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It makes zero sense to compare like this. Geekbench is closed source. So, there is no way of knowing what they're even running on ARM v/s x86. But, no way is my
by aloknnikhil 7y ago
It makes zero sense to compare like this. Geekbench is closed source. So, there is no way of knowing what they're even running on ARM v/s x86. But, no way is my MacBook Pro slower than my iPad Pro
This Geekbench comparison, on the other hand, tells me they're on par (both single and multi-core scores)
https://browser.geekbench.com/v5/cpu/compare/140913?baseline=201758 https://browser.geekbench.com/v5/cpu/compare/140913?baseline...
I'd take this claim with a massive boulder of salt, if you consider it at all that is.
- coldtea 7y agoWell, memory aside (the iPad Pro having less) and perhaps SSD performance, how is the iPad Pro slower? What have you tried? It can run at least some code (the Geekbench) equally well. So what other programs could it run equally well?
- aloknnikhil 7y agoVideo encoding. The iPad pro is significantly slower at encoding 4k video compared to my MacBook Pro.
- deleted 7y ago[deleted]
- holstvoogd 7y agoThat makes sense, you're MBP has a pretty decent GPU to do that.
- Youden 7y agoThe quality of the GPU usually has no impact on video encoding. At best, you can use a hardware encoder that happens to come with the GPU but usually you won't want that because it comes with a compression hit compared to software.
- gambiting 7y agoIt looks like you're getting downvoted and I'm not sure why - most encoding that I do is CPU-only, GPU encoding only works for a very limited set of codecs at a limited range of presets. If you need to encode anything other than those presets CPU it is.
- ttkari 7y agoDoes this compression hit you mention also apply to encoders that use for example CUDA on Nvidia GPUs? With these there definitely are significant differences in encoding speed between different GPUs.
- Youden 7y agoThere's no reason that using CUDA inherently leads to inferior compression but I'm not aware of a CUDA-accelerated encoder that's any good relative to a pure software encoder (or even NVENC, the pure hardware encoder on an NVIDIA GPU).
- FullyFunctional 7y agoWell, it's not that simple. The CUDA model has a inherent penalty for divergent thread behavior, that is, when all threads do the same, peak performance is attained. If they all follow a different path, the result can be disastrous. The relevance to media encoding is that the higher profiles do a lot of data dependent special casing. It's no accident that the earliest CUDA Video codecs only handled the base profile. This also hurts a CPU implementation but much less.
- lostlogin 7y agoHow does a user distinguish between that being due to software versus hardware?
- aloknnikhil 7y agoHow does that matter for this comparison? The claim is that the iPad pro is as fast as the Macbook Pro. If the hardware encoder is slower than a Macbook Pro software encoder and the iPad pro is as fast as the Macbook Pro, then by that corollary, the Macbook Pro's software encoder should perform faster than its hardware encoder. Surely Apple wouldn't add a slower hardware offload and use that?
- ubercow13 7y agoWouldn’t that be hardware accelerated on the iPad? What iOS app is doing software video encoding?
- jasonvorhe 7y agoThat's because of throttling though. Your MacBook Pro has fan(s), the iPad doesn't. I'm pretty sure the iPad Pro SoC in a MacBook Pro case would be at least on par with the latest Intel-specced MBP
- rubbingalcohol 7y agoBased on what evidence? A single core Geekbench run?
- aloknnikhil 7y agoThe iPad, magically, performs well in Geekbench but has throttling issues in a real world task? I find that hard to believe.
- saurik 7y agoAs someone who has literally been running thermal tests against a random Android device for days (note: not as an expert in hardware, but as someone writing software that is causing the device to overheat), analyzing at all of the temperature sensor and power regulator debug information in spreadsheets while varying the workload, it isn't even remotely surprising to me that pegging a single core (which was the point of this benchmark) might not generate enough heat to cause thermal throttling but running a multi-threaded multi-core workload might.
- aloknnikhil 7y agoOh, I'm not talking about single core scores. I'm talking about multi-core scores. The comparison link in my original comment is claiming similar multi core scores.
- zamadatix 7y agoARM SIMD is only 128 bit isn't it? Would eat pretty heavily on video encoding speed.
- gvhst 7y agoIsn’t video encoding a multi-threaded workload?
- aloknnikhil 7y agoYes. And the Geekbench comparison I linked to in my comment claims the multi-core scores are also similar.
- blablabla123 7y agoProcessor aren't getting that faster - per core - anymore because of miniaturization limits. I think comparing old MacBooks with new ones, most performance gains just came from additional cores/hyperthreads. (Before around 2014 it was really common to have just one thread per core.) Also there is little reason to put in cheap processors into iPads, people use it for games, so there must be a lot of performance. > It makes zero sense to compare like this. Geekbench is closed source. But probably there are remarkable differences in Integer vs. Floating point performance or Hardware acceleration. I assume iPad/iPhone have good HW acceleration for anything video/crypto/3D/...
- aloknnikhil 7y ago> But probably there are remarkable differences in Integer vs. Floating point performance or Hardware acceleration. I assume iPad/iPhone have good HW acceleration for anything video/crypto/3D Processor are definitely stalling in IPC (Instructions Per Cycle) improvements. But I don't think it's fair to call the A13 the fastest chip ever in an Apple device based on heavily hardware accelerated tasks. That's like saying an ASIC is faster than an AMD/Intel. Of course the ASIC will perform faster in certain tasks since they're purpose built for that. But the AMD/Intel are general purpose processors that are meant to do anything. The iPad most definitely has crypto/video/image processing hardware offloads and those are as fast as an Intel. But if I run a workload that makes extensive use of AVX (Instructions for processing Vectorized data), the Intel processors will blow the Apple A13 out of the water. The point here is, these kinds of click-baity tweets are the ones that end up on articles and reach the general public. It's irresponsible.
- GeekyBear 7y ago>there is no way of knowing what they're even running on ARM v/s x86 They run the same workload compiled with Clang for each platform, as described in a PDF on their website. https://www.geekbench.com/doc/geekbench5-cpu-workloads.pdf https://www.geekbench.com/doc/geekbench5-cpu-workloads.pdf
- aloknnikhil 7y agoThanks. It's still lacking information on what specific compiler flags were used. Was the compiler running with -mavx turned on? Probably not (Considering there's a single Geekbench binary distributed for all generations of Macbook Pros). Xcode on the other hand, compiles a binary that's optimized for each target device. So, again, not really that informative on what optimizations were applied to the binary and what instruction sets were optimized for.