提交 7d9ff408 编写于 作者: T tensor-tang

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上级 02e0b5f9
......@@ -5,7 +5,7 @@
充分展现英特尔平台的优势,有效提升PaddlePaddle在英特尔架构上的性能。
<div align="center">
<img src="image/overview.png" width=410><br/>
<img src="image/overview.png"><br/>
Figure 1. PaddlePaddle on IA
</div>
......@@ -43,7 +43,7 @@ Figure 1. PaddlePaddle on IA
MKL,MKLML以及MKL-DNN三者关系如下表:
| Name | Open Source | License | Descriptions |
|------------|----------------| ------------| --------------|
| :---------- | :--------------- | :---------- | :------------ |
| MKL | No | Proprietary | Accelerate math processing routines |
| MKLML | No | Proprietary | Small package of MKL, especially for Machine Learning |
| MKL-DNN | Yes | Apache 2.0 | Accelerate primitives processing routines especially for Deep Neural Networks |
......@@ -51,7 +51,7 @@ MKL,MKLML以及MKL-DNN三者关系如下表:
MKLML可以与MKL-DNN共同使用,以此达到最好的性能。
<div align="center">
<img src="image/engine.png" width=410><br/>
<img src="image/engine.png"><br/>
Figure 2. PaddlePaddle with MKL Engines
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......@@ -103,7 +103,7 @@ MKL-DNN的库目前只有动态库`libmkldnn.so`。
所以我们定义了一个`MKLDNNMatrix`用于管理MKL-DNN数据的不同格式以及相互之间的转换。
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<img src="image/matrix.png" height=300><br/>
<img src="image/matrix.png"><br/>
Figure 3. MKLDNNMatrix
</div>
......@@ -113,7 +113,7 @@ Figure 3. MKLDNNMatrix
子类只需要使用定义好的接口,实现具体的函数功能即可。
<div align="center">
<img src="image/layers.png" width=410><br/>
<img src="image/layers.png"><br/>
Figure 4. MKLDNNLayer
</div>
......@@ -150,7 +150,7 @@ Figure 4. MKLDNNLayer
所以整体上,在实现每个子类的时候就不需要关心分支的事情了。
<div align="center">
<img src="image/gradients.png" height=300><br/>
<img src="image/gradients.png"><br/>
Figure 5. Merge Gradients
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