Add design doc for lookup remote table in Fluid

doc/fluid/design/dist_train/prefetch_parameter.md

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+# Design Doc: Prefetching Parameter From Parameter Server
+
+## Abstract
+
+We propose an approach to prefetch parameter from Parameter
+Server while distributed training so that Fluid would training
+a model including the large parameter which could not be stored in one
+trainer's memory.
+
+## Background
+
+For an embedding layer, the trainable parameter may be very large and could
+not be stored in one trainer's memory. In Fluid distributed training,
+[Distributed Transpiler](./parameter_server.md#distributed-transpiler) would split every parameter into a number of small
+parameters and stored in Parameter Server, so we could prefetch the parameter
+from the specified Parameter Server according to the input `Ids`.
+
+## Design
+
+This is a feature of Fluid distributed training, maybe you want
+to know [Distributed Architecture](./distributed_architecture.md) and
+[Parameter Server](./parameter_server.md) before reading the following content.
+
+### Partationed Parameter
+
+<img src="src/split_parameter.png" width="400" />
+
+- **Distributed Transpiler** would split the large parameter
+(weight) into some partitioned parameters (weight_0, weight_1, weight_2) as the
+figure above.
+- We could use `round-robin` to distribute the partitioned parameter.
+
+### Prefetching Parameter
+
+<img src="src/prefetch_parameters.png" width="400" />
+
+- `prefetch_rpc` operator would prefetch the parameter from different Parameter
+    Server according with the input `Ids`, we use [SelectedRows](../../../design/selected_rows.md)
+    as the received variable type.
+- `merge_selected_rows` operator would merge the received parameters into one
+    `SelectedRows` variable.
+
+## TODO
+
+- `prefetch_rpc` operator to send rows index and receive SelectedRows variables.
+- `lookup_table` need to support `SelectedRows` variable type as input `Weight`.
+- Async Update, To avoid slow-node, Async update is important for distributed training,
+  we need a design doc and implement it in future.