Effects of Custom Deep Learning Processor Parameters on Performance and Resource Utilization
Analyze how deep learning processor parameters affect deep learning network performance and bitstream resource utilization. Identify parameters that help improve performance and reduce resource utilization.
This table lists the deep learning processor parameters and their effects on performance and resource utilization.
Deep Learning Processor Parameter | Deep Learning Processor Module | Parameter Action | Effect on Performance | Effect on Resource Utilization |
TargetFrequency | Base module | Increase target frequency. | Improves performance. | Marginal increase in lookup table (LUT) utilization. |
ConvThreadNumber | conv | Increase thread number. | Improves performance. | Increases resource utilization. |
InputMemorySize | conv | Increase input memory size. | Improves performance. | To learn how to optimize your input memory size, see InputMemorySize and OutputMemorySize Optimization. |
OutputMemorySize | conv | Increase output memory size. | Improves performance. | To learn how to optimize your output memory size, see InputMemorySize and OutputMemorySize Optimization. |
FeatureSizeLimit | conv | Increase feature size limit. | None. This option allows the support for a fully connected (FC) layer with a larger feature number. | Marginally increases resource utilization. |
FCThreadNumber | fc | Increase thread number. | Improves performance. | Increases resource utilization. |
InputMemorySize | fc | Increase input memory size. | None. This option allows the support for a FC layer with a larger output activation. | To learn how to optimize your input memory size, see InputMemorySize and OutputMemorySize Optimization. |
OutputMemorySize | fc | Increase output memory size. | None. This option allows the support for a FC layer with a larger output activation. | To learn how to optimize your output memory size, see InputMemorySize and OutputMemorySize Optimization. |
InputMemorySize | custom | Increase input memory size | Marginally increases performance. | Increases Block RAM (BRAM) resource utilization. |
OutputMemorySize | custom | Increase output memory size | Marginally increases performance. | Increases Block RAM (BRAM) resource utilization. |
ProcessorDataType | Top Level | Change data type to int8. | Improves performance. There could be a drop in accuracy. | Reduces resource utilization. |
See Also
dlhdl.ProcessorConfig
| getModuleProperty
| setModuleProperty
| estimatePerformance
| estimateResources