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zoli0726
Journeyman III

Method to share data

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Hi!

I'm trying to implement a multi gpu app.

i need to share data between two gpus.

Because there is random access in the buffers, i cant just split the calculation into half.

I would like to ask, what could be the best way to synchronize modified data after kernel execution. I cant just copy them together, because there are random modifications on both gpu(but they newer write to the same area).

First i thought that svm is the answer, but it seems that its only shared between one device and the host at a time. If i create an svm buffer and do modifications on the kernel side, it

won't be combined on the host side, there is no option to just map the buffer, i can only map the buffer from queue1 or queue2 so map the gpu1's svmbuffer or the gpu2's. I have to

map the buffer to queue1(gpu1) and queue2(gpu2) every time i want to send data to the gpu-s. Am i doing something wrong, or its not actually as shared as i thought.

Thanks!

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dipak
Staff
Staff

Re: Method to share data

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I think, fine grained SVM buffer (with atomic support) can be used for the above purpose. For more details about the fine grained SVM, please refer the OpenCL spec.

FYI:

http://developer.amd.com/community/blog/2015/01/15/opencl-2-0-fine-grain-shared-virtual-memory/

http://developer.amd.com/community/blog/2015/09/08/fine-grain-svm-with-examples/

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dipak
Staff
Staff

Re: Method to share data

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I think, fine grained SVM buffer (with atomic support) can be used for the above purpose. For more details about the fine grained SVM, please refer the OpenCL spec.

FYI:

http://developer.amd.com/community/blog/2015/01/15/opencl-2-0-fine-grain-shared-virtual-memory/

http://developer.amd.com/community/blog/2015/09/08/fine-grain-svm-with-examples/

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zoli0726
Journeyman III

Re: Method to share data

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Fine grain buffer without atomics seems to do the thing. I created an svm fine grained buffer, and can compute randomly in it across multiple dgpu-s.

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dipak
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Re: Method to share data

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Okay. Actually, the atomic functions are useful if any synchronization is needed among multiple accesses of same data from different threads.

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