Luke Pfister lpfis...@illinois.edu writes:
Is there a suggested way to do the equivalent of np.sum along a particular
axis for a high-dimensional GPUarray?
I saw that this was discussed in 2009, before GPUarrays carried stride
information.
Hand-writing a kernel is probably still your best
Jerome Kieffer jerome.kief...@esrf.fr writes:
On Thu, 21 May 2015 07:59:35 -0400
Andreas Kloeckner li...@weasel.tiker.net wrote:
Luke Pfister lpfis...@illinois.edu writes:
Is there a suggested way to do the equivalent of np.sum along a particular
axis for a high-dimensional GPUarray
Alex Park a...@nervanasys.com writes:
Thank you for the response.
As a followup question, I was looking at the underlying code for
ipc_mem_handle, and it seems like when a handle is deleted, it tries to do
a mem_free on the underlying device pointer.
So could there not be a situation as
Alex Park a...@nervanasys.com writes:
Not sure if its sufficiently tested for other peoples' usage, but deleting
/src/cpp/cuda.hpp: line 1624
seemed to solve my problems. Logic here being that the memory will be
freed inside the process that allocated the memory when the object from
Lu, Xinghua xing...@pitt.edu writes:
I am new to pyCuda, and I would appreciate your help in advance.
I were able to write a few short pyCuda code but run into a roadblock with
one at my hand.
The code snippet is as follows:
tumorLnFScore = np.zeros((nTumorMutGenes,
Alex Park a...@nervanasys.com writes:
Hi,
I'm trying to use multiple gpus with mpi and ipc handles instead of the
built-in mpi primitives to p2p communication.
I think I'm not quite understanding how contexts should be managed. For
example, I have two versions of a toy example to try out
Ananth Sridharan ana...@umd.edu writes:
Can someone shed some light on the arguments for the prepare used by
pycuda? I have been unable to find a set of examples to help understand
what the arguments are supposed to look like.
On the official website,
Jannes Nagel jannes.j.na...@gmail.com writes:
Hi!
I just installed pycuda on my system. I have Windows 8.1 and a GTX970 in
my Notebook. Therefore I am using Cuda 7 as the only compatible Cuda
Version with my system.
I ran into 2 problems and I hope someone can help me.
1: If I enable
Jerome Kieffer jerome.kief...@esrf.fr writes:
On Mon, 30 Mar 2015 12:46:42 -0400
Ananth Sridharan ana...@umd.edu wrote:
I have a simulation code which requires the use of multiple kernels. Each
of these kernels (global functions) needs to call a common set of device
functions. To organize
that Andreas Kloeckner
provides on his website. (http://mathema.tician.de/software/pycuda/)
Running the tests provided by that ZIP file goes all well except for
the test_cumath.py file. I receive the following error:
E AssertionError: (2.3841858e-06, 'cosh', type 'numpy.complex64')
E assert built
Fil Peters fil.pet...@yandex.com writes:
Thanks for the answer, it is a pity that you it is not possible to use this
functions, especially since it also seems not possible to use the cublas
functions in the source modules. In order to be able to use the gpu array
functions in a large loop
samie abdul fas...@yahoo.de writes:
Hi,
is it possible to precompile the invoked kernels beforehand? My code makes
use of several CUDA kernels, which are basically called within a fit
function. Profiling the code with cProfile yields:
42272 function calls (42228 primitive calls) in 1.662
Fil Peters fil.pet...@yandex.com writes:
Hello,
I am just new to pycuda and started testing it. I was wondering if it is
possible to use the gpuarray functions in a sourcemodule.
For example, I was trying to covert the following code into a pycuda
sourcemodule:
numpy code:
Alessandro,
Alessandro Barracco bomastu...@gmail.com writes:
Hi all, I'm a newbie to CUDA and looking for python found two alternative:
Anaconda and pyCUDA. I decided to use pyCUDA but I need to read a good book
to understand CUDA. I found several book on the topics but it seems that
each use
Hi all,
I would like to draw your attention to a workshop that might be of
interest to at least some of you:
http://www.sable.mcgill.ca/array/
The point of the workshop is to provide a forum to discuss tools,
abstractions, and languages for high-performance computation on
arrays. Much of what
David A. Markowitz david.a.markow...@gmail.com writes:
Many thanks Andreas, I've solved the problem now. While digging through the
compiler.py code, I noticed a check for the PYCUDA_DEFAULT_NVCC_FLAGS
environment variable, which is then passed to nvcc. Ultimately I was able
to solve my
David A. Markowitz david.a.markow...@gmail.com writes:
Thanks again, Andreas. I'm really looking forward to getting started with
PyCUDA.
