[Numpy-discussion] about SIMD (SSE2 & SSE3)
Sat Nov 6 14:46:35 CDT 2010
On 2010-11-06, at 8:51 AM, qihua wu wrote:
> I used the following command to install the numpy to enable the SSE3
> numpy-1.5.1rc1-win32-superpack-python3.1.exe /arch sse3
> Then how can I know whether numpy is running with SSE or not?
As far as I know, the only thing that uses SSE/SSE2/SSE3 would be BLAS operations. Things like elementwise addition, multiplication, etc. are not implemented to take advantage of vectorized machine instructions, at least not yet, unless the C compiler is aggressively optimizing and doing some loop unrolling which I sort of doubt.
> I have a program to process the data from sql server using java to process 600M rows, it takes 7 hours to complete, about 4 hours is eating the cpu. I am wondering whether I can port the java to numpy to cut the 4 hours to 2hours or even less by enabling the SSE3. Any comment?
It's not clear that crunching data from an SQL database would be any faster with NumPy. It really depends on the specifics of your problem.
More information about the NumPy-Discussion