GPU Performance

For 3D graphics and games the Kirin 970 is the first GPU to make use of ARM’s second generation Bifrost GPU architecture, Heimdall / G72. The new IP is an evolutionary update over last year’s Mali G71 with density and efficiency updates. 

The density increase as well as the process node shrink allowed HiSilicon to increase the GPU core count by 50% from 8 to 12 while still reducing the GPU block complex in terms of absolute silicon area. There is no mincing around with words on last year’s G71 performance: The GPU unfortunately came nowhere near the projected efficiency goals stated by ARM in neither the Exynos 8895 nor the Kirin 960. The Kirin 960 especially was remarkable in terms of how we saw devices powered by it reach until then unheard of average power figures at the peak performance states, ranging at around the 9W mark for the Mate 9. I still remember 2 years ago I had praised HiSilicon for implementing a GPU conservative enough that it could properly sustain its maximum performance state within the device thermal envelope, staying below 4W. Nevertheless before continuing the power argument any power figures of the Kirin 970, let’s go over the peak performance figures of the most commonly used industry 3D benchmarks.

3DMark Sling Shot 3.1 Extreme Unlimited - Overall

3DMark Sling Shot 3.1 Extreme Unlimited - Graphics

3DMark Sling Shot 3.1 Extreme Unlimited - Physics

In 3DMark Sling Shot 3.1 Extreme Unlimited we see the G72 on the Kirin 970, oddly enough, not improving at all. I ran the benchmark several times and made sure thermals weren’t the causen but still the phone wasn’t able to increase performance over the Kirin 960 save for a small increase in the physics score. I’m not yet sure what the cause is here – I wasn’t able to monitor GPU frequency as I haven’t rooted the device yet so I can’t be sure that it’s using some kind of limitation mechanism.

GFXBench Car Chase ES 3.1 / Metal (Off Screen 1080p)

GFXBench Manhattan ES 3.1 / Metal (Off Screen 1080p)

GFXBench T-Rex HD (Offscreen)

Moving on to Kishonti’s GFXBench we see the Kirin 970 achieve its theoretical gains of 15-20%. As a reminder while the GPU core count increased 50% from 8 to 12 cores, the frequency has been vastly reduced from the maximum 1033MHz down to 746MHz, leaving only a more marginal performance upgrade to be expected.

The Kirin 970’s G71MP12 ends up slightly below the Exynos 8895’s G71MP20 and the Snapdragon 835’s Adreno 540 in more compute bound workloads such as Manhattan 3.1 or Car Chase. In TRex the GPU has a slight lead over the Exynos 8895, but only when the device is cool as it quickly starts throttling down from its maximum frequencies at slightly more elevated temperatures.

GPU Power Efficiency

 

GFXBench Manhattan 3.1 Offscreen Power Efficiency
(System Active Power)
  Mfc. Process FPS Avg. Power
(W)
Perf/W
Efficiency
Galaxy S8 (Snapdragon 835) 10LPE 38.90 3.79 10.26 fps/W
LeEco Le Pro3 (Snapdragon 821) 14LPP 33.04 4.18 7.90 fps/W
Galaxy S7 (Snapdragon 820) 14LPP 30.98 3.98 7.78 fps/W
Huawei Mate 10 (Kirin 970) 10FF 37.66 6.33 5.94 fps/W
Galaxy S8 (Exynos 8895) 10LPE 42.49 7.35 5.78 fps/W
Meizu PRO 5 (Exynos 7420) 14LPE 14.45 3.47 4.16 fps/W
Nexus 6P (Snapdragon 810 v2.1) 20Soc 21.94 5.44 4.03 fps/W
Huawei Mate 8 (Kirin 950) 16FF+ 10.37 2.75 3.77 fps/W
Huawei Mate 9 (Kirin 960) 16FFC 32.49 8.63 3.77 fps/W
Huawei P9 (Kirin 955) 16FF+ 10.59 2.98 3.55 fps/W

In terms of average platform active power consumption, the Mate 10 shows as significant improvement over last year’s Mate 9. In Manhattan we go down from 8.6W to 6.33W. In terms of efficiency at similar peak performance the Kirin 970 managed only slightly outpace the Exynos 8895 and Mali G71. The architectural improvements that the G72 is promised to bring is counter-acted by the fact that the Exynos uses more cores at lower frequencies (and efficient voltages), with both ending up at a similar performance and efficiency point. The same effect applies between the Kirin 960 and 970, but in reverse. Here the addition of more cores at a lower frequency amplifies the process and architectural efficiency gains versus the G71, resulting in an absolute efficiency gain of 57% at peak performance, which comes near to Huawei’s stated claims of 50% efficiency gain. It’s to be noted that the true efficiency gain at same performance points is likely near the 100% mark, meaning for the same peak Kirin 960 performance levels the Kirin 970 and G72 implementation will be nearly double its efficiency.

