? (0xe2.0x9a.0x9b@gmail.com) on 3/20/10 wrote:
---------------------------
>Vincent Diepeveen (diep@xs4all.nl) on 3/17/10 wrote:
>---------------------------
>>David Kanter (dkanter@realworldtech.com) on 3/17/10 wrote:
>>---------------------------
>>>I just finished the first of two articles on Westmere, the 32nm, 6-core shrink of
>>>Nehalem. This covers the improvements, including new instructions, minor microarchitectural
>>>tweaks and some basics on the products that are available:
>>>http://www.realworldtech.com/page.cfm?ArticleID=RWT031710140138
>>>
>>>The second piece will be a review that actually includes performance data. I'm
>>>still gathering the data, but this should be a nice short read.
>>>
>>>David
>>>
>>
>>It is a very fast chip. For Diep if we look at performance numbers from 3.33Ghz clocked 980 part:
>>
>>http://www.lostcircuits.com/mambo//index.php?option=com_content&task=view&id=79&Itemid=1&limit=1&limitstart=17
>>
>
>A sentence in the Lost Circuits article caught my attention:
>
>"Once again, we ran Gulftown with and without TurboBoost and, compliment
>to Vincent Diepeveen, that's what scaling should look like."
>
>Reading this sentence, it seems to be implying that such perfect scaling is possible
>for any algorithm: given enough time, any algorithm can be reprogrammed to scale perfectly.
>
>While it actually is the truth (that any algorithm can be reprogrammed to scale
>perfectly), it does *not* tell us anything about the *speed* of computation.
>
>Actually, it is pretty easy to create a program that will take *any* source code
>X and make it scale perfectly up to say 16 cores. Here is what it would look like:
>
>1. On a 16-core machine: Run X on 1 core. The other 15 cores are executing an infinite
>loop until the 1st core finishes executing X.
>
>2. On a 8-core machine: Run X on 1 core. The other 7 cores are executing an infinite
>loop until the 1st core finishes executing X. Then, scrap the results and rerun
>X on the 1st core again! Again the other 7 cores are waiting.
>
>3. On a 4-core machine: 4 times do (Run X on 1 core. The other 3 cores are executing
>an infinite loop until the 1st core finishes executing X. Scrap results, unless it is the last run.)
>
>4. On a 2-core machine: ...
>
>5. On a 1-core machine: 16 times do (Run X on the 1 core. Scrap results, unless it is the last run.)
>
>Now, let's look at the scaling of these 5 cases:
>
>1 core: 16*T seconds
>2 cores: 8*T seconds
>4 cores: 4*T seconds
>8 cores: 2*T seconds
>16 cores: T seconds
>
>So, as you can see, perfect scaling. And it can even be done in a fully automated way. No problem at all.
>
>So, what does the fact that Diep scales perfectly tell us about the actually quality of Diep: probably nothing!
>
>A brain-dead monkey in coma barely able to push a button would be able to make any algorithm scale perfectly ...
>
Then you are saying that 99% of software publishers are brain-dead monkeys who are not even barely able to push a button?