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Does NVIDIA Prohibit GeForce from Operating in the Data Center? This time it was really "wronged"

via:雷锋网     time:2017/12/31 22:39:39     readed:867

First of all, let's start with "re-inventing" the new regulations first and the entire outbreak of this incident.

The new rules actually come from the NVIDIA GeForce driver download page, and users must check the appropriate license agreement before downloading the driver (similar to the one that must be checked before installing the software).

This also means that - all users of the GeForce driver software actually agree to this license by default.

Controversial content appears in the "Restrictions" section of the "License" section, specificallyThe argument is that "data centers are not licensed to use the software unless the data center is doing blockchain."

This content was first discovered and reported in real time by the German technology magazine golem.de and was posted to the Reddit forum by the user "booooomba" but quietly changed in the description of the news -

"The new NVIDIA EULA prohibits Deep Learning applications to be run on GeForce GPUs. (The new NVIDIA EULA prohibits running deep learning applications on GeForce GPUs.")

What exactly "booooomba" will choose this point to interpret the new rules, we do not know, but the new rules do bring the following questions:

What does this "data center" mean in this rule? Why blockchain operation will be excluded?

The other three items in the "Restricted" clause are common product rights. Why does one such specific provision appear in Article 4?

Next, Lei Feng network on these three major questions for further analysis.

Key question 1: What NVIDIA wants to limit what?

Yesterday, NVIDIA official reply to the Lei Feng network, you can clearly that one point - the new rules targeted at not the ordinary GeForce video card users, but a large data center. In the possession of these large data centers, often largecloud serviceBusiness

In an official statement from NVIDIA: "Users are not encouraged to improperly use our GeForce and TITAN products in harsh, large-scale enterprise environments."

At the same time NVIDIA also stressed: "Researchers often use GeForce and TITAN products for non-commercial or other non-data-center research purposes and NVIDIA has no intention of banning them."

Through these two statements, We can easily see that two of them need to meet the key criteria at the same time: whether commercial use, data center scale.

Combining these two conditions, all we can get is medium to large cloud service providers that are currently offering "GPU Cloud Computing" services to their users.

The key question 2: Why should "put" block chain a horse?

In many previous reports, many media have more or less added a "description":

"NVIDIA has limited the data center this time, but has let go of bitcoin mining!" Some friends even wrote a big title on the title: "The new NVIDIA ban: You can not just go deep and learn GeForce graphics (mining can) But is it really so?

The first point to clarify first is that NVIDIA has never supported GeForce products for mining.

In the middle of this year, NVIDIA once said directly on the activity of a graphics card brand: "NVIDIA discourages GeForce graphics cards from mining and discourages users from doing so. To mine, please use a special mining graphics card."

Although so far this sentence has not been written in any regulation, but the NVIDIA in the middle of this year dedicated mining GPU is the best proof.

This year NVIDIA launched a dedicated graphics card mining code "P106-100" in the consumer market GeForce GTX1060 graphics "modified", but not only no hardware image output interface, and even the Dirext function (MicrosoftDisplay API software, which is currently required for all kinds of games on Windows, is also castrated physically.

There is only one such purpose with great care - protect the consumer market as much as possible.

In the bitcoin's once-lucrative 2013-2014, AMD's HD7000 series had been out of stock for a long time.

But as bitcoin cool down dramatically in 2014 and 2015, more and more AMD graphics, once used for mining, "returned" to the consumer market, and the mass of "abusive" mining products hit AMD's consumer spending dramatically Grade product market, the issue posed by the sale is to make AMD complacent.

Nvidia has actually been on guard for the digging boom of the graphics card. As the rise of the "digging boom" driven by ICO earlier in the year, many NVIDIA graphics OEMs posted on the outside of their product packaging:

"If this product is used for mining, we reserve the right to refuse warranty and maintenance."

From AMD's lesson, to the life of OEM manufacturers, and then to the special mining card P106-100 launch, NVIDIA hide mining can not hide it, how could it expressed its support for the attitude?

P106 mining card driver is actually modified by the GeForce driver

The question is, why the rules of this block will be operating on the block it?

In a video card industry professionals finally tell the mystery of the fruit -Not NVIDIA supports blockchain, but GeForce drivers are actually "indirection" also used in mining dedicated graphics cards.

As for why not specifically get a series of drivers Well, NVIDIA no effort, do not want to spend that effort.

Key Question 3: Why does NVIDIA "highlight" this requirement?

While it's common for everyone who drives a user agreement to agree, NVIDIA puts it in line with the bulk of the product's most basic rules, which shows the importance of this rule.

Why should NVIDIA "highlight" this requirement? In addition to direct causeNVIDIA official mentioned in the statement of product suitability concerns, more importantly, NVIDIA's desire to clarify the consumer market, business market differentiation.

