MATEC Web Conf.
Volume 336, 20212020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|Number of page(s)||8|
|Published online||15 February 2021|
Matrix-DSP back-end support based on TVM compilation structure
College of Computer, National University of Defence Technology, 410073 Changsha, China
* Corresponding author: firstname.lastname@example.org
The emergence of deep learning frameworks has greatly facilitated the construction of network models, but it has not solved the problem of network models deployed in different hardware backends. TVM combines hardware-independent optimization and hardware-related optimization decoupling ideas to provide excellent solutions. By analyzing the basic structure of TVM and the basic process of neural network deployment on hardware, TVM has realized the basic support of the independently developed chip Matrix-DSP, which provides a foundation for further exploring the performance of the chip and enriching the application scenarios of the chip.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.