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Deep Learning Processor Customization and IP Generation

Configure, build, and generate custom bitstreams and processor IP cores, estimate and benchmark custom deep learning processor performance

Deep Learning HDL Toolbox™ provides functions to configure, build, and generate custom bitstreams and a custom processor IP. Obtain performance and resource utilization of a pretrained series network on the custom processor. Optimize the custom processor by using the estimation results.


dlhdl.ProcessorConfigConfigure custom deep learning processor


dlhdl.buildProcessorBuild and generate custom processor IP
estimatePerformanceRetrieve layer-level latencies and performance by using estimatePerformance method
estimateResourcesReturn estimated resources used by custom bitstream configuration
getModuleProperty Use the getModuleProperty method to get values of module properties within the dlhdl.ProcessorConfig object
setModuleProperty Use the setModuleProperty method to set properties of modules within the dlhdl.ProcessorConfig object
optimizeConfigurationForNetworkRetrieve optimized network-specific deep learning processor configuration


Custom Processor Configuration

Custom Processor Configuration Workflow

Accelerate the estimation and optimization of custom deep learning processor by configuring parameters of the conv processor and fc processor, created by using the dlhdl.ProcessorConfig object workflow.

Estimate Performance of Deep Learning Network

Analyze the deep learning network layer level latencies and overall performance before deployment.

Estimate Resource Utilization for Custom Processor Configuration

Expedite the time to identify a target hardware board that meets resource utilization budgets before deployment.

Effects of Custom Deep Learning Processor Parameters on Performance and Resource Utilization

Rapidly prototype custom processor configuration and networks by understanding how deep learning processor parameters affect resource utilization and network performance.

Generate Custom Bitstream to Meet Custom Deep Learning Network Requirements

Deploy your custom network that only has layers with the convolution module output format or only layers with the fully connected module output format by generating a resource optimized custom bitstream that satisfies your performance and resource requirements.

Custom Processor Code Generation

Generate Custom Bitstream

Rapidly prototype and iterate custom deep learning networks performance by configuring, building and generating custom bitstreams which can then be deployed to target FPGA and SoC boards.

Generate Custom Processor IP

Build and generate IP for the dlhdl.ProcessorConfig

Featured Examples