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The powerful marketing is the multi core vs clock speed. Sort of like: buy one get one free (of slower clock speed). I am impressed. (by the effective marketi
by puppetmaster3 11y ago
The powerful marketing is the multi core vs clock speed.
Sort of like: buy one get one free (of slower clock speed).
I am impressed. (by the effective marketing deflecting the importance of clock speed).
- sp332 11y agoThis article give higher clock speeds than the chart on Ars Technica does. http://www.anandtech.com/show/10158/the-intel-xeon-e5-v4-review/8 http://www.anandtech.com/show/10158/the-intel-xeon-e5-v4-rev... The Xeon E5-2699 v4 can run at 2.8 GHz with all cores busy, and is capable of boosting up to 3.6 GHz. But the one on Ars says the E5-2699 v4 is only 2.2 GHz.
- Spooky23 11y agoArs is correct.
- creshal 11y agoClock speeds depend on many things, like thermal limits, power draw, what instructions are used, how many cores are active, whether the integrated GPU is running (for OpenCL) if it's enabled, … 2.2 GHz is guaranteed – without AVX, with you only get 1.8. 2.8 GHz is possible, assuming there are thermal reserves, power consumption is not hitting a limit, etc.
- sp332 11y agoOk, so all cores could run at 2.6 GHz momentarily but it would probably start thermal throttling pretty fast. And maybe not at all if the cores were using power-intensive units.
- JoshTriplett 11y agoThe rated clock speed is what you're guaranteed to get when you run all cores. If you run a subset of cores, you'll get significantly more speed via turbo.
- atemerev 11y agoI'm sorry, but pure single core performance ended circa 2007. This is the end of the road. It is shameful that in 2016 we still don't have, say, parallel rendering in browsers. All hope is for Servo.
- Silhouette 11y agoThat seems unrealistic. Single core performance still matters for algorithms that can't be efficiently parallelised. Moreover, writing efficient, parallel versions of a lot of algorithms is hard, and often introduces significant overheads of its own that must be outweighed by the better scalability that the parallelisation brings.
- jakub_h 11y ago> Single core performance still matters for algorithms that can't be efficiently parallelised. Any real world examples? Especially considering that at this point, sacrificing cores to boost the remaining ones seems to be a really bad deal with current silicon. Core power requirements appear to decrease faster than their actual computational speed does if you go low-power. Even if you lose 40% of performance due to overhead, if the same-TDP CPU package is twice as fast with more cores, you still win. (And who's to say that your implementation can't be improved in the future?)
- Silhouette 11y agoI honestly don't know how to answer that. Are you suggesting that you know how to parallelise an arbitrary expensive algorithm? Because if you've beaten Amdahl's law, a lot of people would like to make you very, very rich.
- jakub_h 11y agoSounds like an ambiguous question. Most algorithms are "arbitrarily expensive". It generally depends on some measure of the data you're putting in. But in case you mean "an arbitrary algorithm", then no, nobody knows how to do that. But it appears that the most useful things people actually want to do lie somewhere in the middle: not trivial to parallelize but also not exactly impossible.
- merb 11y agoclock speed is the last thing you should watch on a processor. There are some other factors which boosts the performance incredible. Like the L1-L3 Caches And on servers you prolly watch out the TDP, too. Also clock-speed doesn't mean a processor is slower, there are processors with a slower clock speed and still have a higher IPS.