Monte Carlo eXtreme for OpenCL - works on NVIDIA/ATI GPUs and CPUs

[Qianqian Fang]

Dear colleagues

After procrastinating once and again, I finally
uploaded the OpenCL version of MCX to github:

https://github.com/fangq/mcxcl

The code was essentially written over 2 years ago,
and I have been trying to keep up with the MCX
development with occasional updates. It shares a
lot codes from the CUDA version of MCX, although
it has not been tested as much. I spend some time
over the past two days to update it again, and
tested with nvidia and ATI cards. The basic
features seem to work robustly. Now I think it is
time to benefit from public tests and feedbacks.

A complete develop log can be found at

https://github.com/fangq/mcxcl/commits/master

The code can be checked out via git commands,
or a zip file, listed on the github page.

MCXCL works very much like MCX, except that
it supports majority of modern computing hardware,
including both NVIDIA and ATI GPUs and Intel/AMD
CPUs, benefited from the general heterogeneous
computing model from OpenCL. Performance-wise,
it is as fast as MCX-CUDA on nvidia cards. Using the
-G option, you can specify a single, or multiple, available
devices on your computer to run the simulation. Use
mcxcl -L to list all available devices.

If you have an ATI card, you can use the GPU, or CPU,
or both for computing; if you have an NVIDIA card,
you can only use GPU, as nvidia's OpenCL lib does
not support CPU. You may have to use a free OpenCL
implementation such as freeocl:

http://code.google.com/p/freeocl/

Because OpenCL uses JIT compilation, the different
compilation conditions, like mcx_det, mcx_cached etc,
are now done at run-time, making it possible to use
a single binary for all.

The code will be updated as I continue to optimize the
performance. You are welcome to send me your feedback
either by direct email or mcx-users mailing list.

enjoy!

Qianqian



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