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 # ParallelTrainMethod
 
-What is the best way to train parallely. 
\ No newline at end of file
+What is the best way to train parallely. 
+The most common way to train model in parallel is shared weight gradient.
+Is this way the most efficient way? 
+This repository want to research the several way with physical insight. 
+
+## Introduction
+For the single model training, model weight moves like random walk with SGD optimizer.
+So, the train procedure is actually random target search with multiple target. 
+
+For the case of parallel model training, shared weight gradient can be handled as the interaction between agents. 
+In this case, the problem is multiple agents random target search with interaction. 
+
+In general, the search behavior depends on
+- Domain: Topology of Weight space
+- Random walk behavior: Gaussian, Levy walk, Active particle etc
+- Potential
+    - Global: Loss function
+    - Pairwise: Interaction between agents
+- Etc
+    - Initial configuration
+    - Restart rate
+
+I will investigate the efficiency of model training among those variables.