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Custom Processor Configuration Workflow

Estimate the performance and resource utilization of your custom processor configuration by experimenting with the settings of the deep learning processor convolution and fully connected modules. For more information about the deep learning processor, see Deep Learning Processor Architecture. For information about the convolution and fully connected module parameters, see Properties.

After configuring your custom deep learning processor you can build and generate a custom bitstream and custom deep learning processor IP core. For more information about the custom deep learning processor IP core, see Deep Learning Processor IP Core.

The image shows the workflow to customize your deep learning processor, estimate the custom deep learning processor performance and resource utilization, and build and generate your custom deep learning processor IP core and bitstream.

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