Is OpenCL support for the Mali-T628 (for example as found in the Exynos 5420 SoC on the Arndale Octa board) available? If so, how to set it up?
According to the vendor, OpenCL should be supported, but the Arndale Octa Wiki does not state how this can be achieved.
I am using the latest Linaro developer build and installed Mali drivers that contain OpenCL libraries for Mali T604. According to this guide, the driver actually contains references to the Mali T628. So I tried to create the udev rule as specified, which is supposed to solve a permission problem with /dev/mali0, but I found that there is no /dev/mali0 on my installation at all. So my conclusion is that the driver indeed does not support T628.
When I execute a clinfo utility, clGetDeviceInfo returns CL_OUT_OF_HOST_MEMORY for some device properties. Why can I query the GPU for some characteristics, but does this fail for some others? When running a normal application, the same error appears when trying to create an OpenCL Context.
I was surprised to find this topic, where yoshi seems to have OpenCL working and can run benchmarks on his Arndale Octa board. How is this possible if there is no driver available? Or am I just missing something? I hope that you can help me to also establish a working OpenCL development environment.
I get 6 and 600 respectively. So I would assume that I am running on all six cores at 600 Mhz. Is there anything I can do to verify which core group is actually used?
Just to add to what Chris has said about this, this is indeed what we see with older versions of the driver. As you are seeing, with this version it does return 6 cores, though it really will only run on 4 of them. This particular SoC configures the 6 cores into 2 core-groups, 4 + 2. With the driver version you are using you can only target the 4-core group with CL... it is only later drivers that allow access to both core groups, and then it will be as separate devices so you will need to manually split the work if you want to use all the cores. (Graphics works differently and can automatically spread the workload across the entire GPU).
Hope that helps, Tim