<div dir="ltr"><br><div class="gmail_extra"><br><br><div class="gmail_quote">On Tue, Jun 11, 2013 at 10:48 PM, Kyle Mandli <span dir="ltr"><<a href="mailto:kyle.mandli@gmail.com" target="_blank">kyle.mandli@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Thanks for the pointers on performance, sounds like it will be a mixed bag in my case as I use both the eigen and solver functionality. Excuse my naivety on the topic but would it be possible to not remove support but encourage binary maintainers to use OpenBLAS instead?</div>
</blockquote><div><br></div><div>The main issue is not binaries but people building from source. A simple "python setup.py install" will result in ~70 test failures, plus whatever is broken in scipy.linalg that's not caught by tests. <br>
<br></div><div>Maybe something else can be done - Pauli proposed something on numpy-discussion just now that may help.<br><br></div><div>Ralf<br></div><div> <br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div class="HOEnZb"><div class="h5">
<div class="gmail_extra"><br><br><div class="gmail_quote">On Tue, Jun 11, 2013 at 3:09 PM, Ralf Gommers <span dir="ltr"><<a href="mailto:ralf.gommers@gmail.com" target="_blank">ralf.gommers@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><br><div class="gmail_extra"><br><br><div class="gmail_quote"><div>On Tue, Jun 11, 2013 at 9:16 PM, Kyle Mandli <span dir="ltr"><<a href="mailto:kyle.mandli@gmail.com" target="_blank">kyle.mandli@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">Any idea what kind of performance decrease is this likely to cause (switching from accelerate to OpenBLAS)? I currently rely on wrapping a Fortran routine that uses system_info to find the LAPACK libraries (via f2py --link-lapack_opt).</div>
</blockquote><div><br></div></div><div>Not necessarily a decrease - on average OpenBLAS seems to be comparable to MKL and Accelerate, but it probably depends strongly on your application and your CPU. For example in this thread (<a href="https://github.com/Homebrew/homebrew-science/issues/7" target="_blank">https://github.com/Homebrew/homebrew-science/issues/7</a>) someone finds OpenBLAS is faster, but on eigenvalue decompositions it's slower. <a href="http://home.uchicago.edu/~skrainka/pdfs/Talk.Eigen.pdf" target="_blank">http://home.uchicago.edu/~skrainka/pdfs/Talk.Eigen.pdf</a> also has a few benchmarks showing that OpenBLAS performance is similar to MKL.<br>
<br></div><div>If you're interested, <a href="https://github.com/samueljohn/homebrew-python" target="_blank">https://github.com/samueljohn/homebrew-python</a> allows you to install Numpy and Scipy with OpenBLAS.<span><font color="#888888"><br>
</font></span></div><span><font color="#888888"><div><br></div>
<div>Ralf<br><br></div></font></span><div><div> <br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div>
<br></div><div>Kyle</div></div><div class="gmail_extra"><br><br><div class="gmail_quote"><div><div>On Tue, Jun 11, 2013 at 1:34 AM, Ralf Gommers <span dir="ltr"><<a href="mailto:ralf.gommers@gmail.com" target="_blank">ralf.gommers@gmail.com</a>></span> wrote:<br>
</div></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div><div><div dir="ltr"><div><div><div><div><div>Hi,<br><br></div>Given the issues we've been having with Accelerate on OS X 10.7 and 10.8, we plan to disable support for it completely in scipy (and numpy, will bring that up on numpy-discussion later) before the next release.<br>
<br></div>Background:<br><a href="https://github.com/scipy/scipy/issues/2248" target="_blank">https://github.com/scipy/scipy/issues/2248</a><br><a href="https://github.com/scipy/scipy/issues/2547" target="_blank">https://github.com/scipy/scipy/issues/2547</a><br>
<br></div>This will make compiling on OS X harder, but we can't leave functionality giving incorrect results (and ~70 test errors) hang around forever, so we have to do something. We'll do some testing and write up a guide for how to build against other BLAS/LAPACK implementations. Homebrew already supports OpenBLAS, so that's a good option for who doesn't want to go through compiling their own libraries.<span><font color="#888888"><br>
</font></span></div><span><font color="#888888"><br></font></span></div><span><font color="#888888">Ralf<br><br></font></span></div>
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