[Numpy-discussion] Numpy question: Best hardware for Numpy?
Tue Sep 22 09:39:15 CDT 2009
On 09/22/2009 02:52 AM, Romain Brette wrote:
> David Warde-Farley a écrit :
>> On 21-Sep-09, at 10:53 AM, David Cournapeau wrote:
>>> Concerning the hardware, I have just bought a core i7 (the cheapest
>>> model is ~ 200$ now, with 4 cores and 8 Mb of shared cache), and the
>>> thing flies for floating point computation. My last computer was a
>>> pentium 4 so I don't have a lot of reference, but you can compute ~
>>> 300e6 exp (assuming a contiguous array), and ATLAS 3.8.3 built on it
>>> is extremely fast - using the threaded version, the asymptotic peak
>>> performances are quite impressive. It takes for example 14s to inverse
>>> a 5000x5000 matrix of double.
>> I thought you had a Macbook too?
>> The Core i5 750 seems like a good buy right now as well. A bit
>> cheaper, 4 cores and 8Mb of shared cache though at a slightly lower
>> clock speed.
> How about the Core i7 975 (Extreme)?
> I am wondering if it is worth the extra money.
> NumPy-Discussion mailing list
Check out the charts and stuff at places like
http://www.tomshardware.com or http://www.anandtech.com/ for example:
As far as I know, if you want dual processors (in addition to the cores
and hyperthreads) then you probably are stuck with Xeon's. Also
currently the new Xeon's tend to have a slightly higher clock speed than
the i7 series (xeon w5580 is 3.2GHz) so, without overclocking, they tend
to be faster. The story tends to change with overclocking.
If you overclock then the i7 920 appears to be widely recommended
especially given the current US$900 difference. Really the i7 975 makes
overclocking very easy but there are many guides on overclocking the i7
920 to 3-4Ghz with aircooling. Overclocking xeons may be impossible or
hard to do.
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