The Look

For a few generations now, Huawei has been cultivating a specific look on its devices. The machined aluminium metal unibody combined with the gaps required for the antenna meant that the Mate S, the Mate 8, the Mate 9, and the P9 felt like part of the family. I didn’t get the same feeling with the base P10 models, and I also don’t get the same feeling with the Mate 10 either.  There are three immediate reasons I can think of.

First are the color choices. As I am writing this piece, I have only seen the Mate 10 and Mate 10 Pro in dark colors. When I put them side-by-side with other devices, it does not look significantly different.


Huawei P9, Huawei Mate 10, Huawei Mate 9, LG V30+

This is especially true in low light, and there’s no defining ‘Huawei’ feature. On the rear, the dark color again hides the fact that it is a Huawei device, aside from the perhaps odd way the dual cameras look. There is a band on some of the colors to signify a ‘strip’ where the cameras are, but this is not part of Huawei’s regular look. The strips we have seen to date come on the P9 and P10, not on the Mate units. One caveat to all this: when Huawei launched the P10 in ‘Greenery’, in collaboration with Pantone, it seemed odd at the time. But I can now pick that phone out of a crowd, it is so obvious. There is something to be said about being different.

A note on colors: the Mate 10 will be offered in Mocha Brown, Black, Champagne Gold, and Pink Gold. The Mate 10 Pro will be in Midnight Blue, Titanium Gray, Mocha Brown, and Pink Gold. The Mate 10 Porsche Design will be in Diamond Black only.

Second is the fingerprint sensor. This is perhaps more of a personal issue, but to date I have preferred rear fingerprint sensors. Moving to the front for the P10 put me off a little (especially in a dark color), and the fact that the regular Mate 10 now goes this way, with a thin fingerprint sensor, seems a little off-putting.

Third is the display. With most major smartphone manufacturers focusing on this ‘all-screen’ display technology, there leaves little room for individualization for the OEMs to make a mark. Apple, either by luck or by design, got this right. Despite the backlash on the iPhone X about that little notch for the cameras, there is no mistaking that a phone with a notch is an iPhone X. The Mate 10 and Mate 10 Pro do not have the same instantly recognizable look. How to make it obviously recognizable (and different to the iPhone) is for someone paid a lot more than me to think about, but it means the Mate 10 and Mate 10 Pro have the potential to be lost in the crowd. The P11 (if there is one next year) will have to do something on this front.

The Silicon: The Kirin 970

On the silicon side, at the heart of the new Mate 10 phones is the Kirin 970 SoC. The new Kirin 970 is fabbed at TSMC using its smartphone-focused 10nm process. We were expecting Huawei/HiSilicon to be the first SoC vendor to 10nm last year, but its release cycle was just before 10nm ramped up for mass production. The chip uses the same ARM Cortex-A73 and ARM Cortex-A53 cores as the previous generation, although this time running from more mature blueprints. For the last generation Huawei was the first to the gate with ARM’s latest cores, which had a bit of concern on the power side as shown in Matt’s review. ARM announced the next generation A75/A55 cores earlier this year, but in true ‘not ready yet’ fashion for Huawei, these designs are not ready for mass production.


A PCB mockup of the Kirin chip, alongside a 1.4 cm square Core i7 logo

Aside from the A73/A53 cores, the Kirin 970 uses ARM’s latest Mali G72 graphics, this time in an MP12 configuration. This means a base +50% gain for graphics cores, along with the improvements from G71 to G72, but the benefits of a ‘wider’ graphics engine typically allow running it at lower frequencies, nearer the power efficiency point, and saving power. In the game of silicon cat and mouse, balancing die size with cost and power, Huawei has gone for added cost/die size in order to reduce power consumption.

HiSilicon High-End Kirin SoC Lineup
SoC Kirin 970 Kirin 960 Kirin 950/955
CPU 4x A73 @ 2.40 GHz
4x A53 @ 1.80 GHz
4x A73 @ 2.36GHz
4x A53 @ 1.84GHz
4x A72 @ 2.30/2.52GHz
4x A53 @ 1.81GHz
GPU ARM Mali-G72MP12
? MHz
ARM Mali-G71MP8
1037MHz
ARM Mali-T880MP4
900MHz
LPDDR4
Memory
2x 32-bit
LPDDR4 @ 1833 MHz
2x 32-bit
LPDDR4 @ 1866MHz
29.9GB/s
2x 32-bit
LPDDR4 @ 1333MHz 21.3GB/s
Interconnect ARM CCI ARM CCI-550 ARM CCI-400
Storage UFS 2.1 UFS 2.1 eMMC 5.0
ISP/Camera Dual 14-bit ISP Dual 14-bit ISP
(Improved)
Dual 14-bit ISP
940MP/s
Encode/Decode 2160p60 Decode
2160p30 Encode
 
