Re: [Numpy-discussion] fourier with single precision

2007-08-06 Thread Lars Friedrich
Hello, thanks for your comments. If I got you right, I should look for a FFT-code that uses SSE (what does this actually stand for?), which means that it vectorizes 32bit-single-operations into larger chunks that make efficient use of recent CPUs. You mentioned FFTW and MKL. Is this

Re: [Numpy-discussion] fourier with single precision

2007-08-06 Thread David Cournapeau
Lars Friedrich wrote: Hello, thanks for your comments. If I got you right, I should look for a FFT-code that uses SSE (what does this actually stand for?), which means that it vectorizes 32bit-single-operations into larger chunks that make efficient use of recent CPUs. You mentioned

Re: [Numpy-discussion] fourier with single precision

2007-08-06 Thread Matthieu Brucher
MKL is from Intel (free as in beer on Linux and for academic purpose I think, but of course, you should check whether this applies to you). AFAIK, the MKL is free for non-commercial purposes under Linux only, and there is a special license for academics. Matthieu

Re: [Numpy-discussion] fourier with single precision

2007-08-06 Thread David Cournapeau
Lars Friedrich wrote: Hello, thanks for your comments. If I got you right, I should look for a FFT-code that uses SSE (what does this actually stand for?), which means that it vectorizes 32bit-single-operations into larger chunks that make efficient use of recent CPUs. You mentioned

Re: [Numpy-discussion] How to implement a 'pivot table?'

2007-08-06 Thread Timothy Hochberg
Nicely done Travis. Working code is always better than theory. I copied your interface and used the brute-force, non-numpy approach to construct the pivot table. On the one hand, it doesn't preserve the order that the entires are discovered in as the original does. On the other hand, it's about

Re: [Numpy-discussion] numpy arrays, data allocation and SIMD alignement

2007-08-06 Thread Lisandro Dalcin
On 8/3/07, David Cournapeau [EMAIL PROTECTED] wrote: Here is what I can think of: - adding an API to know whether a given PyArrayObject has its data buffer 16 bytes aligned, and requesting a 16 bytes aligned PyArrayObject. Something like NPY_ALIGNED, basically. - forcing data

Re: [Numpy-discussion] numpy arrays, data allocation and SIMD alignement

2007-08-06 Thread Anne Archibald
On 06/08/07, David Cournapeau [EMAIL PROTECTED] wrote: Well, when I proposed the SIMD extension, I was willing to implement the proposal, and this was for a simple goal: enabling better integration with many numeric libraries which need SIMD alignment. As nice as a custom allocator might be,

Re: [Numpy-discussion] numpy arrays, data allocation and SIMD alignement

2007-08-06 Thread David Cournapeau
Anne Archibald wrote: I have to agree. I can hardly volunteer David for anything, and I don't have time to implement this myself, but I think a custom allocator is a rather special-purpose tool; if one were to implement one, I think the way to go would be to implement a subclass of ndarray

Re: [Numpy-discussion] numpy arrays, data allocation and SIMD alignement

2007-08-06 Thread Anne Archibald
On 07/08/07, David Cournapeau [EMAIL PROTECTED] wrote: Anne, you said previously that it was easy to allocate buffers for a given alignment at runtime. Could you point me to a document which explains how ? For platforms without posix_memalign, I don't see how to implement a memory allocator