Presentation
On the Correlation of CNN Performance and Hardware Metrics for Visual Inference on a Low-Cost CPU-based Platform
Author/s | Velasco Montero, Delia
Fernández Berni, Jorge Carmona Galán, Ricardo Rodríguez Vázquez, Ángel Benito |
Department | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo |
Publication Date | 2019 |
Deposit Date | 2019-12-03 |
Published in |
|
ISBN/ISSN | 978-1-7281-3227-3 2157-8702 2157-8672 |
Abstract | While providing the same functionality, the various Deep Learning software frameworks available these days do not provide similar performance when running the same network model on a particular hardware platform. On the ... While providing the same functionality, the various Deep Learning software frameworks available these days do not provide similar performance when running the same network model on a particular hardware platform. On the contrary, we show that the different coding techniques and underlying acceleration libraries have a great impact on the instantaneous throughput and CPU utilization when carrying out the same inference with Caffe, OpenCV, TensorFlow and Caffe2 on an ARM Cortex-A53 multi-core processor. Direct modelling of this dissimilar performance is not practical, mainly because of the complexity and rapid evolution of the toolchains. Alternatively, we examine how the hardware resources are distinctly exploited by the frameworks. We demonstrate that there is a strong correlation between inference performance - including power consumption - and critical parameters associated with memory usage and instruction flow control. This identified correlation is a preliminary step for the development of a simple empirical model. The objective is to facilitate selection and further performance tuning among the ever-growing zoo of deep neural networks and frameworks, as well as the exploration of new network architectures. |
Project ID. | N00014-19-1-2156
TEC2015-66878-C3-1-R 765866 |
Citation | Velasco Montero, D., Fernández Berni, J., Carmona Galán, R. y Rodríguez Vázquez, Á.B. (2019). On the Correlation of CNN Performance and Hardware Metrics for Visual Inference on a Low-Cost CPU-based Platform. En International Conference on Systems, Signals and Image Processing (IWSSIP) (249-254), Osijek, Croacia: Institute of Electrical and Electronics Engineers. |
Files | Size | Format | View | Description |
---|---|---|---|---|
On the Correlation of CNN ... | 4.210Mb | [PDF] | View/ | |