Must be emphasized in advance that this is related to money, but it is not a simple question of money.

Because in the semiconductor market, this situation is ubiquitous, from NVIDIA rival AMD, Intel to the CPU boss Intel, in fact, have their own market segments. Of course, the root cause is the difference between consumer-level and enterprise-level markets.

Consumer-grade market users tend to be relatively simple to use, while demand for products is also more concentrated.

For example, GPU, as long as you have good graphics performance and stable operation on it.

But for enterprises, providing hardware is not enough. You also need to develop various hardware and software interfaces for them. You need to adapt various application scenarios. You need to provide various enterprise-level services and even engineers To the scene for technical assistance.

These wool should naturally be in the body of the sheep, also created a price gap.

NVIDIA solutions for different GPU acceleration applications

How to separately charge the "two flocks of sheep" in the consumer market and the enterprise market respectively and eventually become a problem the semiconductor industry enterprises must face.

It is "common sense" to charge more for cloud services that generate business benefits while requiring more product service.

On the other hand, "consumer-grade products are cheaper than enterprise-level" can even be understood as "NVIDIA collects enterprise-class marketing costs reasonably, which in turn reduces the cost of the consumer market."

This is not only the choice of the company's overall strategy, but also the result of the final choice of market competition rules.

Additional instructions: consumer products really do not apply to the enterprise market it?

As mentioned above, one of the best explanations of the difference between the consumer market and the enterprise market is the difference between the two:

The consumer market GPU is usually installed in the chassis, you need to complete the entire cooling process, while using a shorter duration, lower frequency of use.

In the enterprise market, GPUs are often "stuffed" intoserverRacks, usually only equipped with heat sink and rely on external power (wind, liquid) to complete the cooling process, the use of very long duration, the frequency of use is very high, the stability requirements will always be the first priority.

This also makes the products of both markets very different in all respects, such as appearance.

Take the same for the GeForce GTX1080Ti and Tesla P40, which also use the GP102 core (different models) and very close key processor parameters. The former and the latter's appearance is completely different:

GTX1080Ti comes with a turbofan, while the tail of the graphics cooler does not allow air circulation, this cooling mode in the consumer PC market environment is very efficient.

The Tesla P40 uses a fanless, head-to-tail design. Several sheets can be arranged closely in the server, without affecting the cooling effect.

In addition to the appearance of the difference, NVIDIA actually will take some potential effort.

Although the same materials and processes are used in the GPU production process, there are often some nuances in the finished product.

For example, some GPUs can work at lower voltages and some GPUs have higher overclocking performances. These subtle differences, combined with NVIDIA's differences in product parameters, eventually lead to the redundancy of server products .

Commercial mainstream cloud service is enterprise-class products

After considering many factors, I believe you may already have their own judgments, at least in the Lei Feng network seems:

The new rules are just a clear NVIDIA for their own product business, and "unlucky" in the recruitment of enterprises, are "not follow the cloud service industry rules" company.

Lei Feng Wang also specifically interviewed the domestic cloud service giantAli CloudAnd Tencent cloud, Ali cloud that no comment.

However, according to Lei Feng network query, Ali cloud has in fact maintained close cooperation with NVIDIA, NVIDIA's latest Tesla V100 series GPU has also been in the hands of Ali cloud, is being deployed.

Tencent cloud response is more direct:

"We do not recommend building an enterprise IaaS (Infrastructure as a Service) service with a GeForce GPU and then selling it. From the perspective of the needs of enterprise users, they place more emphasis on stability. Telsa series of stability, energy efficiency does have an advantage. "

When asked about the value of NVIDIA's cooperation with them, Tencent Cloud Engineer said: "NVIDIA's support for our hardware is very rapid.

Tencent cloud on this basis, through in-depth development, introduced a variety of products to meet the needs of users. "

Interestingly,AmazonIn October of this year, AWS introduced NVIDIA's 8-way Tesla V100 GPU Accelerator and delivered it as a completely new cloud service to end users.

In this way, although using GeForce is more profitable on the books, the cloud service providers that make enterprise-level services like this are actually "heterogeneous" in the industry.

Written in the last: draft also feed a well

As the main "power source" in parallel computing and in the AI ​​era, NVIDIA's several GPUs are driving the industry as a result of their ever-improving performance.

And NVIDIA does more than just create a product, develop hardware and software interfaces, provide application solutions, incubate start-up companies, hold technology summits, and more.

With its Black NVIDIA "monopoly," NVIDIA's own technology is better than "leaps and bounds", creating a huge advantage in its products and services.

However, because an enterprise is rapidly restricting it in terms of technology and market to prevent it from being "monopolized," it violates the original intention of technological development and market development, or is it a genuine "abuse of power"?

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