Unfortunately, I've already tried your suggested approach (updating
nvcc.profile with NVVMIR_LIBRARY_DIR = /usr/local/cuda-6.5/nvvm/libdevice,
which
David A. Markowitz david.a.markow...@gmail.com writes:
Hi, thanks for the quick reply (and good advice!). I wiped my cuda 6.5
installation and reinstalled from scratch. nvcc now works when called from
the command line on simple CUDA samples. It compiles for my GPU's
architecture (3.5) by
David A. Markowitz david.a.markow...@gmail.com writes:
Hi, I just installed PyCUDA, but test_driver.py crashes with the
following error:
CompileError: nvcc compilation of /tmp/tmpNht4bp/kernel.cu failed
[command: nvcc --cubin -arch sm_35
Luigi,
here are a few problems with your approach:
- The contents of your SourceModule is not valid C (as in, C the
programming language)
- 'set' is a Python data structure. PyCUDA will not magically swap out
the code of 'set' and execute its operations on the GPU.
- Working with arrays of
Luigi Assom luigi.as...@gmail.com writes:
Hello Andreas,
thank you for your feedback:
Which prerequisite must have a data structure to be good for GPU?
Should I allocate exact size of memory for each array ?
I hate to say it, but let me just state two facts: (1) There's no canned
Donald Osmeyer donald.osme...@outlook.com writes:
I just installed Ubuntu 14.04, the Nvidia driver 340.29, cuda version 6.5.12.
I tried to install pycuda-2014.1 using the instructions found at
http://wiki.tiker.net/PyCuda/Installation/Linux/Ubuntu
Everything seems to install fine. In
Paul Mullowney paulmullow...@gmail.com writes:
I've been using PyCuda quite a bit recently. Very nice!
I'm trying to use memcpy_atod to message a chunk of CPU data to the GPU
where the size/shapes of the input and output arrays don't match (though
the size of the data transfer certain does).
Hi Craig,
Craig Stringham string...@mers.byu.edu writes:
I keep crashing a server (kernel panic) when using pycuda within ipython.
It doesn't seem to matter what kernel I run and it only crashes several
minutes after I have run a kernel but have kept the ipython shell open. I
am using the
Mike McFarlane mike.mcfarl...@iproov.com writes:
Hi
I've installed pycuda following
http://wiki.tiker.net/PyCuda/Installation/Linux
When I try to run test/test_driver.py it fails many tests, mainly with
'TypeError: 'numpy.ndarray' does not have the buffer interface'. The output
is below
Eric Larson larson.eri...@gmail.com writes:
PyCUDA worked perfectly on Ubuntu 14.04, but after upgrade to 14.10 I get
the following in both Python 2 and Python 3:
import pycuda.autoinit
Traceback (most recent call last):
File stdin, line 1, in module
File
kjs b...@riseup.net writes:
Hello,
I have written an MPI routine in Python that sends jobs to N worker
processes. The root process handles file IO and the workers do
computation. In the worker processes calls are made to the cuda enabled
GPU to do FFTs.
Is it safe to have N processes
Lewis,
Mcgibbney, Lewis J (398M) lewis.j.mcgibb...@jpl.nasa.gov writes:
I DO NOT need to use PyCUDA in stages 1 or 4 e.g. Pre and post processing.
What I am looking for is advice on what is ‘common’ practice for NOT
reimplementing an entire project (13,000 C and IDL code) in PyCUDA but
Simon Perkins simon.perk...@gmail.com writes:
I've modified the patch to take the existing behaviour into account.
Applied to git. Thanks for your contribution!
