GPU Performance & Power: Very, Very Hot

Moving onto the GPU side of things, I was very intrigued coming into this comparison, as both Qualcomm as well as Samsung LSI had made promises of enormous performance upgrades in the range of 35% and 40% respectively. We didn’t exactly know how Qualcomm achieved these performance gains given this year’s rather opaquer reveal of the Snapdragon 888. On the Exynos side, I was immediately dubious about Samsung’s 40% claim given that the new Mali-G78 was only meant to be a small generational performance and efficiency boost, as well as the process node having only a 20% power efficiency gain, however the Exynos 990 was in a bad position so maybe it was possible to achieve. Given a lack of large architectural as well as process node improvements, the large performance improvements must thus come from large power increases.

Basemark GPU 1.2 - Medium 1440p - Off-Screen / Blit

Starting off with Basemark GPU, we’re off to a mixed start. Both the Snapdragon 888 and Exynos 2100 notably outperform their predecessors in terms of peak performance, however their sustained performances on the Galaxy S21 Ultra isn’t too great.

The Exynos 2100 improves dramatically over the Exynos 990 in this regard, however the Snapdragon 888 S21 barely budges the needle against its predecessor, posting roughly the same sustained performance figures as any other Snapdragon 865 device such as the S20 Ultra.

GFXBench Aztec Ruins - High - Vulkan/Metal - Off-screen

In GFXBench Aztec High, we see a similar story, where peak performance of both phones is much greater than before, however it quickly throttles onto mediocre figures. Again, these are still great improvements for the Exynos, but not so great figures for the Snapdragon 888 S21 Ultra, as it’s posting worse figures than the Note20 Ultra with the Snapdragon 865+.

GFXBench Aztec High Offscreen Power Efficiency
(System Active Power)
  Mfc. Process FPS Avg. Power
iPhone 12 Pro (A14) 🔥 Throttled N5 28.36 3.91 7.24
Mate 40 Pro (Kirin 9000) 🔋 Power-Save N5 23.71 3.35 7.07
iPhone 11 Pro (A13) 🔥 Throttled N7P 26.14 3.83 6.82
Galaxy S21U (Snapdragon 888) 🔥 Throttled 5LPE 18.94 2.81 6.71
iPhone 12 Pro (A14) ❄️ Peak N5 37.40 5.57 6.64
iPhone 11 Pro (A13) ❄️ Peak N7P 34.00 6.21 5.47
Galaxy S20U (Snapdragon 865) N7P 20.35 3.91 5.19
Mate 40 Pro (Kirin 9000) 🔥 Throttled N5 27.37 5.39 5.07
iPhone XS (A12) 🔥 Throttled N7 19.32 3.81 5.07
Reno3 5G (Dimensity 1000L) N7 11.93 2.39 4.99
Galaxy S21U (Exynos 2100) 🔥 Throttled 5LPE 18.55 3.73 4.96
iPhone XS (A12) ❄️ Peak N7 26.59 5.56 4.78
Mate 40 Pro (Kirin 9000) ❄️ Peak N5 37.22 8.53 4.36
ROG Phone III (Snapdragon 865+) N7P 22.34 5.35 4.17
Mate 30 Pro (Kirin 990 4G) N7 16.50 3.96 4.16
Galaxy S21U (Snapdragon 888) ❄️ Peak 5LPE 29.82 8.10 3.68
Galaxy S21U (Exynos 2100) ❄️ Peak 5LPE 28.04 7.69 3.64
Galaxy S20+ (Exynos 990) 7LPP 20.20 5.02 3.59
Galaxy S10+ (Snapdragon 855) N7 16.17 4.69 3.44
Galaxy S10+ (Exynos 9820) 8LPP 15.59 4.80 3.24

In terms of power and power efficiency, red alert, red alert!

Both the Exynos 2100 and Snapdragon 888 are showcasing outrageous peak power figures around 8W, which are figures that are simply impossible to sustain or dissipate in a phone.

We can see that both chips are way beyond their predecessors points in the frequency/voltages curves as the power efficiency is either outright flat, for the Exynos, or worse than their predecessors, like the Snapdragon – meaning both chips are using exponentially more power to try to drive more performance.

The phones quickly throttle down to below 4W – and fluctuate lower or higher depending on your environmental conditions. I was able to get power measurements for the Exynos around the 4W range (though it throttles down to below that), however for the Snapdragon this wasn’t possible as the phone’s thermal management had a very binomial behaviour of either settling at 3W power or ramping up to 6W, with very little inbetween.

