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75856ec3
编写于
8月 29, 2017
作者:
H
Helin Wang
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doc/design/ops/dist_train.md
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@@ -2,8 +2,8 @@
## Abstract
We propose an approach to implment the parameter server. In this
approach, there is no fund
i
mental difference between the trainer and
We propose an approach to impl
e
ment the parameter server. In this
approach, there is no fund
a
mental difference between the trainer and
the parameter server: they both run sub-graphs, but sub-graphs of
different purposes.
...
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@@ -16,7 +16,7 @@ trainer and the parameter server.
It would be great if we can write code once and use them on both the
trainer and the parameter server: reduces code duplication and
improves extensibility. Given
during
the current refactor, we are
improves extensibility. Given
that after
the current refactor, we are
representing everything as a computing graph on the
trainer. Representing everything as a computing graph on the parameter
server becomes a natural extension.
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@@ -25,8 +25,8 @@ server becomes a natural extension.
### Graph Converter
The
*graph converter*
converts
user-defined operation (OP) graph into
sub-graphs to be scheduled on different nodes.
The
*graph converter*
converts
the user-defined operation (OP) graph
into
sub-graphs to be scheduled on different nodes.
1.
The user-defined OP graph will be cut into sub-graphs of
different purposes (e.g., trainer, parameter server) to run on
...
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@@ -66,7 +66,7 @@ After converting:
a subgraph.
-
No more duplication logic inside the trainer and the parameter
server in the background section.
server
mentioned
in the background section.
### Challenges
...
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