mace VS pytorch_dlprim

Compare mace vs pytorch_dlprim and see what are their differences.

mace

MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms. (by XiaoMi)

pytorch_dlprim

DLPrimitives/OpenCL out of tree backend for pytorch (by artyom-beilis)
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mace pytorch_dlprim
1 3
4,876 207
0.5% -
2.8 5.9
13 days ago 27 days ago
C++ C++
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

mace

Posts with mentions or reviews of mace. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-06.

pytorch_dlprim

Posts with mentions or reviews of pytorch_dlprim. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-31.

What are some alternatives?

When comparing mace and pytorch_dlprim you can also consider the following projects:

MNN - MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

dlprimitives - Deep Learning Primitives and Mini-Framework for OpenCL

ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform

oneDNN - oneAPI Deep Neural Network Library (oneDNN)

TNN - TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

Boost.Compute - A C++ GPU Computing Library for OpenCL

CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

FluidX3D - The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL.

Simd - C++ image processing and machine learning library with using of SIMD: SSE, AVX, AVX-512, AMX for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM.

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

tensorflow - An Open Source Machine Learning Framework for Everyone