Whilst this all might sound optimistic in terms of performance and efficiency gains, it’s all rather meaningless as the Mate 10 and Kirin 970 average power drains are still far above sustainable thermal envelopes at 6.3W.

GFXBench T-Rex Offscreen Power Efficiency
(System Active Power)
  Mfc. Process FPS Avg. Power
(W)
Perf/W
Efficiency
Galaxy S8 (Snapdragon 835) 10LPE 108.20 3.45 31.31 fps/W
LeEco Le Pro3 (Snapdragon 821) 14LPP 94.97 3.91 24.26 fps/W
Galaxy S7 (Snapdragon 820) 14LPP 90.59 4.18 21.67 fps/W
Galaxy S8 (Exynos 8895) 10LPE 121.00 5.86 20.65 fps/W
Galaxy S7 (Exynos 8890) 14LPP 87.00 4.70 18.51 fps/W
Huawei Mate 10 (Kirin 970) 10FF 127.25 7.93 16.04 fps/W
Meizu PRO 5 (Exynos 7420) 14LPE 55.67 3.83 14.54 fps/W
Nexus 6P (Snapdragon 810 v2.1) 20Soc 58.97 4.70 12.54 fps/W
Huawei Mate 8 (Kirin 950) 16FF+ 41.69 3.58 11.64 fps/W
Huawei P9 (Kirin 955) 16FF+ 40.42 3.68 10.98 fps/W
Huawei Mate 9 (Kirin 960) 16FFC 99.16 9.51 10.42 fps/W

Again on T-Rex, which is less ALU heavy and more texture, fill-rate and triangle rate bound we see the Kirin 970 reach impressive performance levels at impressively bad power figures. At 7.93W the phone doesn’t seem to be able to sustain the peak frequencies for long as even on a second consecutive run we see performance go down as thermal throttling kicks in. So while the Kirin 970 slightly outpaces the Exynos 8895 in performance it does so at 25% lower efficiency.

Against the Kirin 960 as again the previous paragraph might sound dire, it’s a vast improvement in comparison. So disastrous was the peak power of the Mate 9 that still at 28% higher peak performance, the Mate 10 still manages to be 53% more efficient, again validating Huawei’s marketing claims. At iso-performance again I estimate that the Kirin 970 is likely near twice as efficient over the Kirin 960.

In all this you’ll have probably noticed Qualcomm consistently at the top of the charts. Indeed over the last few generations it seems Qualcomm is the only company which has managed to increase performance by architectural and process node improvements without ever increasing and exploding the power budget. On the contrary, Qualcomm seems to steadily able to lower the average power generation after generation, reaching an extremely impressive 3.5-3.8W on the Snapdragon 835. It’s widely quoted that mobile GPU’s power budget is 1.5-2W, but over the last few years the only high-end GPU able to achieve that seems to be Adreno, and this gap seems to be ever increasing generation after generation.

In my review of the Mate 8 there were a lot of users in the comments section who still deemed the performance of the T880MP4 in the Kirin 950 unsatisfactory and uncompetitive. Unfortunately this view is the common widespread notion among most users and most media, and was one of main complaints of Huawei devices in the past. Today Huawei is able to compete at the top of the benchmarks, but at a rather ghastly hidden cost of efficiency and unsustainable power that is perfectly honest a lot harder to test and to communicate to users.

AnandTech is also partly guilty here; you have to just look at the top of the page: I really shouldn’t have published those performance benchmarks as they’re outright misleading and rewarding the misplaced design decisions made by the silicon vendors. I’m still not sure what to do here and to whom the onus falls onto. As long as vendors keep away from configuring devices with unreachable and unsustainable performance states on 3D workloads and keep within reasonable levels then the whole topic becomes a non-issue. If things don’t improve then we’ll have to have a hard look on how to handle these situations I’m considering simply no longer posting any GPU peak performance figures in device reviews and keeping them in separate more technical SoC pieces such as this one.

