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1. Intel® FPGA AI Suite IP Reference Manual
2. About the Intel® FPGA AI Suite IP
3. Intel® FPGA AI Suite IP Generation Utility
4. Intel® FPGA AI Suite Ahead-of-Time Splitter Utility
5. CSR Map and Descriptor Queue
A. Intel® FPGA AI Suite IP Reference Manual Archives
B. Intel® FPGA AI Suite IP Reference Manual Document Revision History
2.4.2.1. Parameter Group: Global Parameters
2.4.2.2. Parameter Group: activation
2.4.2.3. Parameter Group: pe_array
2.4.2.4. Parameter Group: pool
2.4.2.5. Module: softmax
2.4.2.6. Parameter Group: dma
2.4.2.7. Parameter Group: xbar
2.4.2.8. Parameter Group: filter_scratchpad
2.4.2.9. Parameter Group: config_network
4.1. Files Generated by the Intel® FPGA AI Suite Ahead-of-Time (AOT) Splitter Utility
4.2. Building the Intel® FPGA AI Suite Ahead-of-Time (AOT) Splitter Utility
4.3. Running the Intel® FPGA AI Suite Ahead-of-Time (AOT) Splitter Utility
4.4. Intel® FPGA AI Suite Ahead-of-Time (AOT) Splitter Utility Example Application
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2.1.1. MobileNet V2 differences between Caffe and TensorFlow models
There are two inverted bottlenecks (group of expand, depthwise, projection) in which TensorFlow has already gone down to 14x14 while Caffe is still at 28x28. This is the only place where the structure of the graph differs. TensorFlow also uses ReLU6, implemented with a clamp in the Intel® FPGA AI Suite IP, while Caffe uses ReLU.