Andreas
pgp17RNHRiKnp.pgp
Description: PGP signature
___
PyCUDA mailing list
Ashwin Srinath ashwinsr...@gmail.com writes:
I'm not sure - but this may have something to do with the implementation of
`fill`. Because on the flip side, changes to the PETSc Vec *are* reflected
the GPUArray. So I can see that they are actually sharing device memory..
As far as I know, PETSc
Hi Simon,
Simon Perkins simon.perk...@gmail.com writes:
Here's the patch!
The patch looks good. One minor complaint is that in absence of an
allocator kwarg, your patch changes existing behavior. Specifically, the
allocator that was previously used was the one of the array passed to
the
Ashwin Srinath ashwinsr...@gmail.com writes:
Hello, PyCUDA users!
I'm trying to construct a GPUArray from device memory allocated using
petsc4py. I've written some C code that extracts a raw pointer from a PETSc
cusp vector. Now, I am hoping to 'place' this memory into a gpuarray,
using
Dear Marco,
the easiest thing to do is to have nvcc in your $PATH--that should then
enable PyCUDA to automatically find the rest of CUDA.
Andreas
Marco Ippolito ippolito.ma...@gmail.com writes:
Hi all,
in my Ubuntu 14.04 I'm trying to install PyCUDA, but I have this
error's message:
Marco Ippolito ippolito.ma...@gmail.com writes:
Hi Andreas,
thanks for helping.
Following the indications here:
https://help.ubuntu.com/community/EnvironmentVariables#Persistent_environment_variables
in a brand new file nvcc.sh in /etc/profile.d/ I put:
export
Thomas Unterthiner thomas_unterthi...@web.de writes:
Hi again!
How do you completely shut down PyCUDA? After running the following lines:
from pycuda import driver as pycuda_drv
pycuda_drv.init()
device = pycuda_drv.Device(0)
ctx = device.make_context()
I can see a new
Freddie Witherden fred...@witherden.org writes:
Hi Andreas,
On 29/09/14 16:17, Andreas Kloeckner wrote:
GPUArrays don't actually care who owns the data, so if you're OK with
building a GPUArray as a 'descriptor' structure (which is quick and
lightweight) without moving any data around
Thomas Unterthiner thomas_unterthi...@web.de writes:
Hi!
I have a program that makes extensive use of pycuda, but also calls out
to a C library which also uses CUDA internally (it does not share any
state or memory with the pycuda code, and uses the CUDA runtime API).
However, after the
Bruce Labitt bdlab...@gmail.com writes:
I am trying to install PyCuda from git. I have Ubuntu 14.04, and CUDA6.5
installed. (Driver is 340.19 from Nvidia, CUDA from Nvidia) CUDA examples
seem to work, at least the ones supported my my hardware. (3.0) Partially
stuck on setting up
Hi Tomasz,
Tomasz Rybak tomasz.ry...@post.pl writes:
Dnia 2014-08-12, wto o godzinie 20:56 +0200, Tomasz Rybak pisze:
Dnia 2014-08-11, pon o godzinie 15:47 -0500, Andreas Kloeckner pisze:
[ cut ]
I've just fixed (I think) the last known Py3 bug in PyCUDA, so I think
I'll go ahead
Hi James,
James Keaveney james.keave...@durham.ac.uk writes:
I'm having an issue with PyCUDA that at first glance seem like they
might be similar to those of Thomas Unterthiner (messages from Jun 20
2014, Weird bug when slicing arrays on Kepler cards). I'm also using a
Kepler card (GTX
LFC liufubu...@gmail.com writes:
Dear All,
Sorry to interrupt you by this way.
When I tried to test the sample code GlInterop.py, I met a problem as below:
---
Dear LFC,
LFC liufubu...@gmail.com writes:
I did the command rm -Rf build and setup.py build and setup.py
install.
But I sill have the same problem. I don't know why.
First, please make sure to keep the list cc'd, for archival. Next,
please post a complete build log to some pastebin and
elodw a...@pdauf.de writes:
On 11.07.2014 22:14, Andreas Kloeckner wrote:
elodw a...@pdauf.de writes:
The issue is that you're passing integers. Cast to floating point
before you call the function.
