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Intel Vs. Nvidia: The Easy Path For Intel

Aug. 07, 2018 9:43 PM ETIntel Corporation (INTC), NVDAAMD, GOOG, GOOGL214 Comments

Summary

  • Tomorrow, Intel will announce developments to better compete with AMD and Nvidia.
  • I think the development regarding how to compete with Nvidia is obvious, and I say as much.
  • This development is straightforward and will allow Intel to compete well and quickly. I believe it will have an impact on Nvidia's server room prospects.
  • Members of my private investing community, Idea Generator, receive access to my breaking news coverage of this idea. Get started today >>

Image result for Google TPU

Google's TPU. Soon, an equivalent will be found inside Intel chips.

Tomorrow, Intel (NASDAQ:INTC) will announce its plans regarding how it’s going to fight off Advanced Micro Devices (AMD) and Nvidia (NASDAQ:NVDA) in the server room.

A good while ago, I had already postulated that GPU compute was going to take share in the server room, and Nvidia was the main competitor bringing such a threat. In the meantime, we can say that “GPU compute” is being dominated by AI applications, where GPUs are used to speed up neural network training and inference. Nvidia dominates the field there.

So tomorrow, Intel will announce something to fight back against Nvidia. What will that be? I think this is both easy to guess and easy for it to implement. Intel will basically include a logic block dedicated to accelerating NNs (Neural Networks). This is the same as what others like Nvidia have also done (by including tensor cores within its Tesla P100, for instance), or the same as Google’s (GOOG) TPU. Or the same as what Tesla is planning to unveil next year.

With little chip-making expertise, Google managed to bring its TPU (Tensor Processing Unit) to production in a mere 15 months. Intel can do it faster. And when it comes to beating GPUs at NN acceleration, this step is obvious. Moreover, while the GPU part of Nvidia’s P100 is rather “optional” for someone wanting to run mostly NN acceleration, the same can’t be said for the CPU part, which always needs to be present. As a result, including NN acceleration within a CPU is even more obvious than doing so on a GPU.

The benefits of this obvious approach are also obvious. An NN logic bloc is massively more efficient for accelerating NNs than a CPU or GPU. For

This article was written by

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Analyst’s Disclosure: I am/we are short NVDA. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

The "short Idea" is for NVDA only.

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