Still, at these different power measurement points, we coincidentally ended up with similar performance – with the Snapdragon 888 here taking the lead in efficiency by 35%.

GFXBench Aztec Ruins - Normal - Vulkan/Metal - Off-screen

The 1080p variant of Aztec largely looks the same in terms of ranking, with the Exynos 2100 posting a good generational upgrade in sustained performance, while the Snapdragon 888 shows smaller gains.

GFXBench Aztec Normal Offscreen Power Efficiency
(System Active Power)
  Mfc. Process FPS Avg. Power
iPhone 12 Pro (A14) 🔥 Throttled N5 77.44 3.88 19.95
iPhone 12 Pro (A14) ❄️ Peak N5 102.24 5.53 18.48
iPhone 11 Pro (A13) 🔥 Throttled N7P 73.27 4.07 18.00
Galaxy S21U (Snapdragon 888) 🔥 Throttled 5LPE 51.81 2.93 17.67
Mate 40 Pro (Kirin 9000) 🔋 Power-Save N5 53.49 3.10 17.25
iPhone 11 Pro (A13) ❄️ Peak N7P 91.62 6.08 15.06
iPhone XS (A12) 🔥 Throttled N7 55.70 3.88 14.35
Galaxy S20U (Snapdragon 865) N7P 54.09 3.91 13.75
iPhone XS (A12) ❄️Peak N7 76.00 5.59 13.59
Reno3 5G (Dimensity 1000L) N7 27.84 2.12 13.13
Galaxy S21U (Exynos 2100) 🔥 Throttled 5LPE 46.29 3.85 12.02
Mate 40 Pro (Kirin 9000) 🔥 Throttled N5 63.56 5.37 11.84
ROG Phone III (Snapdragon 865+) N7P 58.77 5.34 11.00
Mate 40 Pro (Kirin 9000) ❄️ Peak N5 82.74 7.95 10.40
Mate 30 Pro (Kirin 990 4G) N7 41.68 4.01 10.39
Galaxy S20+ (Exynos 990) 7LPP 49.41 4.87 10.14
Galaxy S10+ (Snapdragon 855) N7 40.63 4.14 9.81
Galaxy S21U (Snapdragon 888) ❄️ Peak 5LPE 81.77 8.40 9.73
Galaxy S21U (Exynos 2100) ❄️ Peak 5LPE 71.53 8.10 8.83
Galaxy S10+ (Exynos 9820) 8LPP 40.18 4.62 8.69

In terms of power, here’s it’s even higher, with the Snapdragon doing one run at 8.4W of power.

Throttling down, the Snapdragon 888 takes the lead in terms of efficiency as seemingly it has a differently shaped power curve and benefits more at lower frequencies.

GFXBench Manhattan 3.1 Off-screen

Same story in Manhattan – good upgrades for the Exynos 2100 – although still not very competitive, while the Snapdragon 888 is flat against most other Snapdragon 865 phones.

GFXBench Manhattan 3.1 Offscreen Power Efficiency
(System Active Power)
  Mfc. Process FPS Avg. Power
iPhone 12 Pro (A14) 🔥 Throttled N5 103.11 3.90 26.43
Galaxy S21U (Snapdragon 888) 🔥 Throttled 5LPE 75.62 2.91 25.98
iPhone 12 Pro (A14) ❄️ Peak N5 137.72 5.63 24.46
iPhone 11 Pro (A13) 🔥 Throttled N7P 100.58 4.21 23.89
Mate 40 Pro (Kirin 9000) 🔋 Power-Save N5 95.01 4.35 21.83
Galaxy S20U (Snapdragon 865) N7P 88.93 4.20 21.15
iPhone 11 Pro (A13) ❄️Peak N7P 123.54 6.04 20.45
iPhone XS (A12) 🔥 Throttled N7 76.51 3.79 20.18
Reno3 5G (Dimensity 1000L) N7 55.48 2.98 18.61
Galaxy S21U (Exynos 2100) 🔥 Throttled 5LPE 72.66 4.04 17.98
Mate 40 Pro (Kirin 9000) 🔥 Throttled N5 87.31 4.98 17.54
iPhone XS (A12) ❄️Peak N7 103.83 5.98 17.36
ROG Phone III (Snapdragon 865+) N7P 93.58 5.56 16.82
Galaxy S21U (Exynos 2100) ❄️ Peak 5LPE 115.20 7.62 15.11
Mate 40 Pro (Kirin 9000) ❄️Peak N5 124.69 8.28 15.05
Mate 30 Pro (Kirin 990 4G) N7 75.69 5.04 15.01
Galaxy S20+ (Exynos 990) 7LPP 85.66 5.90 14.51
Galaxy S10+ (Snapdragon 855) N7 70.67 4.88 14.46
Galaxy S21U (Snapdragon 888) ❄️ Peak 5LPE 120.32 8.34 14.42
Galaxy S10+ (Exynos 9820) 8LPP 68.87 5.10 13.48
Galaxy S9+ (Snapdragon 845) 10LPP 61.16 5.01 11.99
Mate 20 Pro (Kirin 980) N7 54.54 4.57 11.93
Galaxy S9 (Exynos 9810) 10LPP 46.04 4.08 11.28
Galaxy S8 (Snapdragon 835) 10LPE 38.90 3.79 10.26
Galaxy S8 (Exynos 8895) 10LPE 42.49 7.35 5.78

