Custom Deep Learning Network for Xilinx FPGA target
I am researching on building deep learning accelerators on Xilinx FPGA using the Deep Learning HDL Toolbox. I have a custom CNN network that has an input layer size of [1 1024 2]. Using the ProcessorConfig Class, I’m trying to optimize the processor configuration for my custom CNN network with the optimizeConfigurationForNetwork helper.
The optimize processor is generated sucessfully, but while trying to estimate performance of the CNN network i get the following error:
The Conv module in the processor configuration has an InputMemorySize of [150 150 7]. This is insufficient to delploy the ‘AP1’ Layer. Increase the InputMemorySize to [171 171 7] or more using hPC.setModuleProperty(‘conv’, ‘InputMemorySize’, [171 171 7]), where hPC is the dlhdl.ProcessorConfig object.
I’ve tried to increase the InputMemorySize, but the error keeps being thrown with a higher inputMemorySize requirement for the 2D Average Pooling layer.
I’d appreciate you recommendation on how i could fix this. Thank you.
Paul Osinowo,
Graduate Student
University of Strathclyde, Glasgow.I am researching on building deep learning accelerators on Xilinx FPGA using the Deep Learning HDL Toolbox. I have a custom CNN network that has an input layer size of [1 1024 2]. Using the ProcessorConfig Class, I’m trying to optimize the processor configuration for my custom CNN network with the optimizeConfigurationForNetwork helper.
The optimize processor is generated sucessfully, but while trying to estimate performance of the CNN network i get the following error:
The Conv module in the processor configuration has an InputMemorySize of [150 150 7]. This is insufficient to delploy the ‘AP1’ Layer. Increase the InputMemorySize to [171 171 7] or more using hPC.setModuleProperty(‘conv’, ‘InputMemorySize’, [171 171 7]), where hPC is the dlhdl.ProcessorConfig object.
I’ve tried to increase the InputMemorySize, but the error keeps being thrown with a higher inputMemorySize requirement for the 2D Average Pooling layer.
I’d appreciate you recommendation on how i could fix this. Thank you.
Paul Osinowo,
Graduate Student
University of Strathclyde, Glasgow. I am researching on building deep learning accelerators on Xilinx FPGA using the Deep Learning HDL Toolbox. I have a custom CNN network that has an input layer size of [1 1024 2]. Using the ProcessorConfig Class, I’m trying to optimize the processor configuration for my custom CNN network with the optimizeConfigurationForNetwork helper.
The optimize processor is generated sucessfully, but while trying to estimate performance of the CNN network i get the following error:
The Conv module in the processor configuration has an InputMemorySize of [150 150 7]. This is insufficient to delploy the ‘AP1’ Layer. Increase the InputMemorySize to [171 171 7] or more using hPC.setModuleProperty(‘conv’, ‘InputMemorySize’, [171 171 7]), where hPC is the dlhdl.ProcessorConfig object.
I’ve tried to increase the InputMemorySize, but the error keeps being thrown with a higher inputMemorySize requirement for the 2D Average Pooling layer.
I’d appreciate you recommendation on how i could fix this. Thank you.
Paul Osinowo,
Graduate Student
University of Strathclyde, Glasgow. deep learning, deep learning hdl toolbox, hardware acceleration MATLAB Answers — New Questions
