I think I have said this before, but its worth a repeat: Pickle (including cPickle) is a slow hog! That might not be the overhead you see, you just haven't noticed it yet.
I saw this some years ago when I worked on shared memory arrays for Numpy (cf. my account on Github). Shared memory really did not help to speed up the IPC, because the entire overhead was dominated by pickle. (Shared memory is a fine way of saving RAM, though.) multiprocessing.Queue will use pickle for serialization, and is therefore not the right tool for numerical parallel computing with Cython or NumPy. In order to use multiprocessing efficiently with NumPy, we need a new Queue type that knows about NumPy arrays (and/or Cython memoryviews), and treat them as special cases. Getting rid of pickle altogether is the important part, not facilitating its use even further. It is easy to make a Queue type for Cython or NumPy arrays using a duplex pipe and couple of mutexes. Or you can use shared memory as ringbuffer and atomic compare-and-swap on the first bytes as spinlocks. It is not difficult to get the overhead of queuing arrays down to little more than a memcpy. I've been wanting to do this for a while, so maybe it is time to start a new toy project :) Sturla Neal Hughes <[email protected]> wrote: > I like Cython a lot. My only complaint is that I have to keep switching > between the numpy array support and typed memory views. Both have there > advantages but neither can do every thing I need. > > Memoryviews have the clean syntax and seem to work better in cdef classes > and in inline functions. > > But Memoryviews can't be pickled and so can't be passed between > processes. Also there seems to be a high overhead on converting between > memory views and python numpy arrays. Where this overhead is a problem, > or where i need to use pythons multiprocessing module I tend to switch to > numpy arrays. > > If memory views could be converted into python fast, and pickled I would > have no need for the old numpy array support. > > Wondering if these problems will ever be addressed, or if I am missing > something completely. > > -- > > --- > You received this message because you are subscribed to the Google Groups > "cython-users" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > For more options, visit <a > href="https://groups.google.com/groups/opt_out.";>https://groups.google.com/groups/opt_out.</a> > > ------=_Part_1342_18667054.1390644115997 > Content-Type: text/html; charset=UTF-8 > Content-Transfer-Encoding: quoted-printable > > <div dir=3D"ltr">I like Cython a lot. My only complaint is that I have to k= > eep switching between the numpy array support and typed memory views. Both = > have there advantages but neither can do every thing I need.<div><br></div>= > <div>Memoryviews have the clean syntax and seem to work better in cdef clas= > ses and in inline functions.</div><div><br></div><div>But Memoryviews can't= > be pickled and so can't be passed between processes. Also there seems to b= > e a high overhead on converting between memory views and python numpy array= > s. Where this overhead is a problem, or where i need to use pythons multipr= > ocessing module I tend to switch to numpy arrays.</div><div><br></div><div>= > If memory views could be converted into python fast, and pickled I would ha= > ve no need for the old numpy array support.</div><div><br></div><div>Wonder= > ing if these problems will ever be addressed, or if I am missing something = > completely.<br></div><div><br></div><div><br></div></div> > > <p></p> > > -- <br /> > &nbsp;<br /> > --- <br /> > You received this message because you are subscribed to the Google Groups > &= > quot;cython-users&quot; group.<br /> > To unsubscribe from this group and stop receiving emails from it, send an e= > mail to [email protected].<br /> > For more options, visit <a href=3D"https://groups.google.com/groups/opt_out= > ">https://groups.google.com/groups/opt_out</a>.<br /> > > ------=_Part_1342_18667054.1390644115997-- _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
