Hi Jerome,
Jerome Kieffer <[email protected]> writes:
> I spent the day in porting a pyopencl application from Linux to MacOSX.
> I don't blame pyopencl at all but I found the porting was quite
> difficult for a couple of portable tools like python and OpenCL.
>
> I am working on a freshly installed MacOSX Lion on a MacBook Pro from
> 2008 with a dual core "core2" from intel and two GPUs from NVidia 9400M
> and 9600M.
>
> First bug: "RuntimeError: Device not available"
> I selected the most powerfull GPU when creating the context but the
> queue creation failed ... It seems only the gfxCardStatus external
> tool is able to activate (actually switch) GPUs.
>
> Question: Is there a way within PyOpenCL to know if a device is actually
> available or not ?
> The flag: device.available is set to 1 regardless if the GPU is actually ON
> or OFF. The only unacceptable solution I found is based on try/except :(
Sorry, no idea.
> try: queue=pyopencl.CommandQueue(ctx)
> except RuntimeError: print("Sorry, switched off")
What package printed this error message? Doesn't seem to be PyOpenCL?
> Second bug: "pyopencl.RuntimeError: clBuildProgram failed: build program
> failure"
> Solution: options to build the kernel need to be stripped under MacOSX !!!
Was this for code built by PyOpenCL, or from within your application? In
any case, the CL standard documents a few options that are required to
be cross-vendor. Everything else is likely vendor-specific.
>
> Third bug: "LogicError: clEnqueueNDRangeKernel failed: invalid work group
> size"
> When running on CPU, I have the fealing that the only valid workgroup size is
> "1", even when
> device.max_work_group_size advertizes 1024 !!!
This is known:
http://wiki.tiker.net/OpenCLOddities
> I found track of such bugs on this mailing list and others but I have
> the feeling the community developing opencl application on MacOSX is
> not that large, am I wrong ?
Can't say. At least in terms of overall download numbers, PyOpenCL is
doing rather well...
Andreas
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