And another question:
Is there a sqrt-Function?
http://documen.tician.de/pycuda/array.html
Hi all,
Ahmed Fasih wuzzyv...@gmail.com writes:
Hi folks, I write in the hope that someone has gotten a K20 Kepler 3.5
compute capability device and has gotten it to do dynamic parallelism,
wherein a kernel can kick off grids on its own without returning to
the CPU. A hello world example is
Am 14.07.2014 um 16:47 schrieb Forrest Pruitt:
The frustrating thing is that in a stand-alone python shell, pycuda
behaves appropriately. It is only in a Celery process that things
break down.
Any help here would be appreciated!
If I need to provide any more information, just let me know!
elodw a...@pdauf.de writes:
with
import pycuda.gpuarray as gpuarray
import pycuda.driver as drv
import pycuda.autoinit
import numpy
import sys
from pycuda.tools import mark_cuda_test
from pycuda.characterize import has_double_support
from pycuda.compiler import SourceModule
.
Dear Ernst,
elodw a...@pdauf.de writes:
i want to start with pycuda and had a very beginner question:
ok, the header lines are clear,
same to_gpu statement and the get statement,
thats it.
What is the problem defined in Python:
a=array[1000,100]
for i in range(1000-1):
for j in
Daniel Pagan daniel.pa...@andphysicsforall.com writes:
Thanks for this, Andreas. I will try to profile some simple PyCuda code
with the VS profiler as in the above posts, then will experiment to see
how/if I can get the debugger to work. Hopefully I will have some results to
report.
What
Hi Daniel,
Daniel daniel.pa...@andphysicsforall.com writes:
I just installed PyCuda and got it working on my Windows 8.1 laptop. I'm
able to run the examples in VS 2010. My question concerns the 'preferred'
development environment for PyCuda: While it runs on Windows, I'm not able to
JeHoon Song song.je-h...@kaist.ac.kr writes:
Hello,
I just started to develop PyCUDA application.
It build process is not successful as following:
...
bpl-subset/bpl_subset/boost/type_traits/detail/cv_traits_impl.hpp:37:
internal compiler error: in make_rtl_for_nonlocal_decl, at
Bogdan Opanchuk manti...@gmail.com writes:
Hello,
Does PyCUDA support struct arguments to kernels? From the Python side
it means an element of an array with a struct dtype (a numpy.void
object), e.g.
dtype = numpy.dtype([('first', numpy.int32), ('second', numpy.int32)])
pair =
Hi Bogdan,
Bogdan Opanchuk manti...@gmail.com writes:
Thank you for the correction. Just curious, how come in PyOpenCL it
works with rank-0 numpy arrays (which, in my opinion, is more
intuitive than implicitly casting a rank-1 array to a scalar)? Is it
just a difference between PyCUDA and
Dear Danny,
Daniel Jeck dje...@jhmi.edu writes:
My name is Danny Jeck. I don't really want to subscribe to the mailing list
for pycuda, but I thought I should point out to you that the following code
creates an error
import pycuda.gpuarray as gpuarray
import pycuda.driver as cuda
Alexander Bock alexander.asp.b...@gmail.com writes:
I am creating some timing tests with PyCUDA for batch-loading an image
sequence. I first tried timing a normal, synchronous transfer over global
memory.
Now I am looking to test pagelocked memory, specifically, I would like to
test:
Hi Graham,
Graham Mills 13g...@queensu.ca writes:
I am attempting to use a memory pool for some gpu array calculations,
using PyCUDA 2013.1 with python 3.x and CUDA 5.5. The trouble is I
can't find an appropriate integer type with which to call .allocate on
a DeviceMemoryPool object. All
金陆 ret...@eyou.com writes:
I am using an old PC with an old GPU card(GeForce 9800 GT).
As you may know, 9800 does not support printf function in device code.
However, Nvidia supplies cuPrintf. In CU file, it can be used like following.
The situation is how can I use cudaPrintfInit,
Jayanth Channagiri cv.jaya...@hotmail.com writes:
Dear all
I am having problems with slicing a 3D array into 2D array and then sending
it to GPU.
