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This project forked from oaid/mxnet-hrt

Heterogeneous Run Time version of MXNet. Added heterogeneous capabilities to the MXNet, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original MXNet architecture which users deploy their applications seamlessly.

License: Apache License 2.0

CMake 0.49% Makefile 0.43% R 2.54% Rebol 0.01% C++ 32.65% Python 28.11% Java 0.03% Shell 1.20% C 0.88% Jupyter Notebook 13.02% Cuda 5.19% Batchfile 0.11% MATLAB 0.32% Perl 6.28% Perl 6 0.04% Scala 8.71%

mxnet-hrt's Introduction

MXNet-HRT

MXNet-HRT is a project that is maintained by OPEN AI LAB, it uses Arm Compute Library (NEON+GPU) to speed up MXNet and provide utilities to debug, profile and tune application performance.

The release version is 0.3.1, is based on Rockchip RK3399 Platform, target OS is Ubuntu 16.04. Can download the source code from OAID/MXNet-HRT

The ARM Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies. See also Arm Compute Library.
MXNet is a Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more. See also MXNet.

Documents

Arm Compute Library Compatibility Issues :

There are some compatibility issues between ACL and MXNet Layers, we bypass it to MXNet's original layer class as the workaround solution for the below issues