have been trying to figure out why I am getting differing results when running an OpenCL kernel on my CPU and my GPU. The basic idea is that I launch this kernel teamwork on the device, then interact with it on the host by periodically writing to device memory and causing the kernel to advance as d…

Hmm, searching for “OpenCL DirectGMA” leads to a thread on the AMD Forums that seems relevant. Note what it says about having to use Shared Virtual Memory for concurrent access to the buffer from the host and the device and using the cl_amd_bus_addressable_memory extension for utilizing DirectGMA. T…

I don’t know much about OpenCL, but coming from graphics API (especially Vulkan) perspective this looks highly suspect. In those APIs modifications to a buffer object contents without careful synchronization and flushing of caches is undefined behavior. And even then the synchronization is to my kno…

@carsten_neumann , thanks for your insight. Some further details about my use case: I would like to use DirectGMA (aka bus addressable memory) to have real-time data sent over the PCIe bus to d_hb. Every time new data is sent to the memory buffer, a new timestamp would show up in d_hb[0], which is wh…

@carsten_neumann , thank you for the link, it was super helpful. Even though AMD advertised the FirePro W5100 as an OpenCL 2.0 device, my clinfo reveals that it is in fact using OpenCL 1.2, has no SVM capabilities and thus atomic operations will not work. I guess I’ll have to start a new post on how …

If someone with an OpenCL 2.0+ capable GPU would be so kind as to run this code and tell me results, that would be greatly appreciated.

I tried this code out on an NVIDIA Quadro K2200 and got the expected results that I got running on the CPU. clinfo reports that some SVM functions are supported on this GPU. I can’t tell if OpenCL 1.2 or 3.0 is being used. $ clinfo SVM capabilities: Coarse grain buffer: Yes Fine g…

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Different OpenCL kernel result with CPU and GPU

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