For example,
array1 = ones((128,128,128))
array1_gpu = gpuarray.to_gpu(array1) #no problem in sending it to GPU
But if I convert it to a 2D
Hi István,
István Lorentz isti_...@yahoo.com writes:
[snip]
Note, when working with pure numpy arrays, the results is always in a
new copy. I'm using the regular __div__ operator, not the __idiv__
which I understand should be in-place modifier. I noticed similar
optimization for the
kkFreddie Witherden fred...@witherden.org writes:
Thank you for this. However, toying around with the following example:
[snip]
with OpenMPI 1.7.3 (running as mpirun -n 2 python file.py) I find that
the version using cubuf.as_buffer fails with a segmentation fault due to
invalid
Freddie Witherden fred...@witherden.org writes:
This came up a while ago on the mpi4py mailing list [1] and with CUDA 6
brining unified virtual memory it may become more important in the future.
It would be nice if PyCUDA device allocations provided a method for
creating a suitable Python
Hi Alex,
Alex Nitz alex.n...@ligo.org writes:
I've noticed that a change made several months ago to the string error
handling isn't compatible with versions of python earlier than 2.7.
The following fails on python versions 2.7.
s = test string
s.decode(UTF8, error='replace')
as
Dear Ben,
Rowland Ben rowland@claudiusregaud.fr writes:
I am using PyCUDA to render slices out of a 3D texture which are then
passed to an OpenGL PBO for display on the screen. Everything is going
well except that I cannot get my texture to use the address modes WRAP
or MIRROR correctly,
Rowland Ben rowland@claudiusregaud.fr writes:
Thanks for such a quick fix. Can you tell me what the best way is to
upgrade my install and test this out?
Just follow the regular from-source install instructions here:
http://wiki.tiker.net/PyCuda/Installation
HTH,
Andreas
Tomasz Rybak tomasz.ry...@post.pl writes:
Dnia 2013-11-29, pią o godzinie 10:40 -0600, Andreas Kloeckner pisze:
Rowland Ben rowland@claudiusregaud.fr writes:
Thanks for such a quick fix. Can you tell me what the best way is to
upgrade my install and test this out?
Just follow
Rowland Ben rowland@claudiusregaud.fr writes:
That is a seriously rapid response! I think this is the minimal code
example that reproduces the problem, probably I am making a mistake
somewhere in the syntax:
Fixed in git (I think). Thanks for the report, and let me know if you
spot
Hi Andreas,
Healther.astro healther.as...@gmail.com writes:
I have some kernels which will be used over and over again, but as the
compile time of them is pretty high (something like half an hour, for some
hundred kernels). I would like to ensure that they are stored permanently on
my
Hi Ben,
Rowland Ben rowland@claudiusregaud.fr writes:
Just started working with PyCUDA, and already very taken with it, it makes a
whole load of things very simple. Already after a couple of days I have a
working program with OpenGL interop using PySide to provide the GUI and CUDA
ggeo gg...@windowslive.com writes:
Hello, I did all these and when I try to run test_driver.py it gives me:
ExecError: error invoking 'nvcc --version': [Errno 2] No such file or
directory
/usr/lib64/python2.7/site-packages/pytools/prefork.py:53: ExecError
What should I do ?
Are you sure
Hi Graham,
Graham Mills 13g...@queensu.ca writes:
I looked back about a year in the archives and couldn't find anything on
this. I just downloaded and built cgen 2013.1.2 and codepy 2013.1.2 today.
When using thrust as in the example at
http://wiki.tiker.net/PyCuda/Examples/ThrustInterop ,
Rok Roskar ros...@physik.uzh.ch writes:
I've got a host-side CUDA library wrapped in Cython and I'd like to use
it on a device-side array that I've allocated in python with PyCuda.
However, I'm completely at a loss as to how I should pass the device
pointers from the python side of things to
Rok Roškar ros...@physik.uzh.ch writes:
wow that makes it pretty straightforward, thanks!
I'm afraid I'm probably missing something obvious, but is there a similar
trick for streams?
Nope, sorry. Patches welcome, although having this functionality is
somewhat risky: A plain integer
Dear Nicolas,
Nicolas LEMERCIER lemer...@igbmc.fr writes:
I am currently trying to use peer2peer GPU memory access with pycuda and I
face with problems regarding the syntax.
