FLOPs of DAG neural network

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DL
DL 2021-5-25
评论： David Willingham 2021-5-26
Hi, everyone. Is there any way to measure the FLOPs or computational complexity of DAG neural network or functions? I tried to statistic the excution time then calculate the FLOPs by profile roughly, but I think DAG is based on C++ or accelerated, therefore, the result of FLOPs is not trustable? Any suggestion?

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David Willingham
David Willingham 2021-5-26
Hi Dianxin,
FLOPs is a performance measure that's not typically used for Deep Learning. Performance can be measured in many ways, here's a list of some:
Throughput - E.g. Predictions per sec
Training Time - E.g. Time to reach x% of validation accuracy
Memory - E.g. How many MB of the network based on the weights
Power - E.g. For embedded devices, how much energy is required to make a prediction
Regards,
David
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David Willingham
David Willingham 2021-5-26
Hi, by default optmizations are not enabled for inference. You can download this support package to enable it for the "predict function".
If you want more optimizations, these are built into our Coder products, which automatically generate native code for the target environment.
MATLAB Coder (C & C++) - including Intel MKL-DNN for Intel processors and ARM Compute Library for ARM Cortex processors
GPU Coder (Cuda) - NVIDIA® CUDA libraries, including TensorRT™, cuDNN, cuFFT, cuSolver, and cuBLAS
Deep Learning HDL Coder (FPGA)

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