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README.md

 # **MACE** - *Mobile(Mi) Accelerated Compute Engine Library*
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-小米自主研发的移动端神经网络加速引擎。
 
-*可加入用户邮件组 mace-users@xiaomi.com*
-
-## 简介
+## Introduction
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-**利用端侧的异构计算设备加速神经网络模型。**
+**Accelerating Neural Network with Heterogeneous Computing Devices in the phone.**
 
-目前支持的端侧计算设备包括：**CPU(NEON)/GPU/DSP**.
+Supported Devices: **CPU(NEON)/GPU/DSP**.
 
-## 架构
+## Architecture
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-采用Op组成的有向无环图的计算模式，使用**Tensor**对象存储所有数据并进行统一管理。
+- Use computational pattern of **DAG consisting of Ops**. 
+- **Tensor** objects manage all data.
+- **Workspace** manage all **Tensors**.
 
 ## GPU
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-基于OpenCL 2.0实现，使用Image的存储格式优化内存访问和并行计算。
-针对不同Op的算法，设计对应的Image存储格式来优化内存访问。
+Use **Image** object to optimize memory access and parallel computing based on OpenCL 2.0.
 
-下面是针对不同**Tensor**类型对应的Buffer和Image的格式。
-| Tensor类型 | Buffer格式 | Image格式 | 说明 |
+Design the corresponding **Image** format to optimize memory access for different Op algorithm.
+Each pixel of **Image** object contains four elements(e.g. RGBA).
+The Following is **Buffer** and **Image** format for all **Tensors**.
+| Tensor| Buffer| Image| Explanation|
 | --------- | :---------:|:--------:|:----:|
-|Channel-Major Input/Output | NHWC | [W * (C+3)/4, N * H] | 默认输入输出的格式|
-|Height-Major Input/Output | NHWC | [W * C, N * (H+3)/4] | Winograd Convolution所用格式| 
-|Width-Major Input/Output | NHWC | [(W+3)/4 * C, N * H] | Winograd Convolution所用格式|
-|Convolution Filter | HWOI | [H * W * RoundUp<4>(I), (O+3)/4]|卷积核格式，尝试过[H*w*I, (O+3)/4]，两者性能没有区别|
-|Depthwise Convlution Filter | HWIM | [H * W * M, (I+3)/4]|Depthwise卷积核格式|
-|1-D Argument | W | [(W+3)/4, 1] | 一维参数格式，如Bias|
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+|Channel-Major Input/Output | NHWC | [W * (C+3)/4, N * H] | Default Input/Output format|
+|Height-Major Input/Output | NHWC | [W * C, N * (H+3)/4] | Winograd Convolution format| 
+|Width-Major Input/Output | NHWC | [(W+3)/4 * C, N * H] | Winograd Convolution format|
+|Convolution Filter | HWOI | [H * W * RoundUp<4>(I), (O+3)/4]|Convolution filter format，There is no difference compared to [H*w*I, (O+3)/4]|
+|Depthwise Convlution Filter | HWIM | [H * W * M, (I+3)/4]|Depthwise-Convolution filter format|
+|1-D Argument | W | [(W+3)/4, 1] | 1D argument format, e.g. Bias|
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