My code follow this template:
dev1=cuda.Device(1)
ctx1=dev1.make_context()
dev0=cuda.Device(0)
Hi Dorin,
Dorin Niculescu niculescu_dori...@yahoo.com writes:
I have a new ASUS laptop with optimus enabled NVIDIA 750M card and i want to
install pycuda on it. I've installed Ubuntu 12.04,
Bumblebee+nvidia-319, cuda 5.5 and everything was working great until i've
installed pycuda using
Hi Eric,
You'll to declare the function 'extern C', then it should work.
Andreas
Eric Scheffel eric.schef...@nottingham.edu.cn writes:
Thanks again for making available the cuda wrapper library for python. It's
great to use and helps me a lot in my own research. One problem I am facing
at
Hi Eric,
Eric Scheffel eric.schef...@nottingham.edu.cn writes:
I noticed some strange behaviour with the most recent version of PyCuda
(I think I pulled this from the git repository but am not sure anymore).
I am running a loop in which textures continuously have to be rebound
using
Sam Preston j...@sci.utah.edu writes:
Hi all,
I would like to use pycuda to write a few kernels to interoperate with a
larger cuda/python library I'm already using. I can get the raw device
memory address as a python int, and from searching past threads on the
mailing list it sounds like I
Nathaniel Virgo nathanielvi...@gmail.com writes:
$ python GlInterop.py
Hit ESC key to quit, 'a' to toggle animation, and 'e' to toggle cuda
Traceback (most recent call last):
File GlInterop.py, line 136, in display
process_image()
File GlInterop.py, line 188, in process_image
Vivek Saxena spino...@gmail.com writes:
This problem was solved by the following commands:
sudo ln -s /usr/lib/nvidia-325/libcuda.so /usr/lib/libcuda.so
sudo ln -s /usr/lib/nvidia-325/libcuda.so.1 /usr/lib/libcuda.so.1
But I now get a message saying
TypeError: No registered converter was
Hi Trevor,
Trevor Cickovski movingpicture...@gmail.com writes:
I am running pycuda using Python 2.6.5, Cuda 5.0 on Ubuntu 10. My graphics
card is an NVIDIA GTX680.
Whenever I do 'import pycuda.autoinit', everything hangs (requires manual
kill). I have traced it to this statement in
Hi Bogdan, all,
Bogdan Opanchuk manti...@gmail.com writes:
Both in PyCUDA and PyOpenCL constructors of GPU arrays have
``strides`` keyword parameter, and you can create a non-contiguous
array, e.g.:
import pyopencl as cl
from pyopencl.array import Array
import numpy
ctx =
Hi Alex,
Alex Nitz alex.n...@ligo.org writes:
I've noticed that the 'take' function doesn't seem to work for arrays with
complex dtypes (complex64, complex128). I've added to patches that allow
this to work. It requires adding texture support for these types.
As was done for double
Hi Michael,
Michael McNeil Forbes michael.forbes+pyt...@gmail.com writes:
On Jul 18, 2013, at 10:46 PM, Michael McNeil Forbes
michael.forbes+pyt...@gmail.com wrote:
What is the recommended way of preparing ElementwiseKernel instances for
repeated calling on the same GPU arrays for
Michael McNeil Forbes michael.forbes+pyt...@gmail.com writes:
Here is the profile of the slow __call__. All the time is spent in
generate_stride_kernel_and_types:
Line # Hits Time Per Hit % Time Line Contents
==
Lev Givon l...@columbia.edu writes:
I'm trying to access the memory associated with a GPUArray from within a
compiled extension built using Cython's memoryview feature. According to the
Cython documentation, it is possible to access C arrays using this feature;
however, when I attempt to do so
Michael McNeil Forbes michael.forbes+pyt...@gmail.com writes:
Thats the idea, but the problem I am having is getting the pointer into the
correct DeviceAllocation type.
What is the type of x.gpudata in the theano example you show?
