On Sun, 2009-06-14 at 15:50 -0500, Robert Kern wrote:
On Sun, Jun 14, 2009 at 14:31, Bryan Colebr...@cole.uklinux.net wrote:
I'm starting work on an application involving cpu-intensive data
processing using a quad-core PC. I've not worked with multi-core systems
previously and I'm wondering
On Mon, Jun 15, 2009 at 01:22, Bryan Colebr...@cole.uklinux.net wrote:
On Sun, 2009-06-14 at 15:50 -0500, Robert Kern wrote:
On Sun, Jun 14, 2009 at 14:31, Bryan Colebr...@cole.uklinux.net wrote:
I'm starting work on an application involving cpu-intensive data
processing using a quad-core
On Sun, Jun 14, 2009 at 5:27 PM, Bryan Colebr...@cole.uklinux.net wrote:
In fact, I should have specified previously: I need to
deploy on MS-Win. On first glance, I can't see that mpi4py is
installable on Windows.
My mistake. I see it's included in Enthon, which I'm using.
Hi, Bryan... I'm
Bryan Cole wrote:
I'm starting work on an application involving cpu-intensive data
processing using a quad-core PC. I've not worked with multi-core systems
previously and I'm wondering what is the best way to utilise the
hardware when working with numpy arrays. I think I'm going to use the
You may want to look at MPI, e.g. mpi4py is convenient for this kind of
work. For numerical work across processes it is close to a de facto
standard.
It requires an MPI implementation set up on your machine though (but for
single-machine use this isn't hard to set up, typically just
In fact, I should have specified previously: I need to
deploy on MS-Win. On first glance, I can't see that mpi4py is
installable on Windows.
My mistake. I see it's included in Enthon, which I'm using.
Bryan
Bryan
___
Numpy-discussion
On Sun, Jun 14, 2009 at 14:31, Bryan Colebr...@cole.uklinux.net wrote:
I'm starting work on an application involving cpu-intensive data
processing using a quad-core PC. I've not worked with multi-core systems
previously and I'm wondering what is the best way to utilise the
hardware when
