[PyCUDA] Newbie - a book?

[Alessandro Barracco]

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 C++. Any book that explain pyCUDA? If no, please, suggest me a
good book to start. I have experience in python.
Many thanks
--
*eng. Alessandro Barracco, phDTechnology and Management of Aeronautical
Infrastructure*

*Faculty of Engineering and Architecture*
*University of Enna "Kore"*

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[Andreas Kloeckner]

Alessandro,

Post by Alessandro Barracco
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 C++. Any book that explain pyCUDA? If no, please, suggest me a
good book to start. I have experience in python.
Many thanks

PyOpenCL serves a roughly equivalent function as PyCUDA, and this book:

http://www.amazon.com/OpenCL-Action-Accelerate-Graphics-Computations/dp/1617290173/

at least has a section on PyOpenCL.

Hope that helps!
Andreas

[Jerome Kieffer]

On Sat, 14 Feb 2015 12:11:01 +0100

Post by Alessandro Barracco
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 C++. Any book that explain pyCUDA? If no, please, suggest me a
good book to start. I have experience in python.

If you have experience in Python, you need to understand CUDA (and GPU programming).
I would advice you the Udacity CS344 course. It is online and free.

Cheers,

[Jerome Kieffer]

On Sat, 14 Feb 2015 19:47:17 +0100

Thank for fast reply. But OpenCL is not cuda (and haven't the same
performances)

Actually OpenCL is not Cuda but the OpenCL driver for nvidia hardware declares itself as:

Platform Version: OpenCL 1.1 CUDA 6.5.33
Platform Name: NVIDIA CUDA
Platform Vendor: NVIDIA Corporation

The difference in speed is still to be proven (above the error bar)

and udacity is a web service while I need a printed book.

Udacity offers online courses ... in a couple of hours you get bootstrapped.
I guess it would be faster than reading a book.
If you want a book, print the documentation of the nvidia SDK.

[Johan Hake]

I am an experienced Python hacker. I year ago I had never used CUDA or
PyCUDA. I had tried to learn CUDA through many different tutorials and
finally found that udacity course and I immediately understood several
things with GPUs that I never got the hang of before.

After the course I looked at the examples provided by PyCUDA and I had what
I needed to start playing. Now I have a full fledged parallel ODE solver
implemented for arbitrary ODEs using PyCUDA.

Thanks for the excellent software :)

Johan

Post by Jerome Kieffer
On Sat, 14 Feb 2015 19:47:17 +0100

Thank for fast reply. But OpenCL is not cuda (and haven't the same
performances)

Platform Version: OpenCL 1.1 CUDA 6.5.33
Platform Name: NVIDIA CUDA
Platform Vendor: NVIDIA Corporation
The difference in speed is still to be proven (above the error bar)

and udacity is a web service while I need a printed book.

Udacity offers online courses ... in a couple of hours you get
bootstrapped.
I guess it would be faster than reading a book.
If you want a book, print the documentation of the nvidia SDK.
--
JérÎme Kieffer
Data analysis unit - ESRF
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http://lists.tiker.net/listinfo/pycuda

[Alex]

As far as books go, I recommend two:

"CUDA by Example" and "Programming Massively Parallel Processors". The
former is a straightforward intro while the other is a tad more technical.
The latter is also co-authored by the guy who runs the Coursera course.

I took the Udacity course last year, and I am taking the Coursera one now.
Though I am only half-way through the Coursera course, I would probably
recommend Udacity's. It is better structured, more intuitive and better
explained imo.

I think the most important is to get a feel for how CUDA works, and then it
really does not matter which language you use. Granted, the ways you check
for device properties and download/upload memory are slightly different,
but ultimately work the same way.

The mailing list, wiki, github gists and other online resources are there
to help you in case you need it.

- Alex