ArcvaVX: OpenVX Framework for Adaptive Reconfigurable Computer Vision Architectures
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-42921-7_7
Reference15 articles.
1. Giduthuri, R., Pulli, K.: OpenVX: a framework for accelerating computer vision. In: Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) (2016)
2. Hascoë, J., de Dinechin, B.D., Desnos, K., et al.: A distributed framework for low-latency OpenVX over the RDMA NoC of a clustered manycore. In: High Performance Extreme Computing Conference (HPEC), pp. 1–7 (2018)
3. Kalb, T., Kalms, L., Göhringer, D., et al.: Tulipp: towards ubiquitous low-power image processing platforms. In: International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS) (2016)
4. Kalms, L., Amini Rad, P., Ali, M., et al.: A parametrizable high-level synthesis library for accelerating neural networks on fpgas. Journal of Signal Processing Systems (JSPS) (2021)
5. Kalms, L., Göhringer, D.: Scalable clustering and mapping algorithm for application distribution on heterogeneous and irregular FPGA clusters. J. Parallel Distrib. Comput. (JPDC) 133, 367–376 (2019)
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