57 citations · 110 across the 6 of their papers we have counts for
6 papers
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case
Florian Rehm, Sofia Vallecorsa, Vikram Saletore +5
Deep learning is finding its way into high energy physics by replacing traditional Monte Carlo simulations. However, deep learning still requires an excessive amount of computation…
DeepGalaxy: Deducing the Properties of Galaxy Mergers from Images Using Deep Neural Networks
Maxwell X. Cai, Jeroen Bédorf, Vikram A. Saletore +4
Galaxy mergers, the dynamical process during which two galaxies collide, are among the most spectacular phenomena in the Universe. During this process, the two colliding galaxies a…
Training Multiscale-CNN for Large Microscopy Image Classification in One Hour
Kushal Datta, Imtiaz Hossain, Sun Choi +4
Existing approaches to train neural networks that use large images require to either crop or down-sample data during pre-processing, use small batch sizes, or split the model acros…
Efficient 8-Bit Quantization of Transformer Neural Machine Language Translation Model
Aishwarya Bhandare, Vamsi Sripathi, Deepthi Karkada +4
In this work, we quantize a trained Transformer machine language translation model leveraging INT8/VNNI instructions in the latest Intel Xeon Cascade Lake p…
Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models
Derya Cavdar, Valeriu Codreanu, Can Karakus +11
Neural machine translation - using neural networks to translate human language - is an area of active research exploring new neuron types and network topologies with the goal of dr…
Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train
Valeriu Codreanu, Damian Podareanu, Vikram Saletore
For the past 5 years, the ILSVRC competition and the ImageNet dataset have attracted a lot of interest from the Computer Vision community, allowing for state-of-the-art accuracy to…