提交 e00159bb 编写于 作者: L Liangliang He

Update docs with iOS support

上级 15925d14
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[中文](README_zh.md)
**Mobile AI Compute Engine** (or **MACE** for short) is a deep learning inference framework optimized for
mobile heterogeneous computing platforms. The design focuses on the following
mobile heterogeneous computing on Android, iOS and Linux devices. The design focuses on the following
targets:
* Performance
* Runtime is optimized with NEON, OpenCL and Hexagon, and
......@@ -41,8 +41,7 @@ targets:
code and literal obfuscations.
* Platform coverage
* Good coverage of recent Qualcomm, MediaTek, Pinecone and other ARM based
chips. CPU runtime is also compatible with most POSIX systems and
architectures with limited performance.
chips. CPU runtime supports Android, iOS and Linux.
* Rich model formats support
* [TensorFlow](https://github.com/tensorflow/tensorflow),
[Caffe](https://github.com/BVLC/caffe) and
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......@@ -15,7 +15,7 @@
[加入我们](JOBS.md) |
[English](README.md)
**Mobile AI Compute Engine (MACE)** 是一个专为移动端异构计算平台优化的神经网络计算框架。
**Mobile AI Compute Engine (MACE)** 是一个专为移动端异构计算平台(支持Android, iOS, Linux)优化的神经网络计算框架。
主要从以下的角度做了专门的优化:
* 性能
* 代码经过NEON指令,OpenCL以及Hexagon HVX专门优化,并且采用
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* 模型加密与保护
* 模型保护是重要设计目标之一。支持将模型转换成C++代码,以及关键常量字符混淆,增加逆向的难度。
* 硬件支持范围
* 支持高通,联发科,以及松果等系列芯片的CPU,GPU与DSP(目前仅支持Hexagon)计算加速。
同时支持在具有POSIX接口的系统的CPU上运行。
* 支持高通,联发科,以及松果等系列芯片的CPU,GPU与DSP(目前仅支持Hexagon)计算加速。CPU模式支持Android, iOS, Linux等系统。
* 模型格式支持
* 支持[TensorFlow](https://github.com/tensorflow/tensorflow)
[Caffe](https://github.com/BVLC/caffe)[ONNX](https://github.com/onnx/onnx)等模型格式。
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