There has been significant progress in developing neural network
archite...
Deep neural networks (DNNs) have grown exponentially in complexity and s...
Training Deep Neural Networks (DNNs) is a widely popular workload in bot...
Large language models have led to state-of-the-art accuracies across a r...
Specialized accelerators such as GPUs, TPUs, FPGAs, and custom ASICs hav...
Training Deep Neural Networks (DNNs) is resource-intensive and
time-cons...
Modern machine learning workloads use large models, with complex structu...
Many state-of-the-art results in domains such as NLP and computer vision...
Modern deep neural network (DNN) training jobs use complex and heterogen...
Model parameter synchronization across GPUs introduces high overheads fo...
Many large-scale machine learning (ML) applications need to train ML mod...
Modern distributed machine learning (ML) training workloads benefit
sign...
With widespread advances in machine learning, a number of large enterpri...
PipeDream is a Deep Neural Network(DNN) training system for GPUs that
pa...
Distributed deep neural network (DDNN) training constitutes an increasin...
The recent popularity of deep neural networks (DNNs) has generated a lot...
Most work in the deep learning systems community has focused on faster
i...