diff --git a/doc/design/mkldnn/README.MD b/doc/design/mkldnn/README.MD index 287ee620e1228508d4f2cec9c6d6957745b18626..61d453de243c25defc56161641bc4a888a88a3b7 100644 --- a/doc/design/mkldnn/README.MD +++ b/doc/design/mkldnn/README.MD @@ -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。
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Figure 1. PaddlePaddle on IA
@@ -42,16 +42,16 @@ 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 | +| 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 | MKLML可以与MKL-DNN共同使用,以此达到最好的性能。
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Figure 2. PaddlePaddle with MKL Engines
@@ -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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Figure 3. MKLDNNMatrix
@@ -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。
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Figure 4. MKLDNNLayer
@@ -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。
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Figure 5. Merge Gradients
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