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Multi-Core Scaling Performance Of AMD's Bulldozer
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Good article. You did a great job of showing the difference between 8 semi-real cores vs. hyperthreading.
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Originally posted by elanthis View PostYou don't generally _want_ data to be shared betweens threads. That would just mean your threading architecture is all wrong and being hamstrung by data dependencies/locking.
Shared caches save money. They don't improve speed. (generally speaking, of course)
And both AMD's 6-core and Intel's 2600 (Edit: the 2630qm has hyperthreading, so it probably works as substitute) are really missing here for the full picture.Last edited by AnonymousCoward; 26 October 2011, 07:07 AM.
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Yes, it may be better sollution to have larger shared cache than smaller dedicated cache per core (because having "larger" dedicated cache per core is more expensive), but I thought we are talking about Bulldozer in the state as it is and which cores are better to be left enabled. Hope I cleared it up.Last edited by ifkopifko; 26 October 2011, 05:25 AM.
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Originally posted by ifkopifko View Post2RealNC> It is not the case with BD modules. No matter if one per module or two per module, all of them share the whole L3 cache. If one core per module is activated, it has 2MB L2, which it would have to share with the other core otherwise.
In my thinking, it seems better to have a larger, shared cache rather than multiple smaller, non-shared ones.
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Hello.
Very nice test suite, but I would propose some changes:
1) To judge the efficiency of scaling per architekture, functions like Turbo should be disabled. When enabled it is only natural that the scaling with more threads gets lower.
2) I would change the graphs so that they are easier to interpret by the looks (so that linear scaling would look linear). For example, the x-axis should be linear if the y-axis is linear. Not like you have it now, with 1 to 2 distance being the same as 2 to 4 distance. It just looks weird.
2RealNC> It is not the case with BD modules. No matter if one per module or two per module, all of them share the whole L3 cache. If one core per module is activated, it has 2MB L2, which it would have to share with the other core otherwise.
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Originally posted by elanthis View PostYou don't generally _want_ data to be shared betweens threads. That would just mean your threading architecture is all wrong and being hamstrung by data dependencies/locking.
Shared caches save money. They don't improve speed. (generally speaking, of course)
But of course that view comes from someone who doesn't know the details behind CPU cache memory :-P
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Originally posted by smitty3268 View Postrather than separately 1 per module.
That might allow them to share cached data more efficiently between threads?
Shared caches save money. They don't improve speed. (generally speaking, of course)
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I think it may have also been interested to enable the cores together in modules
rather than separately 1 per module.
That might allow them to share cached data more efficiently between threads?
And I think at lower core counts it could enable more aggressive turbo frequencies.
But this was an interesting test as well.
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Multi-Core Scaling Performance Of AMD's Bulldozer
Phoronix: Multi-Core Scaling Performance Of AMD's Bulldozer
There has been a lot of discussion in the past two weeks concerning AMD's new FX-Series processors and the Bulldozer architecture. In particular, with the Bulldozer architecture consisting of "modules" in which each has two x86 engines, but share much of the rest of the processing pipeline with their sibling engine; as such, the AMD FX-8150 eight-core CPU only has four modules. In this article is a look at how well the Bulldozer multi-core performance scales when toggling these different modules. The multi-core scaling performance is compared to AMD's Shanghai, Intel's Gulftown and Sandy Bridge processors.
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