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An Introduction To Intel's Tremont Microarchitecture

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  • #31
    Originally posted by sandy8925 View Post
    True, but multiple cores are very useful.
    Of course having multiple cores is useful. My point was that single thread performance is still (and will continue to be) very important - that doesn't mean everything else is irrelevant.

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    • #32
      Originally posted by caligula View Post

      Heh, I guess you don't even know what that Law means, do you? The law states the theoretical maximum you can get when the number of cores is huge, like hundreds or thousands. In real world, the core count is typically from 4 to 32. So even the law you refer to tells that you get serious speedups with more cores.
      I guess its you who doesn't know what amdahls law means. In actual fact its a statement that you can't parallelize loads indefinitely. If you take almost any single thread x86 load and try to parallelize it vastly dimimishing returns after 4 threads and 16 threads is the very most that doesnt look retarded.

      Amdahls law is -exactly- why things like gcc are still single threaded. It makes more sense to run many single threads in parallel.

      Amdahls law -is- a good reason why single threaded performance is so important.
      Last edited by duby229; 10-25-2019, 01:13 AM.

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      • #33
        Originally posted by duby229 View Post

        I guess its you who doesn't know what amdahls law means. In actual fact its a statement that you can't parallelize loads indefinitely. If you take almost any single thread x86 load and try to parallelize it vastly dimimishing returns after 4 threads and 16 threads is the very most that doesnt look retarded.

        Amdahls law is -exactly- why things like gcc are still single threaded. It makes more sense to run many single threads in parallel.
        Not necessarily. Many real life workloads are interdependent, so they can't totally operate independently. However, if you can split up the data/computation so that it can be performed independently without depending on the results of computation on another core, then yes you can scale linearly with an increasing number of cores.

        In fact, it's the only situation where GPGPU is useful - if you have too many interdependencies, it's inefficient to run it on GPGPU.

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        • #34
          Originally posted by sandy8925 View Post

          Hm, sounds like it can be applied for GPUs then. After all they have thousands of "cores" that do computations in parallel. In fact, I believe that's why NVIDIA dGPUs perform better on average than AMD dGPUs - better power efficiency that allows them to run at significantly higher clock speeds. Thanks to AMD using 7 nm they're now able to run at higher clock speeds, thus enabling better performance and allowing them to be more competitive with NVIDIA.
          Then I guess it might be surprising to you that AMDs GPUs have many times more execution units than nVidias...

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          • #35
            Originally posted by duby229 View Post

            Then I guess it might be surprising to you that AMDs GPUs have many times more execution units than nVidias...
            No it doesn't surprise me. I said that NVIDIA's performance lead was due to higher clock speeds and not due to higher number of execution units.

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            • #36
              Originally posted by sandy8925 View Post

              No it doesn't surprise me. I said that NVIDIA's performance lead was due to higher clock speeds and not due to higher number of execution units.

              thats not the full story. nVidia's execution units are hella more complex than AMD's and have a much higher IPC. even that's not the full story because nvidia instructions aren't equal to AMD instructions, so IPC as a metric isn't real.
              Last edited by duby229; 10-25-2019, 01:29 AM.

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              • #37
                Originally posted by sandy8925 View Post
                Haha, that's true. The only reason mobile devices work so well is due to heavy limitations and strict enforcement of those limitations - no swap, use a lot of specialized chips for various tasks (video decoding and encoding, GPU, low power sensor hub, special chips for recognizing hotwords like Ok Google , and special camera image processing chips etc.),

                This along with other actions such as killing background apps to reclaim memory, killing/suspending background apps to lower CPU usage and enforcing strict entry points for app execution.
                You're mixing things that are unrelated. The OS does things to save power. The CPU too but one doesn't imply the other.

                Also FYI Apple ARM CPU, yeah the one in phones, beats many current Intel/AMD CPU at running the CPU only benchmark SPEC 2006. Welcome to 21st century.

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                • #38
                  Originally posted by Alex/AT View Post
                  No, we are not talking about ARM
                  Oh. I was misguided by people comparing with ARM, actually

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                  • #39
                    Originally posted by sandy8925 View Post

                    True, but multiple cores are very useful. For example, on my Nexus 6, for some idiotic reason, cores are shut down as battery charge level decreases. So when the battery reaches 75% and less, 2 cores are turned off and only 2 are available. There's a huge drop in performance and responsiveness.

                    It turns out, that multiple cores able to run multiple processes/threads in parallel can significantly boost responsiveness - who knew?
                    It turns out, that Android is extremely bloated with far too many background processes doing nothing useful and needs many cores to be responsive - who knew?

                    Originally posted by sandy8925
                    Actually, it is. When you have multiple cores/processors, you're actually running things in parallel. Not just providing the appearance of running things in parallel. It does make a big difference as far as responsiveness.
                    That's called the RT patchset.

                    Originally posted by sandy8925
                    Haha, that's true. The only reason mobile devices work so well is due to heavy limitations and strict enforcement of those limitations - no swap,
                    Have you heard of zram?

                    use a lot of specialized chips for various tasks (video decoding and encoding, GPU, low power sensor hub, special chips for recognizing hotwords like Ok Google,
                    "That chip over there is the OTG USB controller (with buggy drivers that cause kernel panics), and right next to it is what we call the 'Ok' chip. We plan to put an 'Alexa' chip on next year's version."

                    and special camera image processing chips etc.),

                    This along with other actions such as killing background apps to reclaim memory,
                    Because even the app launcher uses 300MB of RAM.

                    killing/suspending background apps to lower CPU usage
                    But obviously only the ones not sending tracking data to Google.

                    and enforcing strict entry points for app execution.

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                    • #40
                      Originally posted by tildearrow View Post

                      Where is my 4.0GHz ARM processor?!

                      (also, they suck at tasks like compiling and video decoding...)
                      Most ARM processors are not at so high frequencies because they are aimed at mobile devices, but I guess it would be possible to make a 4 GHz ARM processor if it was designed for workstations and servers.

                      I don't know about compiling, but aren't ARM processors really good for video decoding considering all phones and tablets that are used for video decoding with very little power usage?

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