In terms of power and efficiency, at peak performance the Snapdragon 888 here actually seems to be fare off worse: it’s posting slightly more FPS, however It’s also higher power, reaching up to 8.34W.

Throttling down again shows that the Snapdragon has a steeper power curve and becomes more efficient at lower frequency points. The throttled states of both phones post nearly the same performance, but the Snapdragon does it at 28% lower power.

GFXBench T-Rex 2.7 Off-screen

GFXBench T-Rex Offscreen Power Efficiency
(System Active Power)
  Mfc. Process FPS Avg. Power
iPhone 12 Pro (A14) 🔥 Throttled N5 260.28 4.08 63.97
Galaxy S21U (Snapdragon 888) 🔥 Throttled 5LPE 172.67 2.70 63.74
iPhone 11 Pro (A13) 🔥 Throttled N7P 289.03 4.78 60.46
iPhone 12 Pro (A14) ❄️ Peak N5 328.50 5.55 59.18
iPhone 11 Pro (A13) ❄️ Peak N7P 328.90 5.93 55.46
Galaxy S20U (Snapdragon 865) N7P 205.37 3.83 53.30
Mate 40 Pro (Kirin 9000) 🔥 Throttled N5 147.13 2.92 50.38
iPhone XS (A12) 🔥 Throttled N7 197.80 3.95 50.07
Mate 40 Pro (Kirin 9000) 🔋 Power-Save N5 201.85 4.10 49.22
ROG Phone III (Snapdragon 865+) N7P 224.48 4.92 45.60
iPhone XS (A12) ❄️Peak N7 271.86 6.10 44.56
Galaxy 10+ (Snapdragon 855) N7 167.16 4.10 40.70
Galaxy S21U (Exynos 2100) 🔥 Throttled 5LPE 153.28 3.80 40.30
Reno3 5G (Dimensity 1000L) N7 139.30 3.57 39.01
Mate 40 Pro (Kirin 9000) ❄️ Peak N5 235.04 6.11 38.46
Galaxy S20+ (Exynos 990) 7LPP 199.61 5.63 35.45
Mate 30 Pro  (Kirin 990 4G) N7 152.27 4.34 35.08
Galaxy S21U (Snapdragon 888) ❄️ Peak 5LPE 279.39 7.98 35.01
Galaxy S9+ (Snapdragon 845) 10LPP 150.40 4.42 34.00
Galaxy 10+ (Exynos 9820) 8LPP 166.00 4.96 33.40
Galaxy S9 (Exynos 9810) 10LPP 141.91 4.34 32.67
Galaxy S8 (Snapdragon 835) 10LPE 108.20 3.45 31.31
Galaxy S21U (Exynos 2100) ❄️ Peak 5LPE 237.71 8.02 29.61
Mate 20 Pro (Kirin 980) N7 135.75 4.64 29.25
Galaxy S8 (Exynos 8895) 10LPE 121.00 5.86 20.65

Finally, in T-Rex, the Snapdragon takes a more significant lead in peak performance at the same power, while when throttled down, the Adreno GPU showcases a +50% advantage in perf/W.

Much Too Hot to Handle

I’ll be quite frank with the results of these new SoCs: they’re terrible. Much like smartphone vendors have for years now copied the worst aspects of Apple’s devices, such a dropping headphone jacks and dropping chargers, the SoC vendors this year have now also copied the worst aspect of Apple’s SoCs: extremely high GPU peak power states.

