180 citations · 196 across the 10 of their papers we have counts for
3 papers · 1 filter
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates
Alex Renda, Yishen Chen, Charith Mendis +1
CPU simulators are useful tools for modeling CPU execution behavior. However, they suffer from inaccuracies due to the cost and complexity of setting their fine-grained parameters,…
TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning
Riyadh Baghdadi, Abdelkader Nadir Debbagh, Kamel Abdous +5
In this paper, we demonstrate a compiler that can optimize sparse and recurrent neural networks, both of which are currently outside of the scope of existing neural network compile…
Comparing Rewinding and Fine-tuning in Neural Network Pruning
Alex Renda, Jonathan Frankle, Michael Carbin
Many neural network pruning algorithms proceed in three steps: train the network to completion, remove unwanted structure to compress the network, and retrain the remaining structu…