CODEWITHSUNDEEP
tensorflow
David Norman
David Norman

Reputation: 73

Tensorflow Device vs DeviceContext

I am implementing a new Device for Tensorflow. I would like some clarification between the Device and the DeviceContext. I have read this question but I think I need a bit more info.

Should it be that each device in my system has one Device instance, with the device instance maintaining information about that physical device? Then the DeviceContext should be maintaining runtime information about this device.

In the other question, the answers state that the GPU device maintains several device contexts, one for each stream, with streams given particular jobs (copying vs executing). It sounds like the kernel ops bound to specific device contexts, and if so, when/where does that occur?

Upvotes: 0

Views: 183

Answers (1)

user3002273
user3002273

Reputation:

Since the GPUDevice has multiple contexts per device, I would argue that you do not need to have one context per device. As such, I would agree that the device class would contain minimal data about the actual hardware which the device context would behave as more of a runtime control of the device (handling memory allocation, data transfer, execution, etc.) judging by the names of the functions in the context

The binding of kernel ops to contexts in GPUs occurs in the FillContextMap where the computation graph nodes are attached to device contexts.

Upvotes: 1

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