Because Nvidia uses IA to make GPUs even faster and better

The world famous chip maker, Nvidia, uses its powerful graphics cards to help its engineers project the next generation of GPUs. Nvidia is currently at the forefront of GPU and artificial intelligence manufacturing. Nvidia DLSS and OptiX are both popular IA technologies that the company has recently developed. The company is also always developing applications that use its GPUs in the best possible way.

Nvidia currently dominates the competition in market share and discrete GPU games. According to Jon Peddie Research, Nvidia has 81% of the dGPU market share. According to a Steam gaming hardware survey, 77.13% of PC gamers use Nvidia GPUs on the platform. This high demand for Nvidia GPUs increased during the pandemic due to a mix of issues with upgrade delivery, scaling and cryptocurrency mining. As a result, Nvidia’s platforms will maintain a double price increase of 300% in 2021 and still be without stocks most of the time. Fortunately, the prices of Nvidia GPUs have started to melt in recent months.

Nvidia produces some of the best GPUs on the market. And now they’re taking their chip design resources to another level, incorporating machine learning resources using their proprietary GPUs. Speaking at an Nvidia GTC, the company’s chief scientist Bill Dally said:It is normal that as an IA specialist you want to stick to that IA and use it to make better chips.So, to project better GPUs, Nvidia’s development team is adopting the design-enabled tools for the current generation of computers with IA resources. It does this mainly in four main areas.

The first area involves mapping the residual voltage to determine where the power is being used in an Nvidia GPU. Dally explained during the presentation that it takes three hours to run it manually in CAD, but using an AI GPU setup can do the same in about 18 minutes. The second area involves parasite testing to verify as a functional circuit project, which is a frequency process that IA lida. In the third area, a GPU with artificial intelligence has different chip layouts to determine a less congested design format. And finally, GPUs are also used to create new designs. Nvidia’s NVCell technology uses Reinforcement Learning to function as an automatic mobile phone layout manager. Dally explained that as technology has always evolved, such as with the transition from our 7nm to 5nm manufacturing process, thousands of cells would have been redesigned using “a very complex set of design backgrounds† Nvidia’s NVCell can apparently recover 92% of the cell library without errors.

For reference, a group of 10 people would have to work for over a year to run a new library of mobile technology. The same can be done these days using some powerful Nvidia GPUs, explains Dally. It is clear that human intervention is still needed in all these areas, for more futuristic than it seems. However, with IA-compatible Nvidia GPUs, companies can save more time and create a chip with a better design. In addition to GPUs, Nvidia in short, may also merge in the CPU industry, but this is a story for another hour.

Source: Nvidia

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