distributed

问题 I am currently using memcached with my java app, and overall it's working great. The features of memcached that are most important to me are: it's fast, since reads and writes are in-memory and don't touch the disk it's just a key/value store (since that's all my app needs) it's distributed it uses memory efficiently by having each object live on exactly one server it doesn't assume that the objects are from a database (since my objects are not database objects) However, there is one thing

问题 I got confused about the two concepts: In-graph replication and Between-graph replication when reading the Replicated training in tensorflow\'s official How-to. It\'s said in above link that In-graph replication. In this approach, the client builds a single tf.Graph that contains one set of parameters (in tf.Variable nodes pinned to /job:ps); ... Does this mean there are multiple tf.Graph s in Between-graph replication approach? If yes, where are the corresponding codes in the provided