Tuesday, May 17, 2022
Latest:

Learning Center

Learn electronics, programming. inventing & MORE!!

Machine Learning 

tinyML Research Symposium 2021: Compiler Toolchains for Deep Learning Workloads on Embedded…

tinyML 533 Comments , , , , , , , ,



tinyML Research Symposium 2021 https://www.tinyml.org/event/research-symposium-2021
Compiler Toolchains for Deep Learning Workloads on Embedded Platforms
Max SPONNER

As the usage of deep learning becomes increasingly popular in mobile and embedded solutions, it is necessary to convert the framework-specific network representations into executable code for these embedded platforms. This paper starts with a survey and benchmark of the available open source deep learning compiler toolchains, which focuses on the capabilities and performance of the toolchains in regard to targeting embedded microcontrollers that are combined with a dedicated accelerator in a heterogeneous fashion. The second part focuses on the implementation and evaluation of a compilation flow that targets such a solution and reuses one of the existing toolchains to demonstrate the necessary steps for hardware developers to build a software flow for their product.

source

You May Also Like

Bundle: Ethical Hacking and Countermeasures: Secure Network Operating Systems and Infrastructures (CEH), 2nd + Ethical Hacking and Countermeasures: … Threats and Defense Mechanisms, 2nd + Ethical

admin 5

Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy: Proceedings of the Second International Conference, MMCITRE 2021 … in Intelligent Systems and Computing, 1405)

admin 6

tinyML Summit 2022: 1 kB and not a bit more! The ideal weight for a tinyML model

tinyML 0

533 thoughts on “tinyML Research Symposium 2021: Compiler Toolchains for Deep Learning Workloads on Embedded…”

Leave a Reply

Your email address will not be published.