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RaViTT: Random Vision Transformer Tokens
Results show that RaViTT increases the accuracy of the baseline in all datasets and outperforms the SOTA augmentation techniques in 3 out of 4 datasets by a significant margin +1. 23% to +4. 32%.
Analyzing GPU Tensor Core Potential for Fast Reductions
The Nvidia GPU architecture has introduced new computing elements such as the \textit{tensor cores}, which are special processing units dedicated to perform fast matrix-multiply-accumulate (MMA) operations and accelerate \textit{Deep Learning} applications.
Distributed, Parallel, and Cluster Computing
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