When I tested the Kirin 9000 a few months ago in the Mate 40 Pro I thought that HiSilicon’s choice of turbocharging their massive GPU up to peak power figures of 8W was a very bad choice, but now Qualcomm and Samsung LSI followed up doing the exactly same thing, as if this was a race to the bottom as to who can create the hottest GPU in the market.

As to why the SoC vendors are doing this, it’s very easy to look at the benchmark charts and see the marketing pressure that Apple applies on the rest of the industry, being far ahead of the pack in terms of performance and efficiency. I wouldn’t be surprised if this generation of SoCs have had design decisions impacted by the marketing departments.

Inside devices such as the Galaxy S21 Ultra today – these peak performance states are utterly pointless as they are just impossible to maintain for any reasonable amount of time, as the thermal envelope of the phones really aren’t any different to that of any other device of this form-factor, including the predecessor S20 Ultra.

The Snapdragon 888’s peak performance state is pretty absurd, as at its 840MHz GPU frequency I’ve measured average power of around 11W. This state can’t be maintained for longer than a few seconds before it throttles down to 778 and 738MHz at 9-8W for the rest of the duration of a test on a cold device, before further limiting down due to thermals during prolonged periods. In terms of sustained performance, the S21U’s advantages over the S20U is in the 5-20% range, depending on workload, well below Qualcomm’s proclaimed 35% performance boost. That margin here actually is even smaller against the Snapdragon 865+ Galaxy Note20 Ultra.

I asked Qualcomm to rationalise these high-wattage peak performance points, and the official response was that these were enabled in order to give a higher level of flexibility in terms of higher power gaming phones and higher thermal envelope devices which are able to sustain greater power levels. I know that at least Xiaomi’s Mi 11 will be more aggressive than the S21 Ultra in terms of sustained power levels, at a cost of higher device temperatures. As for gaming phones – the last few generation of those devices have shown little actual physical design differentiation to actually enable higher thermal envelopes, with most of their advantages simply being that they are allowed to get hotter, showing no advantage over “regular” phones which do the same (OnePlus devices, ZenFone 7 Pro for example). The S21 Ultra here has peak skin temperatures of around 46°C with long-term throttling at around 42°C.

For the Exynos 2100 – Samsung LSI’s claim of a 40% performance boost is more credible as this not only refers to the peak performance figures, but can actually also be applied to the sustained performance figures of the phone. It’s actually a tangible and very large upgrade to the Exynos 990 last year, however it needs to be put into context. The peak power figures here have the same negative connotations as on the Snapdragon unit so I won’t repeat myself in that aspect.

In terms of sustained performance, although the Exynos 2100 is a large generational upgrade, it still falls below that of last-generation Snapdragon 865 devices, and naturally also the newer Snapdragon 888. The benchmark figures here also pretty much correspond to the real-world gaming performance of the phones – the Exynos S21 Ultra fared not only worse than the Snapdragon S21 Ultra, but also worse than a Snapdragon S20 Ultra or Note20 Ultra.

The interesting data here is the comparison to Huawei’s Mate 40 Pro with the Kirin 9000 and its gargantuan Mali-G78MP24 GPU – 10 more cores than the Exynos 2100’s configuration. Putting the Mate 40 Pro into power-saving mode will actually cap the maximum GPU frequency and give you reasonable power consumption figures around 4W, which are comparable to what the Exynos 2100 in the S21 Ultra throttles at. We can see that the Kirin’s performance is either superior, lower power, or both, signifying the chip is being notably more efficient than the Exynos 2100. The larger GPU as well as the superior TSMC 5nm node come at play here.

Samsung LSI’s confirmation that they’ll be deploying AMD’s RDNA-based GPU for next-generation flagship SoCs will hopefully mean that the Exynos’ competitive positioning will be quite different next year; however, we shouldn’t expect miracles as the process node differences to Apple’s GPUs will likely still linger on.

Unfortunately, Samsung’s (the mobile division) battery saving mode on the Galaxy S21 doesn’t affect the GPU frequencies at all, unlike Huawei’s PSM, so it doesn’t help at all for the power envelopes or efficiency. I would highly recommend them to introduce such a mechanism here as having burning hot phones really isn’t a great experience while gaming, and the performance will regress to those sustained levels anyhow.

