Added convergence speed comparison at 1000 nodes

main.tex

@@ -367,8 +367,16 @@ We solve this problem by decoupling the gradient averaging from the weight avera
 % python ../../../learn-topology/tools/plot_convergence.py 1-node-iid/all/2021-03-10-09:20:03-CET fully-connected/all/2021-03-10-09:25:19-CET clique-ring/all/2021-03-10-18:14:35-CET fully-connected-cliques/all/2021-03-10-10:19:44-CET --add-min-max --yaxis test-accuracy --labels '1-node IID bsz=12800' '100-nodes non-IID fully-connected bsz=128' '100-nodes non-IID D-Cliques (Ring) bsz=128' '100-nodes non-IID D-Cliques (Fully-Connected) bsz=128' --legend 'lower right' --ymin 85 --ymax 92.5 --save-figure ../../figures/d-cliques-mnist-vs-1-node-test-accuracy.png
          \centering
          \includegraphics[width=0.7\textwidth]{figures/d-cliques-mnist-vs-1-node-test-accuracy}
-         \caption{\label{fig:d-cliques-mnist-linear-w-clique-averaging-w-initial-averaging} MNIST: D-Cliques Convergence Speed}
+         \caption{\label{fig:d-cliques-mnist-linear-w-clique-averaging-w-initial-averaging} MNIST: D-Cliques Convergence Speed (100 nodes)}
         \end{figure}
+        
+ % To regenerate the figure, from directory results/mnist
+ % python ../../../learn-topology/tools/plot_convergence.py 1-node-iid/all/2021-03-10-09:20:03-CET ../scaling/1000/mnist/fully-connected-cliques/all/2021-03-14-17:56:26-CET ../scaling/1000/mnist/smallworld-logn-cliques/all/2021-03-23-21:45:39-CET ../scaling/1000/mnist/fractal-cliques/all/2021-03-14-17:41:59-CET ../scaling/1000/mnist/clique-ring/all/2021-03-13-18:22:36-CET     --add-min-max --yaxis test-accuracy --legend 'lower right' --ymin 84 --ymax 92.5 --labels '1 node IID'  'd-cliques (fully-connected cliques)' 'd-cliques (smallworld)' 'd-cliques (fractal)' 'd-cliques (ring)'  --save-figure ../../figures/d-cliques-mnist-1000-nodes-comparison.png
+             \begin{figure}[htbp]
+     \centering
+            \includegraphics[width=0.7\textwidth]{figures/d-cliques-mnist-1000-nodes-comparison}
+             \caption{\label{fig:d-cliques-mnist-1000-nodes-comparison} MNIST: D-Clique Convergence Speed  (1000 nodes)}
+     \end{figure}
      
     \begin{figure}[htbp]
      \centering
@@ -527,7 +535,28 @@ In addition, it is important that all nodes are initialized with the same model
          \includegraphics[width=\textwidth]{figures/d-cliques-cifar10-vs-1-node-test-accuracy}
 \caption{\label{fig:d-cliques-cifar10-test-accuracy}  Test Accuracy}
      \end{subfigure}
-\caption{\label{fig:d-cliques-cifar10-convolutional} D-Cliques with Convolutional Network on CIFAR10.}
+\caption{\label{fig:d-cliques-cifar10-convolutional} D-Cliques Convergence Speed with Convolutional Network on CIFAR10 (100 nodes).}
+\end{figure}
+
+
+\begin{figure}[htbp]
+     \centering
+          % To regenerate the figure, from directory results/cifar10
+% python ../../../learn-topology/tools/plot_convergence.py 1-node-iid/all/2021-03-10-13:52:58-CET ../scaling/1000/cifar10/fully-connected-cliques/all/2021-03-14-17:41:20-CET ../scaling/1000/cifar10/fractal-cliques/all/2021-03-14-17:42:46-CET ../scaling/1000/cifar10/clique-ring/all/2021-03-14-09:55:24-CET  --add-min-max --yaxis training-loss --labels '1-node IID' 'd-cliques (fully-connected cliques)' 'd-cliques (fractal)' 'd-cliques (ring)' --legend 'upper right'  --ymax 3 --save-figure ../../figures/d-cliques-cifar10-1000-vs-1-node-training-loss.png
+     \begin{subfigure}[b]{0.48\textwidth}
+         \centering
+         \includegraphics[width=\textwidth]{figures/d-cliques-cifar10-1000-vs-1-node-training-loss}
+\caption{\label{fig:d-cliques-cifar10-1000-vs-1-node-training-loss} Training Loss}
+     \end{subfigure}
+     \hfill
+     % To regenerate the figure, from directory results/cifar10
+% python ../../../learn-topology/tools/plot_convergence.py 1-node-iid/all/2021-03-10-13:52:58-CET ../scaling/1000/cifar10/fully-connected-cliques/all/2021-03-14-17:41:20-CET ../scaling/1000/cifar10/fractal-cliques/all/2021-03-14-17:42:46-CET ../scaling/1000/cifar10/clique-ring/all/2021-03-14-09:55:24-CET  --add-min-max --yaxis test-accuracy --labels '1-node IID' 'd-cliques (fully-connected cliques)' 'd-cliques (fractal)' 'd-cliques (ring)' --legend 'lower right' --save-figure ../../figures/d-cliques-cifar10-1000-vs-1-node-test-accuracy.png
+     \begin{subfigure}[b]{0.48\textwidth}
+         \centering
+         \includegraphics[width=\textwidth]{figures/d-cliques-cifar10-1000-vs-1-node-test-accuracy}
+\caption{\label{fig:d-cliques-cifar10-1000-vs-1-node-test-accuracy}  Test Accuracy}
+     \end{subfigure}
+\caption{\label{fig:d-cliques-cifar10-convolutional} D-Cliques Convergence Speed with Convolutional Network on CIFAR10 (1000 nodes).}
 \end{figure}