increased from 32 per each of 16 SMs to 192 per each of 8 SMX; the register file was only doubled per SMX to 65,536 x 32-bit for an overall lower ratio; between this and other compromises, despite the 3x overall increase in CUDA cores and clock increase (on the 680 vs. the Fermi 580), the actual performance gains ...