Generally, I see this generation as quite the disappointment when it comes to GPU advancements. Qualcomm likely suffered an efficiency set-back and minor improvements due to the process node shift, and while Samsung LSI has achieved good generational advancements, the Exynos still clearly falls behind due to architectural GPU disadvantages.

Mixed-Usage Power & Preliminary Battery Life Conclusion & End Remarks


View All Comments

  • mohamad.zand - Thursday, June 17, 2021 - link

    Hi , thank you for your explanation
    Do you know how many transistors Snapdragon 888 and Exynos 2100 are?
    It is not written anywhere
  • Spunjji - Thursday, February 11, 2021 - link

    I'm not an expert by any means, but I think Samsung's biggest problem was always optimisation - they use lots of die area for computing resources but the memory interfaces aren't optimised well enough to feed the beast, and they kept trying to push clocks higher to compensate.

    The handy car analogy would be:
    Samsung - Dodge Viper. More cubes! More noise! More fuel! Grrr.
    Qualcomm / ARM - Honda Civic. Gets you there. Efficient and compact.
    Apple - Bugatti Veyron. Big engine, but well-engineered. Everything absolutely *sings*.
  • Shorty_ - Monday, February 15, 2021 - link

    you're right but you also don't really touch why Apple can do that and X86 designs can't. The issue is that uOP decoding on x86 is *awfully* slow and inefficient on power.

    This was explained to me as follows:

    Variable-length instructions are an utter nightmare to work with. I'll try to explain with regular words how a decoder handles variable length. Here's all the instructions coming in:

    x86: addmatrixdogchewspout
    ARM: dogcatputnetgotfin

    Now, ARM is fixed length (3-letters only), so if I'm decoding them, I just add a space between every 3 letters.
    ARM: dogcatputnetgotfin
    ARM decoded: dog cat put net got fin

    done. Now I can re-order them in a huge buffer, avoid dependencies, and fill my execution ports on the backend.

    x86 is variable length, This means I cannot reliably figure out where the spaces should go. so I have to try all of them and then throw out what doesn't work.
    Look at how much more work there is to do.

    x86: addmatrixdogchewspoutreading frame 1 (n=3): addmatrixdogchewspout
    Partially decoded ops: add, , dog, , ,
    reading frame 2 (n=4): matrixchewspout
    Partially decoded ops: add, ,dog, chew, ,
    reading frame 3 (n=5): matrixspout
    Partially decoded ops: add, ,dog, chew, spout,
    reading frame 4 (n=6): matrix
    Partially decoded ops: add, matrix, dog, chew, spout,
    Fully Expanded Micro Ops: add, ma1, ma2, ma3, ma4, dog, ch1, ch2, ch3, sp1, sp2, sp3

    This is why most x86 cores only have a 3-4 wide frontend. Those decoders are massive, and extremely energy intensive. They cost a decent bit of transistor budget and a lot of thermal budget even at idle. And they have to process all the different lengths and then unpack them, like I showed above with "regular" words. They have excellent throughput because they expand instructions into a ton of micro-ops... BUT that expansion is inconsistent, and hilariously inefficient.

    This is why x86/64 cores require SMT for the best overall throughput -- the timing differences create plenty of room for other stuff to be executed while waiting on large instructions to expand. And with this example... we only stepped up to 6-byte instructions. x86 is 1-15 bytes so imagine how much longer the example would have been.

    Apple doesn't bother with SMT on their ARM core design, and instead goes for a massive reorder buffer, and only presents a single logical core to the programmer, because their 8-wide design can efficiently unpack instructions, and fit them in a massive 630μop reorder buffer, and fill the backend easily achieving high occupancy, even at low clock speeds. Effectively, a reorder buffer, if it's big enough, is better than SMT, because SMT requires programmer awareness / programmer effort, and not everything is parallelizable.
  • Karim Braija - Saturday, February 20, 2021 - link

    Je suis pas sur si le benchmark SPENCint2006 est vraiment fiable, en plus je pense que ça fait longtemps que ce benchmark est là depuis un moment et je pense qu'il n'a plus bonne fiabilité, ce sont de nouveaux processeurs puissant. Donc je pense que ce n'est pas très fiable et qu'il ne dit pas des choses précises. Je pense que faut pas que vous croyez ce benchmark à 100%. Reply
  • serendip - Monday, February 8, 2021 - link

    "Looking at all these results, it suddenly makes sense as to why Qualcomm launched another bin/refresh of the Snapdragon 865 in the form of the Snapdragon 870."