Overall I think we’re at a critical point in time for the mobile GPU landscape. Qualcomm currently holds such an enormous lead in performance, density and efficiency that other silicon vendors who rely on IP vendors for their GPUs are in a tight and precarious situation in terms of their ability to offer competitive products. I see this as a key catalyst as to why Apple has stated to planning to abandon Imagination as their GPU IP provider in upcoming SoCs and why Samsung has accelerated efforts to replace Mali and also introduce their in-house S-GPU maybe as early as 2019. Over the course of the next 2 years we’ll be seeing some exciting shake-ups of the SoC GPU space, that’s for sure.

SPEC2006 - The Results An Introduction to Neural Network Processing
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  • GreenReaper - Thursday, January 25, 2018 - link

    If it can do 2160p60 Decode then I'd imagine that of course it can do 2160p30 Decode, just as it can do 1080p60/30 decode. You list the maximum in a category.
  • yhselp - Tuesday, January 23, 2018 - link

    What a wonderful article: a joy to read, thoughtful, and very, very insightful. Thank you, Andrei. Here's to more coverage like that in the future.

    It looks like the K970 could be used in smaller form factors. If Huawei were to make a premium, bezel-less ~ 4.8" 18:9 model power by K970, it would be wonderful - a premium, Android phone about the size of the iPhone SE.

    Even though Samsung and Qualcomm (S820) have custom CPUs, it feels like their designs are much closer to stock ARM than Apple's CPUs. Why are they not making wider designs? Is it a matter of inability or unwillingness?
  • Raqia - Tuesday, January 23, 2018 - link

    Props for a nice article with data rich diagrams filled with interesting metrics as well as the efforts to normalize tests now and into the future w/ LLVM + SPECINT 06. (Adding the units after the numbers in the chart and "avg. watts" to the rightward pointing legend at the bottom would have helped me grok faster...) Phones are far from general purpose compute devices and their CPUs are mainly involved in directing program flow rather than actual computation, so leaning more heavily into memory operations with the larger data sets of SPECINT is a more appropriate CPU test than Geekbench. The main IPC uplift from OoOE comes from the prefetching and execution in parallel of the highest latency load and store operations and a good memory/cache subsystem does wonders for IPC in actual workloads. Qualcomm's Hexagon DSP has

    It would be interesting to see the 810 here, but its CPU figures would presumably blow off the chart. A modem or wifi test would also be interesting (care for a donation toward the aforementioned harness?), but likely a blowout in the good direction for the Qualcomm chipsets.
  • Andrei Frumusanu - Friday, January 26, 2018 - link

    Apologies for the chart labels, I did them in Excel and it doesn't allow for editing the secondary label position (watts after J/spec).

    The Snapdragon 810 devices wouldn't have been able to sustain their peak performance states for SPEC so I didn't even try to run it.

    Unless your donation is >$60k, modem testing is far beyond the reach of AT because of the sheer cost of the equipment needed to do this properly.
  • jbradfor - Wednesday, January 24, 2018 - link

    Andrei, two questions on the Master Lu tests. First, is there a chance you could run it on the 835 GPU as well and compare? Second, do these power number include DRAM power, or are they SoC only? If they do not include DRAM power, any chance you could measure that as well?
  • Andrei Frumusanu - Friday, January 26, 2018 - link

    The Master Lu uses the SNPE framework and currently doesn't have the option to chose computing target on the SoC. The GPU isn't any or much faster than the DSP and is less efficient.

    The power figures are the active power of the whole platform (total power minus idle power) so they include everything.
  • jbradfor - Monday, January 29, 2018 - link

    Thanks. Do you have the capability of measuring just the SoC power separately from the DRAM power?
  • ReturnFire - Wednesday, January 24, 2018 - link

    Great article Andrei. So glad there is new mobile stuff on AT. Fingers crossed for more 2018 flagship / soc articles!
  • KarlKastor - Thursday, January 25, 2018 - link

    "AnandTech is also partly guilty here; you have to just look at the top of the page: I really shouldn’t have published those performance benchmarks as they’re outright misleading and rewarding the misplaced design decisions made by the silicon vendors. I’m still not sure what to do here and to whom the onus falls onto."
    That is pretty easy. Post sustained performace values and not only peak power. Just run the benchmarks ten times in a row, it's not that difficult.
    If in every review sustained performance is shown, the people will realize this theater.

    And it is a big problem. Burst GPU performance is useless. No one plays a game for half a minute.
    Burst CPU performance ist perhaps a different matter. It helps to optimize the overall snappiness.
  • Andrei Frumusanu - Friday, January 26, 2018 - link

    I'm planning to switch to this in future reviews.

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