The day started with a team meeting between interns. After the meeting, I continued my ECL learning journey. In the afternoon, we had a Keras walkthrough by Roger. After that, I did a couple of required security training.
Poster contents Background Deep learning implementation demands are rising in various fields, including manufacturing, medicine, art, history, etc. The high demand for powerful graphics cards has led to shortages. Generalized Neural Network (GNN) being one of the choices for distributed neural network training; we want to improve it to have better control over machine utilization and optimize its performance. Within GNN, during backpropagation, the time required for each iteration is equal to the time for the weakest node due to the aggregation of loss required at the end of every iteration Research Questions Can we improve resource usage reduce training time required for deep neural network training using the more powerful machine? Method Adopted the notion of training with a restricted node count Enhanced the Fit function to accommodate nodeNumber parameter. Extracted data aligned with the chosen node count. Conducted training and weight synchronization on chosen nodes. Redistributed...
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