7 citations · 23 across the 8 of their papers we have counts for
3 papers · 1 filter
Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search
Sławomir Kierat, Mateusz Sieniawski, Denys Fridman +4
We propose three novel pruning techniques to improve the cost and results of inference-aware Differentiable Neural Architecture Search (DNAS). First, we introduce Prunode, a stocha…
Pay Attention when Required
Swetha Mandava, Szymon Migacz, Alex Fit Florea
Transformer-based models consist of interleaved feed-forward blocks - that capture content meaning, and relatively more expensive self-attention blocks - that capture context meani…
Optimizing Multi-GPU Parallelization Strategies for Deep Learning Training
Saptadeep Pal, Eiman Ebrahimi, Arslan Zulfiqar +5
Deploying deep learning (DL) models across multiple compute devices to train large and complex models continues to grow in importance because of the demand for faster and more freq…