Memory Management NVDLA and GPU

simon.eichhammer · March 12, 2021, 11:08am

Hi,

i’m using an Jetson AGX Xavier and want to use the NVDLA and GPU for inference.
I’m unsure of the SOC memory management.

Does the NVDLA and GPU have a unified shared memory?
Can data be passed from GPU to NVDLA without any copies and vice versa?

Thanks.

AastaLLL · March 15, 2021, 2:35am

Hi,

DLA has it’s own SRAM.

But the data transfer between GPU <-> DLA is handled by an internal driver.
You will only need to prepare a GPU buffer for TensorRT as input.

Thanks.

simon.eichhammer · March 15, 2021, 9:03am

Thanks for your reply.
Could you please provide me any sample code?

AastaLLL · March 17, 2021, 6:54am

Hi,

You can check following for the DLA sample:

github.com

dusty-nv/jetson-inference/blob/master/c/tensorNet.cpp#L361


      
          {

          	mEngine   = NULL;

          	mInfer    = NULL;

          	mContext  = NULL;

          	mStream   = NULL;

          	mBindings	= NULL;

          

          	mMaxBatchSize   = 0;	

          	mEnableDebug    = false;

          	mEnableProfiler = false;

          

          	mModelType        = MODEL_CUSTOM;

          	mPrecision 	   = TYPE_FASTEST;

          	mDevice    	   = DEVICE_GPU;

          	mAllowGPUFallback = false;

          

          	mProfilerQueriesUsed = 0;

          	mProfilerQueriesDone = 0;

          

          	memset(mEventsCPU, 0, sizeof(mEventsCPU));

          	memset(mEventsGPU, 0, sizeof(mEventsGPU));

Thanks.

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Memory Management NVDLA and GPU

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