2160p30 HEVC & H.264
Decode & Encode

2160p60 HEVC
Decode
1080p H.264
Decode & Encode

2160p30 HEVC
Decode
Integrated Modem Kirin 970 Integrated LTE
(Category 18)
DL = 1200 Mbps
3x20MHz CA, 256-QAM
UL = 150 Mbps
2x20MHz CA, 64-QAM
Kirin 960 Integrated LTE
(Category 12/13)
DL = 600Mbps
4x20MHz CA, 64-QAM
UL = 150Mbps
2x20MHz CA, 64-QAM
Balong Integrated LTE
(Category 6)
DL = 300Mbps
2x20MHz CA, 64-QAM
UL = 50Mbps
1x20MHz CA, 16-QAM
Sensor Hub i7 i6 i5
NPU Yes No No
Mfc. Process TSMC 10nm TSMC 16nm FFC TSMC 16nm FF+

The third main metric for in the hardware is going to be its new ‘Neural Processing Unit’, or NPU. This is silicon dedicated to running artificial intelligence calculations and frameworks, in the form of neural networks. As with other task-specific processors, technically these AI tasks can be run on the CPU or GPU, but because an AI network can run at lower precision and have fixed calculation steps, by developing specific hardware it allows for higher performance at much lower power – the same basic rationale behind GPUs for graphics, ISPs for image processing, etc.

The IP for Huawei’s NPU comes from Cambricon Technologies, and from a high-level might be considered similar to NVIDIA’s Tensor Cores. We are under the impression the Huawei NPU runs several 3x3x3 matrix multiply engines, whereas the Tensor cores run 4x4x4. Huawei runs all this in 16-bit floating point mode, and has a listed performance of 1.92 TFLOPs. This is a relatively high number, and for reference is twice the throughput as what Apple quotes for its new Neural Engine found in the A11 Bionic processors for the iPhone 8 and iPhone X.

The latest unconfirmed reports I have seen put Huawei’s NPU at around 25-30% of the full silicon area. They are quoting ‘under 100 mm2’ for the total die size, and a total of 5.5 billion transistors. That comes out to a surprising 55 million transistors per square millimeter using TSMC’s 10nm process, which is double that of AMD’s Ryzen design, and even above Intel’s own 48MTr/mm2 estimate given at their manufacturing day.

If Huawei did not have an NPU, the die size would be a lot smaller, and here comes a fundamental fact as we move to even smaller process nodes (as in, physically smaller, rather than just a smaller number for a name): it becomes harder and harder to extract pure performance out of a non-parallel design. A chip designer either makes a smaller chip, or spends the transistors on dedicated hardware – either supporting a new video encoder algorithm, a new DSP, or in this case, hardware specifically for artificial intelligence networks.

Smartphone as a Desktop

I remember, almost ten years ago, one of Anand’s prophecies.  It went something like this:

“Give me a smartphone, with all my files, I can dock and use as a PC, and it will revolutionize personal computing.”

At the time, Anand predicted that Microsoft had all the key elements in place: an OS, a smartphone platform, and potentially a gaming platform in the Xbox. All Microsoft had to do was put them all together, although at the time they were focusing on other matters, such as Windows 8 and fixing Windows 8.

Initially we saw Windows RT running on ARM on some hybrid tablets, but the ecosystem did not bite. Eventually we saw Windows' Continuum functionality hit the scene to not a lot of fanfare. It required significant grunt, and we saw a device from Acer, a device from HP, and it also had a slow death.

Qualcomm are going to push the concept via the Windows on Snapdragon platform, using the Snapdragon 835. Qualcomm is working with Microsoft and combined they are working with most of the major laptop OEMs to provide ARM devices that can run almost a full-blown copy of Windows. These are still laptops though, and not Anand’s original vision of a smartphone.

Huawei is going to try and roll its own solution to this. When connecting to a TV, a custom Linux interface will spring up like a traditional desktop operating system, somewhat similar to Samsung's recently launched DeX feature. Bluetooth devices can be connected, and it will have access to all the standard Android apps. The smartphone itself can act as a trackpad for a mouse, or a keyboard, and be connected to something like the MateDock (sold alongside the original Matebook) for additional functionality such as Ethernet, more USB ports, and additional video outputs.

As the headlines for the Mate 10 will be around artificial intelligence, this feature is likely to be left into a footnote for now, similar to how DeX has been on the Galaxy S8 series. In order to get it off the ground, I suspect that Huawei will have to implement some type of ‘Desktop Dock’ that can allow for additional attachments as well as charging at the same time – at this point Huawei says that users will have to buy a splitter cable to support charging at the same time. This is the first generation, so there are some rough edges – it only supports displays at their native resolution up to 1920x1080 for now, and when using a Bluetooth device I did notice some lag. Other features, such as something similar to Windows Snap, should be high on the list.

