Abstract
The rodent whisker system is a prominent experimental subject for the study of sensorimotor integration and active sensing. As a result of improved video-recording technology and progressively better neurophysiological methods, there is now the prospect of precisely analyzing the intact vibrissal sensori-motor system. The vibrissae and snout analyzer (ViSA), a widely used algorithm based on computer vision and image processing, has been proven successful for tracking and quantifying rodent sensorimotor behavior, but at a great cost in processing time. In order to accelerate this offline algorithm and eventually employ it for online whisker tracking (less than 1 ms/frame latency), we have explored various optimizations and acceleration platforms, including OpenMP multithreading, NVidia GPUs and Maxeler Dataflow Engines. Our experimental results indicate that the optimal solution for an offline implementation of ViSA is currently the OpenMP-based CPU execution. By using 16 CPU threads, we achieve more than 4,500x speedup compared to the original Matlab serial version, resulting in an average processing latency of 1.2 ms/frame, which is a solid step towards real-time (and online) tracking. Analysis shows that running the algorithm on a 32-thread-enabled machine can reduce this number to 0.72 ms/frame, thereby enabling real-time performance. This will allow direct interaction with the whisker system during behavioral experiments. In conclusion, our approach shows that a combination of software optimizations and the careful selection of hardware platform yields the best performance increase.
Original language | English |
---|---|
Title of host publication | Proceedings - 2017 17th International Conference on Embedded Computer Systems |
Subtitle of host publication | Architectures, Modeling, and Simulation, SAMOS 2017 |
Editors | Yale Patt, S. K. Nandy |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 137-145 |
Number of pages | 9 |
ISBN (Electronic) | 9781538634370 |
DOIs | |
Publication status | Published - 20 Apr 2018 |
Event | 17th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2017 - Samos, Greece Duration: 16 Jul 2017 → 20 Jul 2017 |
Publication series
Series | Proceedings - 2017 17th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2017 |
---|---|
Volume | 2018-January |
Conference
Conference | 17th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2017 |
---|---|
Country/Territory | Greece |
City | Samos |
Period | 16/07/17 → 20/07/17 |
Bibliographical note
Funding Information:ACKNOWLEDGMENTS This work was supported by the Neuroscience department of the Erasmus MC. We are grateful to Dr. Sebastiaan Koekkoek for his help, to the NVidia Corporation for their donation of the Titan X GPU, and to Maxeler Technologies for their continuous support throughout this research effort.
Publisher Copyright: © 2017 IEEE.