The c++ function claims to expect a ctypes.c_ulonglong, but
Hi all,
PyOpenCL and PyCUDA 2013.1 just rolled off the assembly line. Release
notes here:
https://pypi.python.org/pypi/pyopencl
http://documen.tician.de/pyopencl/misc.html#version-2013-1
https://pypi.python.org/pypi/pycuda
http://documen.tician.de/pycuda/misc.html#version-2013-1
If you notice
Hi all,
I'm writing to let you know that the initial slicing support in PyCUDA
and PyOpenCL has had a slightly unintended performance consequence due
to this numpy bug:
https://github.com/numpy/numpy/issues/3375
I've written about this in the release notes here:
Søren Rasmussen rissed...@gmail.com writes:
Sorry for the late reply - stuff came up.
Faulthandler gave me nothing. The driver version is: NVIDIA UNIX x86_64
Kernel Module 319.21 Sat May 11 23:51:00 PDT 2013
Backtrace:
#0 0x77def181 in ?? () from /lib64/ld-linux-x86-64.so.2
#1
Hi Tomasz,
Tomasz Rybak tomasz.ry...@post.pl writes:
I've been packaging PyCUDA for Debian.
I run all the tests to ensure that package works on Python 2
and Python 3. All tests pass except for on from test_driver.py:
$ python test_driver.py
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
Tomasz Rybak tomasz.ry...@post.pl writes:
Hello.
For some time I've been working on adding new features from CURAND
into PyCUDA ( g...@github.com:rybaktomasz/pycuda.git branch curand-41)
I have added MRG32k3a, and poisson generation to all existing classes.
Branch contains documentation and
Søren Rasmussen rissed...@gmail.com writes:
Hi,
When using PyCUDA with the cuda 5.5 release candidate, I get a
segmentation fault when Python exits.
I guess it's a problem somewhere in the cleanup process..
The segfault can be reproduced by running:
$ python -c import
Pierre Castellani pcastel...@gmail.com writes:
I have bought kepler GPU in order to do some numerical calculation on it.
I would like to use pyCuda (looks to me the best solution).
Unfortunatly when I am running a test like
MeasureGpuarraySpeedRandom
Bob Zigon bob.zi...@gmail.com writes:
Hello
I am using Ubuntu 11.10 with PyCuda 2012.1 and Cuda 5.0 on a K20c.
I have been developing with Cuda for 6 years and Python for 4 weeks.
I use the pycuda.compiler class to compile my Cuda code in my Python code.
Is there a way I can see all of the
Dear Bob,
bob zigon bob.zi...@gmail.com writes:
If a kernel is called from within a python loop, how frequently is nvcc
called?
If the kernel is essentially static, I would hope that nvcc is called once
irregardless of
the number of times the loop iterates.
On the other hand, if the
albeam alb...@ncsu.edu writes:
I'm having issues getting pycuda to run properly. I had issues installing,
which I suspect is the root of my issue now. Following these instructions:
http://wiki.tiker.net/PyCuda/Installation/Linux/Ubuntu
I had to remove the last configuration flag
Dear Mr. Maze,
Mr. Maze v...@madmaze.net writes:
I am currently working on an application where I need to retrieve the index
of the max value.
Is there a way to get the index along with the max of a gpuarray?
At the moment I am returning the array back to the host just to locate
where the
Dear Malcolum,
Malcolm Tobias mtob...@wustl.edu writes:
Sorry to bug you, but I run a cluster at Washington Univ. in St. Louis and we
recently added some GPU nodes. We have several python users, and one has
requested that I install PyCUDA on our system. For the first attempt, I
tried
Tomasz Rybak tomasz.ry...@post.pl writes:
Hello.
I've pulled latest git version and built PyCUDA on Debian
unstable. I've tested on two machines - one with Fermi (GTX 460)
and one with ION (9400M). In both cases all tests pass for Python 2.7.3
and only 2 tests fail for Python 3.2.
Failing
Geoffrey Anderson mrco...@yahoo.com writes:
So I've got this program using Elementwise and I want to up the
performance one more level. Nobody to my knowledge has written about
using shared memory, but that does not mean it can't be done in an
Elementwise program. How can shared memory be
Ahmed Fasih wuzzyv...@gmail.com writes:
Sorry for troubling everyone with this petty question, but I recall reading
maybe a couple of years ago how PyCUDA itself consisted of about 1200 lines
of C++ code and about half as much Python code. I went looking for this but
couldn't find this
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