The Mate 10, Mate 10 Pro, and Mate 10 Porsche Design Microsoft Translate: Artificial Intelligence and Application Lag
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  • cfenton - Monday, October 16, 2017 - link

    The only thing interesting about the Kirin 970 is the AI processor, and they can't provide even a single interesting app that uses it. I'm sure there will eventually be cool uses for it, but probably not before Huawei's next phone comes out. That's not much of a selling feature. Reply
  • Valantar - Monday, October 16, 2017 - link

    I might sound like an old fart here (29 going on 70?), but I just don't get all this AI hype. If the neural network isn't trained through use on the phone, how is this different from any application doing the same job through conventional means? The bar for calling something AI seems to be precariously low. Is it AI if the app/algorithm in question was written by an AI, and it never changes or adapts? I would say no, not unless the output itself is reactive and flexible and adapts over time. After all, any algorithm adapts to new input - that's what they do. If it doesn't learn over time, there's nothing making it even remotely "intelligent". Now, I'm probably way over my head in terms of both programming and hardware understanding, but isn't this just a fancy new marketing term for highly specialized parallel workloads? I.e. something a GPU can do with minor (if any) modifications? If so: what's intelligent about it?

    If all AI can do for consumers is a slightly better job at applying preset filters to your photos than the current algorithms do, I'm glad to pass on that. Thanks, but no thanks.
    Reply
  • serendip - Monday, October 16, 2017 - link

    I wonder what the AI is for. My usual day isn't very usual other than the coffee, weather check and commute, and the phone-related changes are all taken care of by Tasker on Android. I don't need an AI to preempt my actions by doing the opposite of what I want. Reply
  • jospoortvliet - Tuesday, October 17, 2017 - link

    A static non learning AI neural network can do things a normal core can do (e.g. face recognition and object following, translating, voice recognition or generation etc) far more efficient. Just like there is no need to include a GPU unless ypubcare about efficiency... the learning aspect is not core to AI as most networks get trained on super computers and then just used. Reply
  • Valantar - Tuesday, October 17, 2017 - link

    So in other words, the term AI is utterly meaningless. If the algorithm doing face recognition on my phone is generated by training a neural network rather than being written by a programmer, how does this make it "intelligent" in any way? An algorithm is an algorithm, no matter its origins. Sure, it might be a /better/ algorithm, but calling that "intelligence" is nothing more than marketing fluff. I suppose we could call it "AI-originated" or some such, but again: what value does that bring to the table? Reply
  • philehidiot - Thursday, October 19, 2017 - link

    I'm totally with you on this. The AI thing just seems to be a load of marketing bollocks. It may be useful for huge datasets where you want to determine patterns but most of the stuff we see as "AI" is just a load of IF, AND and OR statements. Alexa is a prime example - you have to get the phrasing just right for your question and even then it often struggles. It's the voice assistant equivalent of typing commands in DOS - get one word wrong and it won't work. To me this isn't intelligent, it's voice recognition attached to a list of "IFTTT" statements. Maybe I'm just old and stupid but I made stuff like this as a kid using BASIC which identified key words or phrases being typed and responded appropriately.... or inappropriately given I was a teenager and enjoyed giving out abuse using "AI". Reply
  • FreidoNumeroUno - Saturday, October 21, 2017 - link

    I think the same. AI really sounds like a hype in mobile industry. Its possible apple or some other companies research on AI. But that does not mean they can make any notable changes to the apps or architecture that can actually "learn" unless predefined in the program itself, which makes it just another program with minor changes.
    Apple's AI claims are laughable btw
    Reply
  • varase - Sunday, November 19, 2017 - link

    My guess is a little bird told Huawei that Apple was including a neural processor capable of 600 billion ops/second, and Huawei decided to put in one capable of a trillion ops/second to give them bragging rights (if anyone remembers the snark with which they announced the 970 as the iPhone 8 killer [the iPhone X name at the time in the rumor mills]).

    They had to have compared the 970's CPU and GPU against the A10 and they certainly don't warrant that level of snark - or any snark at all really.

    Unfortunately for them, they had no idea what was coming from the A11 as this is one aspect of Apple's development Apple could actually keep under wraps (since it's entirely in-house).
    Reply
  • Valantar - Monday, October 16, 2017 - link

    RGBW LCD? There goes any hope that Huawei should start caring about colour accuracy, then. Not that my Oneplus 3T needs replacement any time soon, but this is disappointing (and what kept me from getting a Huawei phone last time around - that, and the UX).

    Oh, and that chip is gigantic for a phone SoC. Wow.
    Reply
  • Andrei Frumusanu - Monday, October 16, 2017 - link

    RGBW has absolutely no effect on colour accuracy. Reply

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