    So this means Qualcomm is hedging its bets by having two flagship chips on separate TSMC and Samsung processes? Hopefully the situation will improve once X1 cores get built on TSMC 5nm and there's more experience with integrating X1 + A78. All this also makes SD888 phones a bit pointless if you already have an SD865 device.
  • Bluetooth - Monday, February 8, 2021 - link

    Why would they skimp on the cache. Was neural engine or something else with higher priority getting silicon? Reply
  • Kangal - Tuesday, February 9, 2021 - link

    I think Samsung was rushing, and its usually easier to stamp out something that's smaller (cache takes alot of silicon estate). Why they rushed was due to a switch from their M-cores to the X-core, and also internalising the 5G-radio.

    Here's the weird part, I actually think this time their Mongoose Cores would be competitive. Unlike Andrei, I estimated the Cortex-X1 was going to be a load of crap, and seems I was right. Having node parity with Qualcomm, the immature implementation that is the X1, and the further refined Mongoose core... it would've meant they would be quite competitive (better/same/worse) but that's not saying much after looking at Apple.

    How do I figure?
    The Mongoose core was a Cortex A57 alternative which was competitive against Cortex A72 cores. So it started as midcore (Cortex A72) and evolved into a highcore implementation as early as 2019 with the S9 when they began to get really wide, really fast, really hot/thirsty. Those are great for a Large Tablet or Ultrabook, but not good properties for a smaller handheld.

    There was a precedence for this, in the overclocked QSD 845 SoCs, 855+, and the subpar QSD 865 implementation. Heck, it goes all the way back to 2016 when MediaTek was designing 2+4+4 core chipsets (and they failed miserably as you would imagine). I think when consumers buy these, companies send orders, fabs design them, etc... they always forget about the software. This is what separates Apple from Qualcomm, and Qualcomm from the rest. You can either brute-force your way to the top, or try to do things more cost/thermal efficiently.
  • Andrei Frumusanu - Tuesday, February 9, 2021 - link

    > Unlike Andrei, I estimated the Cortex-X1 was going to be a load of crap, and seems I was right.

    The X1 *is* great, and far better than Samsung's custom cores.
  • Kangal - Wednesday, February 10, 2021 - link

    First of all, apologies for sounding crass.
    Also, you're a professional in this field, I'm merely an enthusiast (aka Armchair Expert) take what I say with a grain of salt. So if you correct me, I stand corrected.

    Nevertheless, I'm very unimpressed by big cores: Mongoose M5, to a lesser extent the Cortex-X1, and to a much Much much lesser extent the Firestorm. I do not think the X1 is great. Remember, the "middle cores" still haven't hit their limits, so it makes little sense to go even thirstier/hotter. Even if the power and thermal issues weren't so dire with these big-cores, the performance difference between the middle cores vs big cores is negligible, also there is no applications that are optimised/demand the big cores. Apple's big-core implementation is much more optimised, they're smarter about thermals, and the performance delta between it and the middle-cores is substantial, hence why their implementation works and why it favours compared to the X1/M5.

    I can see a future for big-cores. Yet, I think it might involve killing the little-cores (A53/A55), and replacing it with a general purpose cores that will be almost as efficient yet be able to perform much better to act as middle-cores. Otherwise latency is always going to be an issue when shifting work from one core to another then another. I suspect the Cortex-X2 will right many wrongs of the X1, combined with a node jump, it should hopefully be a solid platform. Maybe similar to the 20nm-Cortex A57 versus the 16nm-Cortex A72 evolution we saw back in 2016. The vendors have little freedom when it comes to implementing the X1 cores, and I suspect things will ease up for X2, which could mean operating at reasonable levels.

    So even with the current (and future) drawbacks of big-cores, I think they could be a good addition for several reasons: application-specific optimisations, external dock. We might get a DeX implementation that's native to Android/AOSP, and combined that with an external dock that provides higher power delivery AND adequate active-cooling. I can see that as a boon for content creators and entertainment consumers alike. My eye is on emulation performance, perhaps this brute-force can help stabilise the weak Switch and PS2 emulation currently on Android (WiiU next?).
  • iphonebestgamephone - Monday, February 15, 2021 - link

    The improvement with the 888 in damonps2 and eggns are quite good. Check some vids on youtube. Reply

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