Create a custom processor configuration object of class dlhdl.ProcessorConfig
.
Create an object of class workflow
by using the dlhdl.Workflow
class.
Set the deep learning network and processor configuration for the workflow object.
Call the estimate
function for the workflow object.
The speed and latency is stored in a structure struct
and displayed on the screen.
For example:
hPC = dlhdl.ProcessorConfig; snet = vgg19; hW = dlhdl.Workflow('Network', snet, 'ProcessorConfig',hPC); result = hW.estimate('Performance');
The result of the estimation is:
Deep Learning Processor Estimator Performance Results LastLayerLatency(cycles) LastLayerLatency(seconds) FramesNum Total Latency Frames/s ------------- ------------- --------- --------- --------- Network 202770372 1.01385 1 202770372 1.0 conv_module 158812469 0.79406 conv1_1 2022004 0.01011 conv1_2 15855549 0.07928 pool1 2334753 0.01167 conv2_1 7536365 0.03768 conv2_2 14837392 0.07419 pool2 1446960 0.00723 conv3_1 7950445 0.03975 conv3_2 14365933 0.07183 conv3_3 14365933 0.07183 conv3_4 14365933 0.07183 pool3 930145 0.00465 conv4_1 7073684 0.03537 conv4_2 13761300 0.06881 conv4_3 13761300 0.06881 conv4_4 13761300 0.06881 pool4 572644 0.00286 conv5_1 3432645 0.01716 conv5_2 3432645 0.01716 conv5_3 3432645 0.01716 conv5_4 3432645 0.01716 pool5 140249 0.00070 fc_module 43957903 0.21979 fc6 36535923 0.18268 fc7 5965299 0.02983 fc8 1456681 0.00728 * The clock frequency of the DL processor is: 200MHz
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