Variation of CIFAR10 with 1 class/node

mlsys2022style/appendix.tex

@@ -424,7 +424,7 @@ We provide comments only if the results deviate substantially.
 
 % From directory 'results-v2':
 % MNIST
-% python $TOOLS/analyze/filter.py all --dataset:name mnist --topology:name d-cliques/greedy-swap --nodes:name 2-shards-uneq-classes --meta:seed 1 --nodes:nb-nodes 100 | python $TOOLS/analyze/diff.py
+% python $TOOLS/analyze/filter.py all --dataset:name mnist --topology:name d-cliques/ideal --nodes:name max-local-skew --meta:seed 1 --nodes:nb-nodes 100 | python $TOOLS/analyze/diff.py
 % python $TOOLS/analyze/diff.py --rundirs all/2021-09-29-03:52:47-CEST-labostrex118 all/2021-09-28-23:18:40-CEST-labostrex118 --pass-through | python $TOOLS/plot/convergence.py --add-min-max --ymin 89 --ymax 92.5 --yaxis test-accuracy --labels 'd-cliques (fc) w/o c-avg.' 'd-cliques (fc) w/ c-avg.' --save-figure ../mlsys2022style/figures/convergence-speed-mnist-dc-no-c-avg-vs-c-avg-1-class-per-node.png --linestyles 'solid' 'dashed' --font-size 18 --linewidth 2.5
 \begin{figure}[htbp]
          \centering
@@ -432,6 +432,29 @@ We provide comments only if the results deviate substantially.
 \caption{\label{fig:d-clique-mnist-clique-avg-1-class-per-node} Effect of Clique Averaging on MNIST on 100 nodes. Y axis starts at 89. (Variation of \autoref{fig:d-clique-mnist-clique-avg} with balanced classes and 1 class/node).}
 \end{figure}
 
+% CIFAR10
+%  python $TOOLS/analyze/filter.py all --dataset:name cifar10 --topology:name d-cliques/greedy-swap --nodes:name 2-shards-eq-classes --meta:seed 1 --nodes:nb-nodes 100 | python $TOOLS/analyze/diff.py
+% w/o Clique Averaging
+% python $TOOLS/analyze/diff.py --rundirs all/2021-10-03-23:22:09-CEST-labostrex118 all/2021-10-04-02:50:28-CEST-labostrex118 --pass-through | python $TOOLS/plot/convergence.py --add-min-max --ymin 0 --ymax 100 --yaxis test-accuracy --labels 'd-cliques (fc) w/o momentum' 'd-cliques (fc) w/ momentum' --save-figure ../mlsys2022style/figures/convergence-speed-cifar10-wo-c-avg-no-mom-vs-mom-1-class-per-node.png --linestyles 'solid' 'dashed' --font-size 18 --linewidth 3
+% w/ Clique Averaging
+% python $TOOLS/analyze/diff.py --rundirs all/2021-10-03-16:11:33-CEST-labostrex118 all/2021-10-03-19:45:14-CEST-labostrex118 --pass-through | python $TOOLS/plot/convergence.py --add-min-max --ymin 0 --ymax 100 --yaxis test-accuracy --labels 'd-cliques (fc) w/o momentum' 'd-cliques (fc) w/ momentum' --save-figure ../mlsys2022style/figures/convergence-speed-cifar10-w-c-avg-no-mom-vs-mom-1-class-per-node.png --linestyles 'solid' 'dashed' --font-size 18 --linewidth 3 --legend 'lower right'
+\begin{figure}[htbp]
+    \centering        
+    \begin{subfigure}[b]{0.23\textwidth}
+    \centering
+    \includegraphics[width=\textwidth]{figures/convergence-speed-cifar10-wo-c-avg-no-mom-vs-mom-1-class-per-node}
+    \caption{\label{fig:convergence-speed-cifar10-wo-c-avg-no-mom-vs-mom-1-class-per-node} Without Clique Averaging }
+    \end{subfigure}
+    \hfill
+    \begin{subfigure}[b]{0.23\textwidth}
+    \centering
+    \includegraphics[width=\textwidth]{figures/convergence-speed-cifar10-w-c-avg-no-mom-vs-mom-1-class-per-node}
+    \caption{\label{fig:convergence-speed-cifar10-w-c-avg-no-mom-vs-mom-1-class-per-node} With Clique Averaging}
+    \end{subfigure}
+\caption{\label{fig:cifar10-c-avg-momentum-1-class-per-node} Effect of Clique Averaging and
+Momentum on CIFAR10 with LeNet on 100 nodes (Variation of \autoref{fig:cifar10-c-avg-momentum} with 1 class/node).}
+\end{figure}
+
 
 
 % From directory 'results-v2':